Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-05-12T10:34:59.134604Z
Paper Citation Record · LEDGER
$\pi^{*}_{0.6}$: a VLA That Learns From Experience
As of 6 August 2026, this Paper Citation Record lists 87 of 87 outbound references and 100 inbound Pith citation observations for arXiv:2511.14759.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-06T06:34:29.942622+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-04T05:46:48.385585Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-05T02:28:24.338817Z
Reference resolution
87 of 87 outbound references displayed
- verified exact35
- verified fuzzy45
- unresolved2
- parse uncertain0
- malformed identifier1
- metadata mismatch4
External citation measurements
0
pith, observed 2026-08-05T02:28:24.338817Z
Outbound references
Observation 5dcd0a3f-fb95-4417-97d6-22b819deb5dc · outbound
This paper cites MIT press.
$\pi^{*}_{0.6}$: a VLA That Learns From Experience MIT press
Reference 1
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T10:34:59.628520Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation f2239f95-3fb5-48ad-8321-dbd2b30598d7 · outbound
This paper cites Riedmiller.
$\pi^{*}_{0.6}$: a VLA That Learns From Experience Riedmiller
Reference 2
- Resolution
- verified exact
- doi, observed 2026-05-12T10:34:59.202868Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation a8beca63-e9f0-4739-8ca2-675a1853e085 · outbound
This paper cites Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems.
$\pi^{*}_{0.6}$: a VLA That Learns From Experience Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems
Reference 3
- Resolution
- verified exact
- local_arxiv, observed 2026-05-12T10:34:59.242880Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation c674f213-37de-4d0d-bacb-bec5bad07779 · outbound
This paper cites Diffusion Guidance Is a Controllable Policy Improvement Operator.
$\pi^{*}_{0.6}$: a VLA That Learns From Experience Diffusion Guidance Is a Controllable Policy Improvement Operator
Reference 4
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T10:34:59.250729Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation e437fd5b-1f71-4cab-9bd9-9a33ad1c500c · outbound
This paper cites In9th Annual Conference on Robot Learning.
$\pi^{*}_{0.6}$: a VLA That Learns From Experience In9th Annual Conference on Robot Learning
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T10:34:59.640156Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation fa478c9a-afc6-40cc-bcc5-c80fd89d0599 · outbound
This paper cites an unresolved cited work.
$\pi^{*}_{0.6}$: a VLA That Learns From Experience Unresolved cited work
Reference 6
- Resolution
- unresolved
- raw_fallback, observed 2026-05-12T10:34:59.529595Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 12c10b72-88f9-4ac2-8cc5-ff4de9f5fbd4 · outbound
This paper cites A reduction of imitation learning and structured prediction to no-regret online learning.
$\pi^{*}_{0.6}$: a VLA That Learns From Experience A reduction of imitation learning and structured prediction to no-regret online learning
Reference 7
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T10:34:59.525394Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 63c05c4a-f4c5-4ae9-9545-65a8bf51f63f · outbound
This paper cites Shiv: Reducing supervisor burden in dagger using support vectors for efficient learning from demonstrations in high dimensional state spaces.
$\pi^{*}_{0.6}$: a VLA That Learns From Experience Shiv: Reducing supervisor burden in dagger using support vectors for efficient learning from demonstrations in high dimensional state spaces
Reference 8
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T10:34:59.620826Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 33adf923-a9f3-4145-8b09-b9e428f2244d · outbound
This paper cites In: 2016 IEEE International Conference on Robotics and Automation, pp.
$\pi^{*}_{0.6}$: a VLA That Learns From Experience In: 2016 IEEE International Conference on Robotics and Automation, pp
Reference 9
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-12T10:34:59.184958Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation f7eb68c1-41c6-44a2-aec1-1b761dbb3a5f · outbound
This paper cites Dra- gan, and Ken Goldberg.
$\pi^{*}_{0.6}$: a VLA That Learns From Experience Dra- gan, and Ken Goldberg
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T10:34:59.616102Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 10f7c1e5-0b4e-4858-a56c-9f0e7db0931d · outbound
This paper cites Bc-z: Zero-shot task generalization with robotic imitation learning.
$\pi^{*}_{0.6}$: a VLA That Learns From Experience Bc-z: Zero-shot task generalization with robotic imitation learning
Reference 11
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T10:34:59.563569Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation a06ac923-93be-4b52-bcbf-00d503e5f779 · outbound
This paper cites RaC: Robot Learning for Long-Horizon Tasks by Scaling Recovery and Correction.
$\pi^{*}_{0.6}$: a VLA That Learns From Experience RaC: Robot Learning for Long-Horizon Tasks by Scaling Recovery and Correction
Reference 12
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T10:34:59.258097Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 30bf1ff6-c63f-49b3-9388-2e56e7ccbbee · outbound
This paper cites Hg-dagger: Inter- active imitation learning with human experts.
$\pi^{*}_{0.6}$: a VLA That Learns From Experience Hg-dagger: Inter- active imitation learning with human experts
Reference 13
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T10:34:59.539271Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation d8e94625-a3ca-4068-9548-1bd8780f0867 · outbound
This paper cites End-to-end training of deep visuomotor policies.
$\pi^{*}_{0.6}$: a VLA That Learns From Experience End-to-end training of deep visuomotor policies
Reference 14
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T10:34:59.544242Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 0a795517-5ea7-4ca0-922b-cf519cd4f3a5 · outbound
This paper cites QT-Opt: Scalable Deep Reinforcement Learning for Vision-Based Robotic Manipulation.
$\pi^{*}_{0.6}$: a VLA That Learns From Experience QT-Opt: Scalable Deep Reinforcement Learning for Vision-Based Robotic Manipulation
Reference 15
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T10:34:59.265492Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 245d0e33-8e3a-4f39-83f8-c0095b40de9c · outbound
This paper cites Iris: Implicit reinforcement without interaction at scale for learning control from offline robot manipulation data.ICRA.
$\pi^{*}_{0.6}$: a VLA That Learns From Experience Iris: Implicit reinforcement without interaction at scale for learning control from offline robot manipulation data.ICRA
Reference 16
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T10:34:59.553493Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation a4612fd2-75cd-4478-a963-e12d53ba35aa · outbound
This paper cites Ahmed Ahmed Rehaan Ahmad, and Chelsea Finn.
$\pi^{*}_{0.6}$: a VLA That Learns From Experience Ahmed Ahmed Rehaan Ahmad, and Chelsea Finn
Reference 17
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T10:34:59.558379Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 0b5ab1bd-e684-4e94-a076-009a709ce7c0 · outbound
This paper cites ImmFusion: Robust mmWave-RGB Fusion for 3D Human Body Reconstruction in All Weather Conditions.
$\pi^{*}_{0.6}$: a VLA That Learns From Experience ImmFusion: Robust mmWave-RGB Fusion for 3D Human Body Reconstruction in All Weather Conditions
Reference 18
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-12T10:34:59.197814Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation feb8868e-dfd1-4400-be0a-29b092bf2ad3 · outbound
This paper cites Continuously improving mobile manipulation with autonomous real- world rl.
$\pi^{*}_{0.6}$: a VLA That Learns From Experience Continuously improving mobile manipulation with autonomous real- world rl
Reference 19
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T10:34:59.568147Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 6ce860c6-f134-4433-9a46-83bc854ad6ae · outbound
This paper cites Serl: A software suite for sample-efficient robotic reinforcement learning.
$\pi^{*}_{0.6}$: a VLA That Learns From Experience Serl: A software suite for sample-efficient robotic reinforcement learning
Reference 20
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T10:34:59.573045Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 9aa860a1-91ee-41a7-947e-78bd7d88c623 · outbound
This paper cites Residual off-policy rl for finetuning behavior cloning policies.
$\pi^{*}_{0.6}$: a VLA That Learns From Experience Residual off-policy rl for finetuning behavior cloning policies
Reference 21
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T10:34:59.277473Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 08871e90-a466-4c7c-a63d-0d90562e2a38 · outbound
This paper cites 10610948.
Reference 22
- Resolution
- malformed identifier
- arxiv_id, observed 2026-05-12T10:34:59.285013Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 7915e3fe-a197-4270-b62c-5412084809c3 · outbound
This paper cites What Matters for Batch Online Reinforcement Learning in Robotics?.
$\pi^{*}_{0.6}$: a VLA That Learns From Experience What Matters for Batch Online Reinforcement Learning in Robotics?
Reference 23
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T10:34:59.291343Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 8abd7861-ce6c-4201-870a-edd8d0987e0d · outbound
This paper cites Ren, Justin Lidard, Lars Lien Ankile, Anthony Simeonov, Pulkit Agrawal, Anirudha Majumdar, Ben- jamin Burchfiel, Hongkai Dai, and Max Simchowitz.
$\pi^{*}_{0.6}$: a VLA That Learns From Experience Ren, Justin Lidard, Lars Lien Ankile, Anthony Simeonov, Pulkit Agrawal, Anirudha Majumdar, Ben- jamin Burchfiel, Hongkai Dai, and Max Simchowitz
Reference 24
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T10:34:59.591296Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation c7f91144-73d1-4c16-b0c5-a6bb0338e430 · outbound
This paper cites Rl-100: Performant robotic manipulation with real-world reinforcement learning.
$\pi^{*}_{0.6}$: a VLA That Learns From Experience Rl-100: Performant robotic manipulation with real-world reinforcement learning
Reference 25
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T10:34:59.298836Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 78e5e364-1465-43f5-ab5e-307a1dc66238 · outbound
This paper cites Mt-opt: Continuous multi- task robotic reinforcement learning at scale.arXiv.
$\pi^{*}_{0.6}$: a VLA That Learns From Experience Mt-opt: Continuous multi- task robotic reinforcement learning at scale.arXiv
Reference 26
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T10:34:59.602663Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 1c0dd07e-16d1-4e17-bc8e-5406a3eb8608 · outbound
This paper cites Zhao, Vikash Kumar, Aaron Rovinsky, Kelvin Xu, Thomas Devlin, and Sergey Levine.
$\pi^{*}_{0.6}$: a VLA That Learns From Experience Zhao, Vikash Kumar, Aaron Rovinsky, Kelvin Xu, Thomas Devlin, and Sergey Levine
Reference 27
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T10:34:59.606908Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 52fe8996-0e6c-4e63-9037-c81cb7567ed4 · outbound
This paper cites RoboCat: A Self-Improving Generalist Agent for Robotic Manipulation.
$\pi^{*}_{0.6}$: a VLA That Learns From Experience RoboCat: A Self-Improving Generalist Agent for Robotic Manipulation
Reference 28
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T10:34:59.306163Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 9d63d13e-2499-46c3-8d43-496b22386510 · outbound
This paper cites Pre-training for robots: Offline reinforcement learning enables learning new tasks from a handful of trials.
$\pi^{*}_{0.6}$: a VLA That Learns From Experience Pre-training for robots: Offline reinforcement learning enables learning new tasks from a handful of trials
Reference 29
- Resolution
- verified exact
- doi, observed 2026-05-12T10:34:59.190623Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 33e7d781-4892-4a66-b4e3-24285b00a19c · outbound
This paper cites 10610948.
Reference 30
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-12T10:34:59.228044Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 5f6ecec2-6ead-4619-853d-ba97fdcad20f · outbound
This paper cites Interactive Post-Training for Vision-Language-Action Models.
$\pi^{*}_{0.6}$: a VLA That Learns From Experience Interactive Post-Training for Vision-Language-Action Models
Reference 31
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T14:25:47.344448Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 18c063c8-8a2b-4822-85b1-e981fe93cbcf · outbound
This paper cites VLA-RL: Towards Masterful and General Robotic Manipulation with Scalable Reinforcement Learning.
$\pi^{*}_{0.6}$: a VLA That Learns From Experience VLA-RL: Towards Masterful and General Robotic Manipulation with Scalable Reinforcement Learning
Reference 32
- Resolution
- verified exact
- arxiv_id, observed 2026-05-16T12:55:40.591564Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation a31667a7-a6a9-471c-a68e-17e40c2c4aee · outbound
This paper cites What can rl bring to vla generalization? an empirical study.arXiv preprint arXiv:2505.19789.
$\pi^{*}_{0.6}$: a VLA That Learns From Experience What can rl bring to vla generalization? an empirical study.arXiv preprint arXiv:2505.19789
Reference 33
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T10:34:59.325937Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation c86132ea-c38b-4ca5-9eb4-75fb2e0eb079 · outbound
This paper cites pi rl: Online rl fine-tuning for flow-based vision-language-action mod- els.arXiv preprint arXiv:2510.25889.
$\pi^{*}_{0.6}$: a VLA That Learns From Experience pi rl: Online rl fine-tuning for flow-based vision-language-action mod- els.arXiv preprint arXiv:2510.25889
Reference 34
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T10:34:59.334967Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation df616bc2-710d-412b-99d3-f631e51d532e · outbound
This paper cites SimpleVLA-RL: Scaling VLA Training via Reinforcement Learning.
$\pi^{*}_{0.6}$: a VLA That Learns From Experience SimpleVLA-RL: Scaling VLA Training via Reinforcement Learning
Reference 35
- Resolution
- verified exact
- arxiv_id, observed 2026-05-15T08:02:11.500343Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 96f1fb71-e18f-481e-972d-a1fafab88cf6 · outbound
This paper cites Improving Vision-Language-Action Model with Online Reinforcement Learning.
$\pi^{*}_{0.6}$: a VLA That Learns From Experience Improving Vision-Language-Action Model with Online Reinforcement Learning
Reference 36
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T10:34:59.347237Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 2c61e69c-06d0-4bc3-a4a7-24f95a767725 · outbound
This paper cites Self- improving vision-language-action models with data gen- eration via residual rl.
$\pi^{*}_{0.6}$: a VLA That Learns From Experience Self- improving vision-language-action models with data gen- eration via residual rl
Reference 37
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T10:34:59.647039Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 9cd1f206-e1e4-4e35-9094-886b02fa9b09 · outbound
This paper cites ConRFT: A Reinforced Fine-tuning Method for VLA Models via Consistency Policy.
$\pi^{*}_{0.6}$: a VLA That Learns From Experience ConRFT: A Reinforced Fine-tuning Method for VLA Models via Consistency Policy
Reference 38
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T10:34:59.353437Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 609b4a33-52c6-4b10-aecf-d739fcbb9438 · outbound
This paper cites Policy Agnostic RL: Offline RL and Online RL Fine-Tuning of Any Class and Backbone.
$\pi^{*}_{0.6}$: a VLA That Learns From Experience Policy Agnostic RL: Offline RL and Online RL Fine-Tuning of Any Class and Backbone
Reference 39
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T10:34:59.359504Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation b240e196-727f-4d3d-a44f-6d163d7e5038 · outbound
This paper cites Steering your generalists: Improving robotic foundation models via value guidance.
$\pi^{*}_{0.6}$: a VLA That Learns From Experience Steering your generalists: Improving robotic foundation models via value guidance
Reference 40
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T10:34:59.664038Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 2b94fcba-d01d-45a2-92f5-c1861269572d · outbound
This paper cites Align-Then-stEer: Adapting the Vision-Language Action Models through Unified Latent Guidance.
$\pi^{*}_{0.6}$: a VLA That Learns From Experience Align-Then-stEer: Adapting the Vision-Language Action Models through Unified Latent Guidance
Reference 41
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T10:34:59.368442Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 87644b33-10a7-4362-a00a-c8c7bc9e6212 · outbound
This paper cites Steering your diffusion policy with latent space reinforcement learning.
$\pi^{*}_{0.6}$: a VLA That Learns From Experience Steering your diffusion policy with latent space reinforcement learning
Reference 42
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T10:34:59.459439Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 298d2bfe-c995-4e35-9711-a71c32863790 · outbound
This paper cites RLDG: Robotic Generalist Policy Distillation via Reinforcement Learning.
$\pi^{*}_{0.6}$: a VLA That Learns From Experience RLDG: Robotic Generalist Policy Distillation via Reinforcement Learning
Reference 43
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T10:34:59.374709Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation f3d6fb73-8d81-4939-ade9-134f28c319f0 · outbound
This paper cites CO-RFT: Efficient Fine-Tuning of Vision-Language-Action Models through Chunked Offline Reinforcement Learning.
$\pi^{*}_{0.6}$: a VLA That Learns From Experience CO-RFT: Efficient Fine-Tuning of Vision-Language-Action Models through Chunked Offline Reinforcement Learning
Reference 44
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T10:34:59.381175Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 1dd654af-0a47-4061-a394-7a1a3f3bf613 · outbound
This paper cites GRAPE: Generalizing Robot Policy via Preference Alignment.
$\pi^{*}_{0.6}$: a VLA That Learns From Experience GRAPE: Generalizing Robot Policy via Preference Alignment
Reference 45
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T10:34:59.387695Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 6a4a20d1-9c89-4675-9771-3952f454a83e · outbound
This paper cites A vision- language-action-critic model for robotic real-world rein- forcement learning.arXiv preprint arXiv:2509.15937.
$\pi^{*}_{0.6}$: a VLA That Learns From Experience A vision- language-action-critic model for robotic real-world rein- forcement learning.arXiv preprint arXiv:2509.15937
Reference 46
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T10:34:59.393800Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 788af721-76c2-4e37-aba2-3075430651d8 · outbound
This paper cites Self-improving embodied foundation models.
$\pi^{*}_{0.6}$: a VLA That Learns From Experience Self-improving embodied foundation models
Reference 47
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T10:34:59.399105Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 7542ae43-ba7b-45cf-b733-1f13a4991a15 · outbound
This paper cites Reinforcement Learning Upside Down: Don't Predict Rewards -- Just Map Them to Actions.
$\pi^{*}_{0.6}$: a VLA That Learns From Experience Reinforcement Learning Upside Down: Don't Predict Rewards -- Just Map Them to Actions
Reference 48
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T10:34:59.408653Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 334c2d12-73fa-4d3b-9df4-d5254ff8fd4c · outbound
This paper cites Reward-Conditioned Policies.
$\pi^{*}_{0.6}$: a VLA That Learns From Experience Reward-Conditioned Policies
Reference 49
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T10:34:59.416893Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 60020006-bd82-428d-b465-b0999b87336a · outbound
This paper cites Decision transformer: Rein- forcement learning via sequence modeling.
$\pi^{*}_{0.6}$: a VLA That Learns From Experience Decision transformer: Rein- forcement learning via sequence modeling
Reference 50
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T10:34:59.492892Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 74147d76-9be9-4914-bc10-e079fcedf03c · outbound
This paper cites When does return- conditioned supervised learning work for offline rein- forcement learning? InAdvances in Neural Information Processing Systems (NeurIPS) 35.
$\pi^{*}_{0.6}$: a VLA That Learns From Experience When does return- conditioned supervised learning work for offline rein- forcement learning? InAdvances in Neural Information Processing Systems (NeurIPS) 35
Reference 51
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T10:34:59.497502Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 31d3abc4-1555-4f36-87cd-2aec7df1529b · outbound
This paper cites Rvs: What is essential for offline rl via supervised learning? InProceedings of the 10th International Conference on Learning Representations (ICLR).
$\pi^{*}_{0.6}$: a VLA That Learns From Experience Rvs: What is essential for offline rl via supervised learning? InProceedings of the 10th International Conference on Learning Representations (ICLR)
Reference 52
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T10:34:59.501395Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 1636963a-4305-42b9-a179-d85bb12eae5f · outbound
This paper cites Generalized decision transformer for offline hindsight information matching.
$\pi^{*}_{0.6}$: a VLA That Learns From Experience Generalized decision transformer for offline hindsight information matching
Reference 53
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T10:34:59.505991Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 8160b27b-73b1-420d-a612-54682522becb · outbound
This paper cites Q-learning decision transformer: Leveraging dynamic programming for conditional sequence mod- elling in offline rl.
$\pi^{*}_{0.6}$: a VLA That Learns From Experience Q-learning decision transformer: Leveraging dynamic programming for conditional sequence mod- elling in offline rl
Reference 54
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T10:34:59.511141Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 9cd398b2-c4fa-4d0a-83f3-29bbc23202e7 · outbound
This paper cites Online decision transformer.
$\pi^{*}_{0.6}$: a VLA That Learns From Experience Online decision transformer
Reference 55
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T10:34:59.515926Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 73edf8f2-ab91-4ee6-8d2e-1b58ed15f4a4 · outbound
This paper cites Advantage-conditioned diffusion: Offline rl via general- ization.
$\pi^{*}_{0.6}$: a VLA That Learns From Experience Advantage-conditioned diffusion: Offline rl via general- ization
Reference 56
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T10:34:59.520844Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation dc7a5f55-249a-4ef7-8a6e-7287f9caab4b · outbound
This paper cites Elastic decision transformer.
$\pi^{*}_{0.6}$: a VLA That Learns From Experience Elastic decision transformer
Reference 57
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T10:34:59.218576Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 1b47a4de-1ed4-47f8-88e5-30d2dfcae865 · outbound
This paper cites Concept2robot: Learning manipu- lation concepts from instructions and human demonstra- tions.
$\pi^{*}_{0.6}$: a VLA That Learns From Experience Concept2robot: Learning manipu- lation concepts from instructions and human demonstra- tions
Reference 58
- Resolution
- verified exact
- doi, observed 2026-05-12T10:34:59.211955Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 97208df7-d5c7-4075-b661-9248a6a0936d · outbound
This paper cites in-the- wild.
$\pi^{*}_{0.6}$: a VLA That Learns From Experience in-the- wild
Reference 59
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T10:34:59.534382Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 5868eb68-fd47-4081-96e7-3733a3261135 · outbound
This paper cites Learning language- conditioned robot behavior from offline data and crowd- sourced annotation.
$\pi^{*}_{0.6}$: a VLA That Learns From Experience Learning language- conditioned robot behavior from offline data and crowd- sourced annotation
Reference 60
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T10:34:59.548981Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 28565aa5-5f5d-4ca8-9c11-5a0c5e38f1fd · outbound
This paper cites Sontakke, Jesse Zhang, S ´ebastien M.R.
$\pi^{*}_{0.6}$: a VLA That Learns From Experience Sontakke, Jesse Zhang, S ´ebastien M.R
Reference 61
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T10:34:59.577261Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 1079ff25-f206-45dc-998e-a346556f0e0e · outbound
This paper cites Language to rewards for robotic skill synthesis.
$\pi^{*}_{0.6}$: a VLA That Learns From Experience Language to rewards for robotic skill synthesis
Reference 62
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T10:34:59.581726Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation b25b6e64-0c71-4a0d-8e6e-9ce9d0041fa7 · outbound
This paper cites Lim, Jesse Thomason, Erdem Bıyık, and Jesse Zhang.
$\pi^{*}_{0.6}$: a VLA That Learns From Experience Lim, Jesse Thomason, Erdem Bıyık, and Jesse Zhang
Reference 63
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T10:34:59.586493Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 1bf69143-533a-4a3e-8e5a-dc40e515d2e8 · outbound
This paper cites Video-language critic: Transferable reward functions for language-conditioned robotics.Transac- tions on Machine Learning Research, 2025:1–22.
$\pi^{*}_{0.6}$: a VLA That Learns From Experience Video-language critic: Transferable reward functions for language-conditioned robotics.Transac- tions on Machine Learning Research, 2025:1–22
Reference 64
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T10:34:59.598140Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation eb9a043b-8d9c-4cd4-9765-f92ee79e5b02 · outbound
This paper cites Liv: Language-image representations and rewards for robotic control.
$\pi^{*}_{0.6}$: a VLA That Learns From Experience Liv: Language-image representations and rewards for robotic control
Reference 65
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T10:34:59.611605Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 96b606e6-3bd1-4ba6-81f1-6a49dc31a0c9 · outbound
This paper cites Vision language models are in-context value learners.
$\pi^{*}_{0.6}$: a VLA That Learns From Experience Vision language models are in-context value learners
Reference 66
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T10:34:59.624912Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation b251e6ef-ce49-4f58-8b11-b29d2320ae6d · outbound
This paper cites Proximal Policy Optimization Algorithms.
$\pi^{*}_{0.6}$: a VLA That Learns From Experience Proximal Policy Optimization Algorithms
Reference 67
- Resolution
- verified exact
- local_arxiv, observed 2026-05-12T10:34:59.235701Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 212203cb-f019-4248-b4e0-ccf0eb861e57 · outbound
This paper cites Maximum a posteriori policy optimisation.
$\pi^{*}_{0.6}$: a VLA That Learns From Experience Maximum a posteriori policy optimisation
Reference 68
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T10:34:59.632562Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 5e2c454d-e7f1-4db5-8325-b01196157eed · outbound
This paper cites Advantage-Weighted Regression: Simple and Scalable Off-Policy Reinforcement Learning.
$\pi^{*}_{0.6}$: a VLA That Learns From Experience Advantage-Weighted Regression: Simple and Scalable Off-Policy Reinforcement Learning
Reference 69
- Resolution
- verified exact
- local_arxiv, observed 2026-05-12T10:34:59.422852Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 3fffcf59-8ba6-471a-a24b-116aa2c13322 · outbound
This paper cites an unresolved cited work.
$\pi^{*}_{0.6}$: a VLA That Learns From Experience Unresolved cited work
Reference 70
- Resolution
- verified exact
- doi, observed 2026-05-12T10:34:59.207330Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 69649c11-9323-49c3-abe7-5afef49fd71a · outbound
This paper cites Rel- ative entropy policy search.
$\pi^{*}_{0.6}$: a VLA That Learns From Experience Rel- ative entropy policy search
Reference 71
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T10:34:59.643617Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation da2778fd-a054-454f-bc79-3c004ceba287 · outbound
This paper cites Exponentially weighted imitation learning for batched historical data.
$\pi^{*}_{0.6}$: a VLA That Learns From Experience Exponentially weighted imitation learning for batched historical data
Reference 72
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T10:34:59.650399Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation de86c718-e261-440f-9ccd-ce84835fc8eb · outbound
This paper cites A distributional perspective on reinforcement learning.
$\pi^{*}_{0.6}$: a VLA That Learns From Experience A distributional perspective on reinforcement learning
Reference 73
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T10:34:59.659808Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 5e52e2cc-5f9f-4b73-b839-ec2dd811298e · outbound
This paper cites Knowledge insulating vision-language-action models: Train fast, run fast, generalize better.
$\pi^{*}_{0.6}$: a VLA That Learns From Experience Knowledge insulating vision-language-action models: Train fast, run fast, generalize better
Reference 74
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T10:34:59.455997Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 30a3883e-2db7-46e1-b7a4-8605c3f7c401 · outbound
This paper cites Soft actor-critic: Off-policy maximum entropy deep reinforcement learning with a stochastic actor.ICML.
$\pi^{*}_{0.6}$: a VLA That Learns From Experience Soft actor-critic: Off-policy maximum entropy deep reinforcement learning with a stochastic actor.ICML
Reference 75
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T10:34:59.463116Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation c3734c80-8077-4bff-9667-e848fd0f809c · outbound
This paper cites Critic regularized regression.
$\pi^{*}_{0.6}$: a VLA That Learns From Experience Critic regularized regression
Reference 76
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T10:34:59.466649Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation a32ca1de-c36c-459f-a4a8-276481a9e877 · outbound
This paper cites Offline reinforcement learning with implicit q-learning.
$\pi^{*}_{0.6}$: a VLA That Learns From Experience Offline reinforcement learning with implicit q-learning
Reference 77
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T10:34:59.470485Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation ccbfcb12-752d-4658-8525-31dfdc40743c · outbound
This paper cites FAST: Efficient action tok- enization for vision-language-action models.Robotics: Science and Systems.
$\pi^{*}_{0.6}$: a VLA That Learns From Experience FAST: Efficient action tok- enization for vision-language-action models.Robotics: Science and Systems
Reference 78
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T10:34:59.474216Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation ab3e6269-6ed5-4742-a243-a1e7972cffed · outbound
This paper cites an unresolved cited work.
$\pi^{*}_{0.6}$: a VLA That Learns From Experience Unresolved cited work
Reference 79
- Resolution
- unresolved
- raw_fallback, observed 2026-05-12T10:34:59.478607Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 5dbc5840-8bd8-4a10-a4a5-cfd8ed472dab · outbound
This paper cites Flow Matching for Generative Modeling.
$\pi^{*}_{0.6}$: a VLA That Learns From Experience Flow Matching for Generative Modeling
Reference 80
- Resolution
- verified exact
- local_arxiv, observed 2026-05-12T10:34:59.428506Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 3010726f-688c-4e34-91de-673ea3383a76 · outbound
This paper cites Understanding diffu- sion objectives as the elbo with simple data augmenta- tion.
$\pi^{*}_{0.6}$: a VLA That Learns From Experience Understanding diffu- sion objectives as the elbo with simple data augmenta- tion
Reference 81
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T10:34:59.488745Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 01ef8a05-630b-4073-bc33-f59c021e03cc · outbound
This paper cites $\pi_0$: A Vision-Language-Action Flow Model for General Robot Control.
$\pi^{*}_{0.6}$: a VLA That Learns From Experience $\pi_0$: A Vision-Language-Action Flow Model for General Robot Control
Reference 82
- Resolution
- verified exact
- local_arxiv, observed 2026-05-12T10:34:59.433800Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 44e99cfc-de44-4698-b672-c8c86153c0ec · outbound
This paper cites Flow matching policy gradients.
$\pi^{*}_{0.6}$: a VLA That Learns From Experience Flow matching policy gradients
Reference 83
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T10:34:59.483666Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation f3196016-432c-4f6f-bf90-8630c3dea41b · outbound
This paper cites Simple policy optimization.
$\pi^{*}_{0.6}$: a VLA That Learns From Experience Simple policy optimization
Reference 84
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-12T10:34:59.636641Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation adb13b4b-71bd-4495-b751-9bdfe8dba9c1 · outbound
This paper cites The Ingredients of Real-World Robotic Reinforcement Learning.
$\pi^{*}_{0.6}$: a VLA That Learns From Experience The Ingredients of Real-World Robotic Reinforcement Learning
Reference 85
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T10:34:59.439726Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 43626bdb-b668-4803-872b-89dfce2c51de · outbound
This paper cites Autonomous Reinforcement Learning: Formalism and Benchmarking.
$\pi^{*}_{0.6}$: a VLA That Learns From Experience Autonomous Reinforcement Learning: Formalism and Benchmarking
Reference 86
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T10:34:59.446657Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 3c453cca-20f2-4bff-873f-c86d8923f044 · outbound
This paper cites Hi Robot: Open-Ended Instruction Following with Hierarchical Vision-Language-Action Models.
$\pi^{*}_{0.6}$: a VLA That Learns From Experience Hi Robot: Open-Ended Instruction Following with Hierarchical Vision-Language-Action Models
Reference 87
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-15T22:53:37.470313Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Pith citing papers
Observation d656d3fc-cfa3-458f-b907-a720ca3ae3ff · inbound
A Survey on Vision-Language-Action Models for Embodied AI cites this paper.
A Survey on Vision-Language-Action Models for Embodied AI $\pi^{*}_{0.6}$: a VLA That Learns From Experience
Reference 19
- Resolution
- verified exact
- local_arxiv, observed 2026-05-24T01:25:54.273628Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation b700710a-bf86-40f9-b41a-f96b56b5d410 · inbound
PALM: Progress-Aware Policy Learning via Affordance Reasoning for Long-Horizon Robotic Manipulation cites this paper.
PALM: Progress-Aware Policy Learning via Affordance Reasoning for Long-Horizon Robotic Manipulation $\pi^{*}_{0.6}$: a VLA That Learns From Experience
Reference 44
- Resolution
- verified exact
- local_arxiv, observed 2026-05-16T15:08:01.701442Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 069f214e-bc61-41d4-9ce6-5dce93bd9be7 · inbound
TouchGuide: Inference-Time Steering of Visuomotor Policies via Touch Guidance cites this paper.
TouchGuide: Inference-Time Steering of Visuomotor Policies via Touch Guidance $\pi^{*}_{0.6}$: a VLA That Learns From Experience
Reference 31
- Resolution
- verified exact
- local_arxiv, observed 2026-05-16T11:07:47.840570Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 492e2bcf-f89e-435b-ad68-3c7b5935f288 · inbound
Language Movement Primitives: Grounding Language Models in Robot Motion cites this paper.
Language Movement Primitives: Grounding Language Models in Robot Motion $\pi^{*}_{0.6}$: a VLA That Learns From Experience
Reference 21
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T05:17:28.099404Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 456df98f-5d2b-4699-af17-2cc0c13daf57 · inbound
World-VLA-Loop: Closed-Loop Learning of Video World Model and VLA Policy cites this paper.
World-VLA-Loop: Closed-Loop Learning of Video World Model and VLA Policy $\pi^{*}_{0.6}$: a VLA That Learns From Experience
Reference 9
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T03:56:47.154587Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 08c15000-9bea-496d-bf00-ab0ec2c4dfe4 · inbound
Action-to-Action Flow Matching cites this paper.
Action-to-Action Flow Matching $\pi^{*}_{0.6}$: a VLA That Learns From Experience
Reference 8
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-05-16T06:57:29.225522Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation bd027e24-351f-4214-a143-d25652b4c97a · inbound
Self-Supervised Bootstrapping of Action-Predictive Embodied Reasoning cites this paper.
Self-Supervised Bootstrapping of Action-Predictive Embodied Reasoning $\pi^{*}_{0.6}$: a VLA That Learns From Experience
Reference 10
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-05-21T14:04:11.970546Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 5399d154-392f-4eac-9870-fa665a2caff4 · inbound
Combined Constrained Sampling and Reinforcement Learning for Robotic Manipulation cites this paper.
Combined Constrained Sampling and Reinforcement Learning for Robotic Manipulation $\pi^{*}_{0.6}$: a VLA That Learns From Experience
Reference 26
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T03:18:42.039197Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 14a13e2d-bc73-4c3e-9803-cb92aa2eaca7 · inbound
SERNF: Sample-Efficient Real-World Dexterous Policy Fine-Tuning via Action-Chunked Critics and Normalizing Flows cites this paper.
SERNF: Sample-Efficient Real-World Dexterous Policy Fine-Tuning via Action-Chunked Critics and Normalizing Flows $\pi^{*}_{0.6}$: a VLA That Learns From Experience
Reference 24
- Resolution
- verified exact
- local_arxiv, observed 2026-05-16T03:37:13.860172Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 30299ff5-a561-4b6e-865d-6883cb23ea8c · inbound
SERNF: Sample-Efficient Real-World Dexterous Policy Fine-Tuning via Action-Chunked Critics and Normalizing Flows cites this paper.
SERNF: Sample-Efficient Real-World Dexterous Policy Fine-Tuning via Action-Chunked Critics and Normalizing Flows $\pi^{*}_{0.6}$: a VLA That Learns From Experience
Reference 23
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T02:53:16.108040Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 71bb122c-598e-466f-81fd-07ce3b3ed833 · inbound
RISE: Self-Improving Robot Policy with Compositional World Model cites this paper.
RISE: Self-Improving Robot Policy with Compositional World Model $\pi^{*}_{0.6}$: a VLA That Learns From Experience
Reference 2
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-05-16T02:30:32.143070Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 65c3e564-9f56-4902-ac84-9ac87c0dd074 · inbound
Beyond Imitation: Reinforcement Learning-Based Sim-Real Co-Training for VLA Models cites this paper.
Beyond Imitation: Reinforcement Learning-Based Sim-Real Co-Training for VLA Models $\pi^{*}_{0.6}$: a VLA That Learns From Experience
Reference 29
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T23:48:57.949446Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6ec06c83-7a1b-4938-b7b9-d086d9509fb2 · inbound
ALOE: Action-Level Off-Policy Evaluation for Vision-Language-Action Model Post-Training cites this paper.
ALOE: Action-Level Off-Policy Evaluation for Vision-Language-Action Model Post-Training $\pi^{*}_{0.6}$: a VLA That Learns From Experience
Reference 14
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T23:47:55.179001Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation fb9fa478-13d0-4ec9-b9ca-ca2f7c7e2e85 · inbound
VLANeXt: Recipes for Building Strong VLA Models cites this paper.
VLANeXt: Recipes for Building Strong VLA Models $\pi^{*}_{0.6}$: a VLA That Learns From Experience
Reference 17
- Resolution
- verified exact
- local_arxiv, observed 2026-05-21T13:00:09.863649Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 0dc9129e-996e-4fcf-9081-d6df4b8aefca · inbound
TOPReward: Token Probabilities as Hidden Zero-Shot Rewards for Robotics cites this paper.
TOPReward: Token Probabilities as Hidden Zero-Shot Rewards for Robotics $\pi^{*}_{0.6}$: a VLA That Learns From Experience
Reference 14
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T21:43:07.989656Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation fc8a87a6-2d43-4351-a88b-8e605df661b5 · inbound
PhysMem: Scaling Test-Time Memory for Embodied Physical Reasoning cites this paper.
PhysMem: Scaling Test-Time Memory for Embodied Physical Reasoning $\pi^{*}_{0.6}$: a VLA That Learns From Experience
Reference 47
- Resolution
- verified exact
- local_arxiv, observed 2026-05-15T20:06:33.769825Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 2e410113-341d-4f7c-84b7-7cda7ac62ed0 · inbound
RMBench: Memory-Dependent Robotic Manipulation Benchmark with Insights into Policy Design cites this paper.
RMBench: Memory-Dependent Robotic Manipulation Benchmark with Insights into Policy Design $\pi^{*}_{0.6}$: a VLA That Learns From Experience
Reference 6
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T19:42:46.514018Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation cf568421-15ba-4304-824e-22bb63730f5c · inbound
Robometer: Scaling General-Purpose Robotic Reward Models via Trajectory Comparisons cites this paper.
Robometer: Scaling General-Purpose Robotic Reward Models via Trajectory Comparisons $\pi^{*}_{0.6}$: a VLA That Learns From Experience
Reference 59
- Resolution
- verified exact
- local_arxiv, observed 2026-05-15T18:00:12.574856Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 701392f9-6ab7-48d0-9f4f-c19492a94438 · inbound
CoFL: Continuous Flow Fields for Language-Conditioned Navigation cites this paper.
CoFL: Continuous Flow Fields for Language-Conditioned Navigation $\pi^{*}_{0.6}$: a VLA That Learns From Experience
Reference 31
- Resolution
- verified exact
- local_arxiv, observed 2026-05-15T17:20:10.476539Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 3df4d643-291c-4e93-a3ba-19629da9680a · inbound
Optimization landscapes of variational quantum algorithms cites this paper.
Optimization landscapes of variational quantum algorithms $\pi^{*}_{0.6}$: a VLA That Learns From Experience
Reference 11
- Resolution
- unresolved
- no resolver link, observed 2026-07-15T14:44:57.978537Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation bcb4c41c-a3cd-4f7d-9ba7-bd8c7bbb1db9 · inbound
Safe-Night VLA: Seeing the Unseen via Thermal-Perceptive Vision-Language-Action Models for Safety-Critical Manipulation cites this paper.
Safe-Night VLA: Seeing the Unseen via Thermal-Perceptive Vision-Language-Action Models for Safety-Critical Manipulation $\pi^{*}_{0.6}$: a VLA That Learns From Experience
Reference 2025
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T18:44:43.510752Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ac17d9de-4eea-4839-91d7-f606ebe49032 · inbound
GeMPO: Generalized Measure Matching for Online Diffusion Reinforcement Learning cites this paper.
GeMPO: Generalized Measure Matching for Online Diffusion Reinforcement Learning $\pi^{*}_{0.6}$: a VLA That Learns From Experience
Reference 39
- Resolution
- unresolved
- no resolver link, observed 2026-07-14T23:47:45.866615Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 106e493e-314a-41a6-86f7-e14ec4c7fae0 · inbound
You've Got a Golden Ticket: Improving Generative Robot Policies With A Single Noise Vector cites this paper.
You've Got a Golden Ticket: Improving Generative Robot Policies With A Single Noise Vector $\pi^{*}_{0.6}$: a VLA That Learns From Experience
Reference 12
- Resolution
- verified exact
- local_arxiv, observed 2026-05-15T09:55:24.225788Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation e425baf7-6393-4ef6-8402-519b01ff1be0 · inbound
Simulation Distillation: Pretraining World Models in Simulation for Rapid Real-World Adaptation cites this paper.
Simulation Distillation: Pretraining World Models in Simulation for Rapid Real-World Adaptation $\pi^{*}_{0.6}$: a VLA That Learns From Experience
Reference 19
- Resolution
- verified exact
- local_arxiv, observed 2026-05-15T09:49:54.496767Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation beedb161-72f4-4344-9bc6-d192029c325e · inbound
MemoAct: Atkinson-Shiffrin-Inspired Hierarchical Memory-Augmented Policy for Robotic Manipulation cites this paper.
MemoAct: Atkinson-Shiffrin-Inspired Hierarchical Memory-Augmented Policy for Robotic Manipulation $\pi^{*}_{0.6}$: a VLA That Learns From Experience
Reference 1
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T05:46:48.385585Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation cdd44350-9566-4b35-944f-ee1a87cc6dd6 · inbound
FASTER: Rethinking Real-Time Flow VLAs cites this paper.
FASTER: Rethinking Real-Time Flow VLAs $\pi^{*}_{0.6}$: a VLA That Learns From Experience
Reference 31
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-05-15T08:05:15.387111Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 9254c69b-ab9d-40f5-b1eb-c3e4d4f0f9e3 · inbound
FASTER: Rethinking Real-Time Flow VLAs cites this paper.
FASTER: Rethinking Real-Time Flow VLAs $\pi^{*}_{0.6}$: a VLA That Learns From Experience
Reference 31
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-05-21T10:50:01.094248Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation ba0b2f20-8946-4f9b-b859-3408db88f193 · inbound
SOLE-R1: Video-Language Reasoning as the Sole Reward for On-Robot Reinforcement Learning cites this paper.
SOLE-R1: Video-Language Reasoning as the Sole Reward for On-Robot Reinforcement Learning $\pi^{*}_{0.6}$: a VLA That Learns From Experience
Reference 19
- Resolution
- unresolved
- no resolver link, observed 2026-07-13T16:10:12.689957Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 341318fb-f226-41d3-9cae-558f220d78dc · inbound
Open-Loop Planning, Closed-Loop Verification: Speculative Verification for VLA cites this paper.
Open-Loop Planning, Closed-Loop Verification: Speculative Verification for VLA $\pi^{*}_{0.6}$: a VLA That Learns From Experience
Reference 10
- Resolution
- verified exact
- local_arxiv, observed 2026-05-13T19:48:11.455634Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 27d0a391-d7f8-447b-98d2-0124304f98fe · inbound
ARM: Advantage Reward Modeling for Long-Horizon Manipulation cites this paper.
ARM: Advantage Reward Modeling for Long-Horizon Manipulation $\pi^{*}_{0.6}$: a VLA That Learns From Experience
Reference 12
- Resolution
- verified exact
- local_arxiv, observed 2026-05-13T19:28:09.926570Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 099112c4-1561-49ef-aabf-015a9e4faecd · inbound
Redefining End-of-Life: Intelligent Automation for Electronics Remanufacturing Systems cites this paper.
Redefining End-of-Life: Intelligent Automation for Electronics Remanufacturing Systems $\pi^{*}_{0.6}$: a VLA That Learns From Experience
Reference 134
- Resolution
- verified exact
- local_arxiv, observed 2026-05-13T19:23:09.520029Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 1da0bcd2-2a79-413e-9c2c-9f66411ef23b · inbound
Multi-View Video Diffusion Policy: A 3D Spatio-Temporal-Aware Video Action Model cites this paper.
Multi-View Video Diffusion Policy: A 3D Spatio-Temporal-Aware Video Action Model $\pi^{*}_{0.6}$: a VLA That Learns From Experience
Reference 1
- Resolution
- verified exact
- local_arxiv, observed 2026-05-13T18:58:08.855870Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation d6d35575-9365-4cbc-bc1a-8c7c767b4f5a · inbound
E-VLA: Event-Augmented Vision-Language-Action Model for Dark and Blurred Scenes cites this paper.
E-VLA: Event-Augmented Vision-Language-Action Model for Dark and Blurred Scenes $\pi^{*}_{0.6}$: a VLA That Learns From Experience
Reference 26
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-10T22:00:48.378858Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation f2cb6e96-cc98-47ee-825b-4ea282c16191 · inbound
CoEnv: Driving Embodied Multi-Agent Collaboration via Compositional Environment cites this paper.
CoEnv: Driving Embodied Multi-Agent Collaboration via Compositional Environment $\pi^{*}_{0.6}$: a VLA That Learns From Experience
Reference 22
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-10T22:55:52.412697Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 96cc6f07-83ad-4ed4-912b-311ad1d1a9c0 · inbound
Action Images: End-to-End Policy Learning via Multiview Video Generation cites this paper.
Action Images: End-to-End Policy Learning via Multiview Video Generation $\pi^{*}_{0.6}$: a VLA That Learns From Experience
Reference 21
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-10T23:50:53.514156Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 28bb7d2c-38e4-4ca0-8c27-16dead3fbd92 · inbound
ViVa: A Video-Generative Value Model for Robot Reinforcement Learning cites this paper.
ViVa: A Video-Generative Value Model for Robot Reinforcement Learning $\pi^{*}_{0.6}$: a VLA That Learns From Experience
Reference 16
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-11T07:25:59.082501Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation aa38d91c-7794-46a2-a4ea-787c90f77b9c · inbound
Activation Steering for Aligned Open-ended Generation without Sacrificing Coherence cites this paper.
Activation Steering for Aligned Open-ended Generation without Sacrificing Coherence $\pi^{*}_{0.6}$: a VLA That Learns From Experience
Reference 17
- Resolution
- unresolved
- no resolver link, observed 2026-07-13T00:03:53.609175Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d040512f-ed95-4966-8cc8-6cd42c87e1fa · inbound
VAG: Dual-Stream Video-Action Generation for Embodied Data Synthesis cites this paper.
VAG: Dual-Stream Video-Action Generation for Embodied Data Synthesis $\pi^{*}_{0.6}$: a VLA That Learns From Experience
Reference 27
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T07:11:01.142615Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 60535b7f-9c12-4054-9027-6c34510a347d · inbound
ScoRe-Flow: Complete Distributional Control via Score-Based Reinforcement Learning for Flow Matching cites this paper.
ScoRe-Flow: Complete Distributional Control via Score-Based Reinforcement Learning for Flow Matching $\pi^{*}_{0.6}$: a VLA That Learns From Experience
Reference 2
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T09:26:00.670288Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 849a9f66-883f-42de-b293-8ff9b5fac114 · inbound
${\pi}_{0.7}$: a Steerable Generalist Robotic Foundation Model with Emergent Capabilities cites this paper.
${\pi}_{0.7}$: a Steerable Generalist Robotic Foundation Model with Emergent Capabilities $\pi^{*}_{0.6}$: a VLA That Learns From Experience
Reference 52
- Resolution
- verified exact
- arxiv_id, observed 2026-05-10T11:45:21.702816Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 11bbe7f9-32f6-437f-ba42-ed36faef8f79 · inbound
OmniVLA-RL: A Vision-Language-Action Model with Spatial Understanding and Online RL cites this paper.
OmniVLA-RL: A Vision-Language-Action Model with Spatial Understanding and Online RL $\pi^{*}_{0.6}$: a VLA That Learns From Experience
Reference 12
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-10T09:28:39.271234Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation d2ef1d48-631d-4ff8-8db6-427455325208 · inbound
SpanVLA: Efficient Action Bridging and Learning from Negative-Recovery Samples for Vision-Language-Action Model cites this paper.
SpanVLA: Efficient Action Bridging and Learning from Negative-Recovery Samples for Vision-Language-Action Model $\pi^{*}_{0.6}$: a VLA That Learns From Experience
Reference 25
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-11T12:56:10.899312Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 79dc5373-be84-473e-ba4a-68b154ed655c · inbound
VLA Foundry: A Unified Framework for Training Vision-Language-Action Models cites this paper.
VLA Foundry: A Unified Framework for Training Vision-Language-Action Models $\pi^{*}_{0.6}$: a VLA That Learns From Experience
Reference 53
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T13:16:04.018345Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation b5e9749d-9299-4baf-9de1-9b59876d33bd · inbound
FASTER: Value-Guided Sampling for Fast RL cites this paper.
FASTER: Value-Guided Sampling for Fast RL $\pi^{*}_{0.6}$: a VLA That Learns From Experience
Reference 37
- Resolution
- verified exact
- arxiv_id, observed 2026-05-10T02:48:27.263461Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 1aa59379-c0d1-4e27-bee2-2f0ee93b78ee · inbound
RL Token: Bootstrapping Online RL with Vision-Language-Action Models cites this paper.
RL Token: Bootstrapping Online RL with Vision-Language-Action Models $\pi^{*}_{0.6}$: a VLA That Learns From Experience
Reference 4
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-11T19:26:09.184643Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation d75b9113-b2cd-43fa-b10f-fbe96e1cfa2e · inbound
Cooptimizing Safety and Performance Using Safety Value-Constrained Model Predictive Control cites this paper.
Cooptimizing Safety and Performance Using Safety Value-Constrained Model Predictive Control $\pi^{*}_{0.6}$: a VLA That Learns From Experience
Reference 1
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T21:21:11.452892Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 11f572ef-8fe3-4103-837a-9962c0a0b575 · inbound
DiscreteRTC: Discrete Diffusion Policies are Natural Asynchronous Executors cites this paper.
DiscreteRTC: Discrete Diffusion Policies are Natural Asynchronous Executors $\pi^{*}_{0.6}$: a VLA That Learns From Experience
Reference 17
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T22:46:11.935381Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 52f3a094-dec9-40ca-a545-fc9f7b17afdd · inbound
DiscreteRTC: Discrete Diffusion Policies are Natural Asynchronous Executors cites this paper.
DiscreteRTC: Discrete Diffusion Policies are Natural Asynchronous Executors $\pi^{*}_{0.6}$: a VLA That Learns From Experience
Reference 19
- Resolution
- verified exact
- local_arxiv, observed 2026-07-01T08:35:33.445649Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 7db32639-0052-4126-a62f-dc40a36e8002 · inbound
PRTS: A Primitive Reasoning and Tasking System via Contrastive Representations cites this paper.
PRTS: A Primitive Reasoning and Tasking System via Contrastive Representations $\pi^{*}_{0.6}$: a VLA That Learns From Experience
Reference 14
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T09:51:29.124042Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation f33c21b4-a7c7-4353-875f-222d94b944c1 · inbound
LaST-R1: Reinforcing Robotic Manipulation via Adaptive Physical Latent Reasoning cites this paper.
LaST-R1: Reinforcing Robotic Manipulation via Adaptive Physical Latent Reasoning $\pi^{*}_{0.6}$: a VLA That Learns From Experience
Reference 30
- Resolution
- verified exact
- local_arxiv, observed 2026-05-12T10:31:30.071764Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 7bd5b30e-bf2e-4c10-b421-b84ef469c9f8 · inbound
LaST-R1: Reinforcing Robotic Manipulation via Adaptive Physical Latent Reasoning cites this paper.
LaST-R1: Reinforcing Robotic Manipulation via Adaptive Physical Latent Reasoning $\pi^{*}_{0.6}$: a VLA That Learns From Experience
Reference 30
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T22:17:04.478386Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 821bdf88-6d1b-478d-8eab-c3df931350d6 · inbound
Learning While Deploying: Fleet-Scale Reinforcement Learning for Generalist Robot Policies cites this paper.
Learning While Deploying: Fleet-Scale Reinforcement Learning for Generalist Robot Policies $\pi^{*}_{0.6}$: a VLA That Learns From Experience
Reference 15
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T15:36:10.922526Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 31042599-b993-42b1-9b4f-31a07958c008 · inbound
Learning While Deploying: Fleet-Scale Reinforcement Learning for Generalist Robot Policies cites this paper.
Learning While Deploying: Fleet-Scale Reinforcement Learning for Generalist Robot Policies $\pi^{*}_{0.6}$: a VLA That Learns From Experience
Reference 15
- Resolution
- verified exact
- local_arxiv, observed 2026-07-01T08:15:32.263986Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 0cd918c7-08e8-44e9-a758-020f720c804a · inbound
Seeing Realism from Simulation: Efficient Video Transfer for Vision-Language-Action Data Augmentation cites this paper.
Seeing Realism from Simulation: Efficient Video Transfer for Vision-Language-Action Data Augmentation $\pi^{*}_{0.6}$: a VLA That Learns From Experience
Reference 13
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-09T06:35:38.643323Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 366acde0-6660-495b-91cb-b42c6ed4a338 · inbound
RLDX-1 Technical Report cites this paper.
RLDX-1 Technical Report $\pi^{*}_{0.6}$: a VLA That Learns From Experience
Reference 4
- Resolution
- verified exact
- local_arxiv, observed 2026-05-12T10:51:30.983227Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation fa180a3b-b5db-44ba-8a1c-f25384a8d997 · inbound
RLDX-1 Technical Report cites this paper.
RLDX-1 Technical Report $\pi^{*}_{0.6}$: a VLA That Learns From Experience
Reference 4
- Resolution
- verified exact
- arxiv_id, observed 2026-05-09T06:05:35.153838Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation e24d812c-f698-4b26-8779-0c2e81e705f0 · inbound
Long-Horizon Q-Learning: Accurate Value Learning via n-Step Inequalities cites this paper.
Long-Horizon Q-Learning: Accurate Value Learning via n-Step Inequalities $\pi^{*}_{0.6}$: a VLA That Learns From Experience
Reference 3
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T19:41:08.137796Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation e1727c4a-b0e3-47a2-b37f-63bcd996ca70 · inbound
Long-Horizon Q-Learning: Accurate Value Learning via n-Step Inequalities cites this paper.
Long-Horizon Q-Learning: Accurate Value Learning via n-Step Inequalities $\pi^{*}_{0.6}$: a VLA That Learns From Experience
Reference 3
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T05:41:24.464065Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 9de942b0-daca-4732-a02a-971cd3a69ced · inbound
Is the Future Compatible? Diagnosing Dynamic Consistency in World Action Models cites this paper.
Is the Future Compatible? Diagnosing Dynamic Consistency in World Action Models $\pi^{*}_{0.6}$: a VLA That Learns From Experience
Reference 18
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T03:15:57.016888Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 653d5306-3366-43d4-8e0e-62ea18775bfb · inbound
How to Utilize Failure Demo Data?: Effective Data Selection for Imitation Learning Using Distribution Differences in Attention Mechanism cites this paper.
How to Utilize Failure Demo Data?: Effective Data Selection for Imitation Learning Using Distribution Differences in Attention Mechanism $\pi^{*}_{0.6}$: a VLA That Learns From Experience
Reference 10
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T03:55:55.326380Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation d404f7cb-cff8-4653-b92d-35a61034809b · inbound
How to Utilize Failure Demo Data?: Effective Data Selection for Imitation Learning Using Distribution Differences in Attention Mechanism cites this paper.
How to Utilize Failure Demo Data?: Effective Data Selection for Imitation Learning Using Distribution Differences in Attention Mechanism $\pi^{*}_{0.6}$: a VLA That Learns From Experience
Reference 10
- Resolution
- verified exact
- local_arxiv, observed 2026-05-21T08:19:52.285237Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation cea9e3d8-b191-4f83-ac5b-e72cab9015ed · inbound
ProcVLM: Learning Procedure-Grounded Progress Rewards for Robotic Manipulation cites this paper.
ProcVLM: Learning Procedure-Grounded Progress Rewards for Robotic Manipulation $\pi^{*}_{0.6}$: a VLA That Learns From Experience
Reference 2
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T01:41:20.081536Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 642b95dc-67fa-4f8e-8b92-201795b07d38 · inbound
RePO-VLA: Recovery-Driven Policy Optimization for Vision-Language-Action Models cites this paper.
RePO-VLA: Recovery-Driven Policy Optimization for Vision-Language-Action Models $\pi^{*}_{0.6}$: a VLA That Learns From Experience
Reference 11
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T06:01:25.887746Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation cee6d915-3da8-49d6-96cb-a32a0428e05d · inbound
UniSteer: Unified Noise Steering for Efficient Human-Guided VLA Adaptation cites this paper.
UniSteer: Unified Noise Steering for Efficient Human-Guided VLA Adaptation $\pi^{*}_{0.6}$: a VLA That Learns From Experience
Reference 27
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T06:36:25.616019Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 3ee5fb14-c9e3-499d-8773-69be5697373f · inbound
UniSteer: Unified Noise Steering for Efficient Human-Guided VLA Adaptation cites this paper.
UniSteer: Unified Noise Steering for Efficient Human-Guided VLA Adaptation $\pi^{*}_{0.6}$: a VLA That Learns From Experience
Reference 26
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T14:26:01.108089Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 243ca8ad-4a03-4ec7-b345-de498c102a9b · inbound
Offline Policy Evaluation for Manipulation Policies via Discounted Liveness Formulation cites this paper.
Offline Policy Evaluation for Manipulation Policies via Discounted Liveness Formulation $\pi^{*}_{0.6}$: a VLA That Learns From Experience
Reference 11
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-05-13T02:17:06.392865Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation e4264a32-1d3d-49d1-9a89-c8c7440005cb · inbound
TMRL: Diffusion Timestep-Modulated Pretraining Enables Exploration for Efficient Policy Finetuning cites this paper.
TMRL: Diffusion Timestep-Modulated Pretraining Enables Exploration for Efficient Policy Finetuning $\pi^{*}_{0.6}$: a VLA That Learns From Experience
Reference 3
- Resolution
- verified exact
- local_arxiv, observed 2026-05-13T04:22:14.539966Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 477f222f-4cf3-4775-8aec-db52d2a03170 · inbound
Reinforcing VLAs in Task-Agnostic World Models cites this paper.
Reinforcing VLAs in Task-Agnostic World Models $\pi^{*}_{0.6}$: a VLA That Learns From Experience
Reference 11
- Resolution
- verified exact
- local_arxiv, observed 2026-05-13T04:22:14.806687Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation d6057664-e984-408a-8b65-ccf9339154e9 · inbound
Reinforcing VLAs in Task-Agnostic World Models cites this paper.
Reinforcing VLAs in Task-Agnostic World Models $\pi^{*}_{0.6}$: a VLA That Learns From Experience
Reference 11
- Resolution
- verified exact
- local_arxiv, observed 2026-05-21T08:14:03.120777Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 0d479dcf-08d8-4105-a675-33e93d0b1b76 · inbound
Runtime Monitoring of Perception-Based Autonomous Systems via Embedding Temporal Logic cites this paper.
Runtime Monitoring of Perception-Based Autonomous Systems via Embedding Temporal Logic $\pi^{*}_{0.6}$: a VLA That Learns From Experience
Reference 26
- Resolution
- verified exact
- local_arxiv, observed 2026-05-14T21:38:01.112967Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 708bd060-aef4-4677-b570-80664becf849 · inbound
Runtime Monitoring of Perception-Based Autonomous Systems via Embedding Temporal Logic cites this paper.
Runtime Monitoring of Perception-Based Autonomous Systems via Embedding Temporal Logic $\pi^{*}_{0.6}$: a VLA That Learns From Experience
Reference 26
- Resolution
- verified exact
- local_arxiv, observed 2026-05-15T05:05:01.918390Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 0528ad19-a077-4bd0-8fb8-1e9a2e37f3c6 · inbound
RotVLA: Rotational Latent Action for Vision-Language-Action Model cites this paper.
RotVLA: Rotational Latent Action for Vision-Language-Action Model $\pi^{*}_{0.6}$: a VLA That Learns From Experience
Reference 20
- Resolution
- verified exact
- local_arxiv, observed 2026-05-14T17:49:23.121112Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation af909c11-c285-409d-b62a-a28fbf9940b2 · inbound
Evo-Depth: A Lightweight Depth-Enhanced Vision-Language-Action Model cites this paper.
Evo-Depth: A Lightweight Depth-Enhanced Vision-Language-Action Model $\pi^{*}_{0.6}$: a VLA That Learns From Experience
Reference 14
- Resolution
- verified exact
- local_arxiv, observed 2026-07-01T14:25:46.144820Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 11c89708-b46b-4666-8511-5819eda6a17f · inbound
Hand-in-the-Loop: Improving VLA Policies for Dexterous Manipulation via Seamless Hand-Arm Intervention cites this paper.
Hand-in-the-Loop: Improving VLA Policies for Dexterous Manipulation via Seamless Hand-Arm Intervention $\pi^{*}_{0.6}$: a VLA That Learns From Experience
Reference 9
- Resolution
- verified exact
- local_arxiv, observed 2026-05-15T03:09:42.194160Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 547d1aa1-9442-4d13-adb5-101ebdf8b4ec · inbound
Hand-in-the-Loop: Improving VLA Policies for Dexterous Manipulation via Seamless Hand-Arm Intervention cites this paper.
Hand-in-the-Loop: Improving VLA Policies for Dexterous Manipulation via Seamless Hand-Arm Intervention $\pi^{*}_{0.6}$: a VLA That Learns From Experience
Reference 9
- Resolution
- verified exact
- local_arxiv, observed 2026-05-21T08:34:05.577883Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation bbf4e9fb-371b-497c-bc86-212e66694060 · inbound
AffordVLA: Injecting Affordance Representations into Vision-Language-Action Models via Implicit Feature Alignment cites this paper.
AffordVLA: Injecting Affordance Representations into Vision-Language-Action Models via Implicit Feature Alignment $\pi^{*}_{0.6}$: a VLA That Learns From Experience
Reference 33
- Resolution
- verified exact
- local_arxiv, observed 2026-05-20T12:53:17.733969Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation a8ad6fdb-2863-43b8-8ae3-94d9e214331b · inbound
ManiSoft: Towards Vision-Language Manipulation for Soft Continuum Robotics cites this paper.
ManiSoft: Towards Vision-Language Manipulation for Soft Continuum Robotics $\pi^{*}_{0.6}$: a VLA That Learns From Experience
Reference 2
- Resolution
- verified exact
- local_arxiv, observed 2026-05-20T09:58:11.298331Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 1bbed8e8-9328-4cbb-9cdf-cc0c8222db22 · inbound
RoVLA: Multi-Consistency Constraints for Robust Vision-Language-Action Models cites this paper.
RoVLA: Multi-Consistency Constraints for Robust Vision-Language-Action Models $\pi^{*}_{0.6}$: a VLA That Learns From Experience
Reference 31
- Resolution
- verified exact
- local_arxiv, observed 2026-05-20T04:53:04.916497Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 403221ff-756d-48c9-a339-941450a8772b · inbound
Beyond Action Residuals: Real-World Robot Policy Steering via Bottleneck Latent Reinforcement Learning cites this paper.
Beyond Action Residuals: Real-World Robot Policy Steering via Bottleneck Latent Reinforcement Learning $\pi^{*}_{0.6}$: a VLA That Learns From Experience
Reference 18
- Resolution
- verified exact
- local_arxiv, observed 2026-05-20T05:13:03.351681Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 91aab0bf-fc79-4861-be4e-4ae4888e955c · inbound
VLA-REPLICA: A Low-Cost, Reproducible Benchmark for Real-World Evaluation of Vision-Language-Action Models cites this paper.
VLA-REPLICA: A Low-Cost, Reproducible Benchmark for Real-World Evaluation of Vision-Language-Action Models $\pi^{*}_{0.6}$: a VLA That Learns From Experience
Reference 13
- Resolution
- verified exact
- local_arxiv, observed 2026-05-21T04:59:36.440417Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 4dbb3016-900d-4394-90f8-4d375e570ff3 · inbound
VGenST-Bench: A Benchmark for Spatio-Temporal Reasoning via Active Video Synthesis cites this paper.
VGenST-Bench: A Benchmark for Spatio-Temporal Reasoning via Active Video Synthesis $\pi^{*}_{0.6}$: a VLA That Learns From Experience
Reference 30
- Resolution
- verified exact
- local_arxiv, observed 2026-05-22T07:14:42.831553Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 74fd6aeb-5451-4804-992f-b9c84461e9ca · inbound
ParkingWorld: End-to-End Autonomous Parking Reinforcement Learning from Corrective Experience in 3DGS Simulation cites this paper.
ParkingWorld: End-to-End Autonomous Parking Reinforcement Learning from Corrective Experience in 3DGS Simulation $\pi^{*}_{0.6}$: a VLA That Learns From Experience
Reference 16
- Resolution
- verified exact
- local_arxiv, observed 2026-07-01T16:35:50.720005Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 29701e97-9c2c-43b4-9f76-3528a17411ff · inbound
EXPO-FT: Sample-Efficient Reinforcement Learning Finetuning for Vision-Language-Action Models cites this paper.
EXPO-FT: Sample-Efficient Reinforcement Learning Finetuning for Vision-Language-Action Models $\pi^{*}_{0.6}$: a VLA That Learns From Experience
Reference 35
- Resolution
- verified exact
- local_arxiv, observed 2026-06-29T22:13:59.942734Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 36e776f9-fe90-4494-9c13-671cb8343c63 · inbound
TapSampling: Inference-Time Sampling with a Task-Progress-Understanding Verifier for Robotic Manipulation cites this paper.
TapSampling: Inference-Time Sampling with a Task-Progress-Understanding Verifier for Robotic Manipulation $\pi^{*}_{0.6}$: a VLA That Learns From Experience
Reference 6
- Resolution
- verified exact
- local_arxiv, observed 2026-06-29T22:04:00.522441Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 7d89163c-bb81-4dd7-b6c4-3e9bb2facfbe · inbound
Trust Region Q Adjoint Matching cites this paper.
Trust Region Q Adjoint Matching $\pi^{*}_{0.6}$: a VLA That Learns From Experience
Reference 18
- Resolution
- verified exact
- local_arxiv, observed 2026-06-29T19:13:52.794109Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 0e1d34ea-87b6-4f86-b9e3-ff665c722e1f · inbound
PhAIL: A Real-Robot VLA Benchmark and Distributional Methodology cites this paper.
PhAIL: A Real-Robot VLA Benchmark and Distributional Methodology $\pi^{*}_{0.6}$: a VLA That Learns From Experience
Reference 38
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-06-29T14:13:31.047658Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 12a7c66d-2bfb-47dd-b1a9-86fc9af5fb00 · inbound
MARS Policy: Multimodality Only When It Matters cites this paper.
MARS Policy: Multimodality Only When It Matters $\pi^{*}_{0.6}$: a VLA That Learns From Experience
Reference 4
- Resolution
- verified exact
- local_arxiv, observed 2026-06-29T06:43:10.272087Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation e894690e-f8fd-47ba-8873-8d707a76205a · inbound
BORA: Bridging Offline Reinforcement Learning and Online Residual Adaptation for Real-World Dexterous VLA Models cites this paper.
BORA: Bridging Offline Reinforcement Learning and Online Residual Adaptation for Real-World Dexterous VLA Models $\pi^{*}_{0.6}$: a VLA That Learns From Experience
Reference 5
- Resolution
- verified exact
- local_arxiv, observed 2026-06-29T07:23:12.765963Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 14378c67-19f3-4148-9481-a6f631bf846f · inbound
Feat2Go: Visual Feature-Grounded Value Estimation for Embodied Reinforcement Learning cites this paper.
Feat2Go: Visual Feature-Grounded Value Estimation for Embodied Reinforcement Learning $\pi^{*}_{0.6}$: a VLA That Learns From Experience
Reference 7
- Resolution
- verified exact
- local_arxiv, observed 2026-06-28T22:42:46.165638Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation c7c2f300-52f1-4ac5-99ad-46e28abb972f · inbound
Hide-and-Seek in Trajectories: Discovering Failure Signals for VLA Runtime Monitoring cites this paper.
Hide-and-Seek in Trajectories: Discovering Failure Signals for VLA Runtime Monitoring $\pi^{*}_{0.6}$: a VLA That Learns From Experience
Reference 3
- Resolution
- verified exact
- local_arxiv, observed 2026-06-28T22:42:46.564956Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation f25ab638-847b-491d-a10f-6304913606e0 · inbound
DeMaVLA: A Vision-Language-Action Foundation Model for Generalizable Deformable Manipulation cites this paper.
DeMaVLA: A Vision-Language-Action Foundation Model for Generalizable Deformable Manipulation $\pi^{*}_{0.6}$: a VLA That Learns From Experience
Reference 16
- Resolution
- verified exact
- local_arxiv, observed 2026-07-01T19:56:10.403716Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation e04488e6-68e4-4b8f-bb07-81620419a62e · inbound
Set-Supervised Diffusion Policy: Learning Action-Chunking Diffusion through Corrections cites this paper.
Set-Supervised Diffusion Policy: Learning Action-Chunking Diffusion through Corrections $\pi^{*}_{0.6}$: a VLA That Learns From Experience
Reference 1
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-07-01T23:26:21.980669Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation b8fd35c3-3510-4838-bb18-a42bc7998cad · inbound
Grasp-Then-Plan with Failure Attribution: A Closed Two-Stage Framework for Precise and Generalizable Robotic Manipulation cites this paper.
Grasp-Then-Plan with Failure Attribution: A Closed Two-Stage Framework for Precise and Generalizable Robotic Manipulation $\pi^{*}_{0.6}$: a VLA That Learns From Experience
Reference 20
- Resolution
- verified exact
- local_arxiv, observed 2026-07-02T03:56:34.450797Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 1b030e9c-c707-4ca2-9d50-7611f9179f14 · inbound
FlowPRO: Reward-Free Reinforced Fine-Tuning of Flow-Matching VLAs via Proximalized Preference Optimization cites this paper.
FlowPRO: Reward-Free Reinforced Fine-Tuning of Flow-Matching VLAs via Proximalized Preference Optimization $\pi^{*}_{0.6}$: a VLA That Learns From Experience
Reference 17
- Resolution
- verified exact
- local_arxiv, observed 2026-07-02T09:06:49.372377Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation d554ed0a-01b6-471c-93d0-a43f932aa4e7 · inbound
What Matters When Cotraining Robot Manipulation Policies on Everyday Human Videos? cites this paper.
What Matters When Cotraining Robot Manipulation Policies on Everyday Human Videos? $\pi^{*}_{0.6}$: a VLA That Learns From Experience
Reference 37
- Resolution
- verified exact
- local_arxiv, observed 2026-07-02T13:46:58.988013Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 651a7c5f-a301-4467-86d2-997c9a4ff715 · inbound
VoLo: A Physical Orchestrator for Open-Vocabulary Long-Horizon Manipulation cites this paper.
VoLo: A Physical Orchestrator for Open-Vocabulary Long-Horizon Manipulation $\pi^{*}_{0.6}$: a VLA That Learns From Experience
Reference 26
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-07-02T19:07:18.115064Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 3486b7c9-061a-4cc8-b3b9-e2968784ef6a · inbound
PACT: Self-Evolving Physical Safety Alignment for Diffusion Policies in Embodied Manipulation cites this paper.
PACT: Self-Evolving Physical Safety Alignment for Diffusion Policies in Embodied Manipulation $\pi^{*}_{0.6}$: a VLA That Learns From Experience
Reference 1
- Resolution
- verified exact
- local_arxiv, observed 2026-06-27T18:51:07.725191Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 7febade0-ee7d-4ffe-89c9-bbe104161c40 · inbound
Scaling by Diversified Experience for Vision-Language-Action Models cites this paper.
Scaling by Diversified Experience for Vision-Language-Action Models $\pi^{*}_{0.6}$: a VLA That Learns From Experience
Reference 9
- Resolution
- verified exact
- local_arxiv, observed 2026-07-03T00:27:29.754454Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation dd797f3e-e316-42e9-84b0-789fbdbef3d1 · inbound
TORL-VLA: Tactile Guided Online Reinforcement Learning for Contact-Rich Manipulation cites this paper.
TORL-VLA: Tactile Guided Online Reinforcement Learning for Contact-Rich Manipulation $\pi^{*}_{0.6}$: a VLA That Learns From Experience
Reference 16
- Resolution
- verified exact
- local_arxiv, observed 2026-07-03T01:27:31.335128Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation db3cb8b3-808f-41af-bd49-de6b64e2e1f9 · inbound
DexPIE: Stable Dexterous Policy Improvement from Real-World Experience cites this paper.
DexPIE: Stable Dexterous Policy Improvement from Real-World Experience $\pi^{*}_{0.6}$: a VLA That Learns From Experience
Reference 9
- Resolution
- verified exact
- local_arxiv, observed 2026-07-03T01:07:30.747483Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.