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Paper Citation Record · LEDGER

DEMONSTRATE: Zero-shot Language to Robotic Control via Multi-task Demonstration Learning

As of 10 August 2026, this Paper Citation Record lists 41 of 41 outbound references and 0 inbound Pith citation observations for arXiv:2507.12855.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2507.12855 v1

Coverage vector

measured 41 of 41 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T16:42:32.565645Z

measured 41 of 41 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

41 of 41 outbound references displayed

  • verified exact0
  • verified fuzzy24
  • unresolved17
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation c5988630-96d3-471f-b8af-6e0eb73b10e9 · outbound

This paper cites Prompt a Robot to Walk with Large Language Models.

DEMONSTRATE: Zero-shot Language to Robotic Control via Multi-task Demonstration Learning Prompt a Robot to Walk with Large Language Models

Reference 1

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Observation cb5aba63-d637-4b46-9bd8-18583e79c2d7 · outbound

This paper cites VIMA: General Robot Manipulation with Multimodal Prompts.

DEMONSTRATE: Zero-shot Language to Robotic Control via Multi-task Demonstration Learning VIMA: General Robot Manipulation with Multimodal Prompts

Reference 2

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source=pdf_text observed=2026-08-06T16:42:29.495001Z digest=sha256:6b18cd92fec995cc30a86fb85871e35106a169fbd9cddc245ec159e3759fecca

Observation 9914c040-d89e-4c15-bb40-048cc53278a7 · outbound

This paper cites Perceiver-actor: A multi-task transformer for robotic manipulation,.

DEMONSTRATE: Zero-shot Language to Robotic Control via Multi-task Demonstration Learning Perceiver-actor: A multi-task transformer for robotic manipulation,

Reference 3

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Observation 2e7d2c0e-353b-4999-a12d-7ef984f4ed83 · outbound

This paper cites RoCo: Dialectic Multi-Robot Collaboration with Large Language Models.

DEMONSTRATE: Zero-shot Language to Robotic Control via Multi-task Demonstration Learning RoCo: Dialectic Multi-Robot Collaboration with Large Language Models

Reference 4

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source=pdf_text observed=2026-08-06T16:42:29.682230Z digest=sha256:f2a0ee6684edef816d21217cc1d1b22cfe91533282fad38ab1f0f6ed1069338d

Observation 1101ef12-3c55-4749-9713-1120c2e4ddf0 · outbound

This paper cites Program Synthesis with Large Language Models.

DEMONSTRATE: Zero-shot Language to Robotic Control via Multi-task Demonstration Learning Program Synthesis with Large Language Models

Reference 5

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source=pdf_text observed=2026-08-06T16:42:29.764952Z digest=sha256:9ae833a68d0874f8287863fba808354e89daf2abd48d234cdcb34548899893bf

Observation 8a276ed9-d8e6-428c-a2c2-7c149d2ec71a · outbound

This paper cites Learning to synthesize programs as interpretable and generalizable policies,.

DEMONSTRATE: Zero-shot Language to Robotic Control via Multi-task Demonstration Learning Learning to synthesize programs as interpretable and generalizable policies,

Reference 6

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raw_fallback, observed 2026-08-06T16:42:38.174480Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T16:42:29.836752Z digest=sha256:5e15a759ff01911d7eed7b5293860097c62941fc790def1786747d69b93df7ab

Observation 07aa2c47-8344-4288-90c1-03be2816e94f · outbound

This paper cites Code as policies: Language model programs for embodied control,.

DEMONSTRATE: Zero-shot Language to Robotic Control via Multi-task Demonstration Learning Code as policies: Language model programs for embodied control,

Reference 7

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T16:42:29.890045Z digest=sha256:6a72f8fad5949380e8249c4e28c17af7b31687d358c8513aa4f0c09e21044242

Observation c5ecb967-8c7d-4298-870b-52fdb129f268 · outbound

This paper cites Using Natural Language for Reward Shaping in Reinforcement Learning.

DEMONSTRATE: Zero-shot Language to Robotic Control via Multi-task Demonstration Learning Using Natural Language for Reward Shaping in Reinforcement Learning

Reference 8

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-06T16:42:29.948812Z digest=sha256:aa3f2448d337e46ee03492717f5e9831bef8870f890e3cea95e1619601fa34ec

Observation c6c10f6b-9231-42e3-89c1-5a6461a56315 · outbound

This paper cites Language to Rewards for Robotic Skill Synthesis.

DEMONSTRATE: Zero-shot Language to Robotic Control via Multi-task Demonstration Learning Language to Rewards for Robotic Skill Synthesis

Reference 9

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source=pdf_text observed=2026-08-06T16:42:30.008389Z digest=sha256:0042652758724e2f625ba7ca4f715a354c11cbbb99cbd8756279dee2952aba23

Observation 83159f12-2f15-44a0-bb26-a3614668dd31 · outbound

This paper cites Eureka: Human-Level Reward Design via Coding Large Language Models.

DEMONSTRATE: Zero-shot Language to Robotic Control via Multi-task Demonstration Learning Eureka: Human-Level Reward Design via Coding Large Language Models

Reference 10

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source=pdf_text observed=2026-08-06T16:42:30.086075Z digest=sha256:628740c4f5e38c9f9ef291157989e58af6f7a8e1208a98fa1b4df647ea8d096c

Observation 95326558-20b4-473e-acde-3252769638a2 · outbound

This paper cites Narrate: Versatile language architecture for optimal control in robotics,.

DEMONSTRATE: Zero-shot Language to Robotic Control via Multi-task Demonstration Learning Narrate: Versatile language architecture for optimal control in robotics,

Reference 11

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T16:42:30.149892Z digest=sha256:9f1a34eacbc430e2b0fea551a4e4a1b42b6159c460c7d034e1e0bdc192e7bb45

Observation cc884e2b-906a-4901-a73c-502bdf7df60f · outbound

This paper cites A survey of inverse reinforcement learning,.

DEMONSTRATE: Zero-shot Language to Robotic Control via Multi-task Demonstration Learning A survey of inverse reinforcement learning,

Reference 12

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T16:42:30.215841Z digest=sha256:e52e8e298c88f48a306356a6e0d28aca1a5470e24fa636a7a2d2dacb1fec0c6d

Observation 26b76d71-0c19-4001-817c-cb0f6eb5b088 · outbound

This paper cites The benefit of mul- titask representation learning,.

DEMONSTRATE: Zero-shot Language to Robotic Control via Multi-task Demonstration Learning The benefit of mul- titask representation learning,

Reference 13

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 0e3153f5-0105-4fe0-988b-b142170573f3 · outbound

This paper cites A survey on multi-task learning,.

DEMONSTRATE: Zero-shot Language to Robotic Control via Multi-task Demonstration Learning A survey on multi-task learning,

Reference 14

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source=pdf_text observed=2026-08-06T16:42:30.347246Z digest=sha256:79ebcf9d01fe9eee78ad397c72c70967a836a93952b8cbe4a1b935f6130e4e92

Observation e789a49d-f4a1-4c21-9732-313c3c1679e4 · outbound

This paper cites Context-aware LLM-based Safe Control Against Latent Risks.

DEMONSTRATE: Zero-shot Language to Robotic Control via Multi-task Demonstration Learning Context-aware LLM-based Safe Control Against Latent Risks

Reference 15

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source=pdf_text observed=2026-08-06T16:42:30.415689Z digest=sha256:dcf3b5b31a38118f32f4588550c186eecf11c775d0e6c793b6f856ea8a3c5c2d

Observation 4f002d04-76be-4341-866e-57a131254568 · outbound

This paper cites Affordance-Guided Reinforcement Learning via Visual Prompting.

DEMONSTRATE: Zero-shot Language to Robotic Control via Multi-task Demonstration Learning Affordance-Guided Reinforcement Learning via Visual Prompting

Reference 16

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Observation 15029b27-b492-4663-86d8-82104bcc6169 · outbound

This paper cites Language models are few-shot learners,.

DEMONSTRATE: Zero-shot Language to Robotic Control via Multi-task Demonstration Learning Language models are few-shot learners,

Reference 17

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 1e06b238-f171-4003-a72d-a260514e8cb5 · outbound

This paper cites A survey of controllable text generation us- ing transformer-based pre-trained language models,.

DEMONSTRATE: Zero-shot Language to Robotic Control via Multi-task Demonstration Learning A survey of controllable text generation us- ing transformer-based pre-trained language models,

Reference 18

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 274fbae3-19da-469b-89d0-9d534947e15f · outbound

This paper cites How can we know what language models know?.

DEMONSTRATE: Zero-shot Language to Robotic Control via Multi-task Demonstration Learning How can we know what language models know?

Reference 19

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T16:42:30.651127Z digest=sha256:bf947d9f8cc06ae32241e72e7b6186f92e8b994a0e7235430f4d564374ef1917

Observation 4ba9d490-7e65-432c-bc43-a999a4bc3d65 · outbound

This paper cites AutoPrompt: Eliciting Knowledge from Language Models with Automatically Generated Prompts.

DEMONSTRATE: Zero-shot Language to Robotic Control via Multi-task Demonstration Learning AutoPrompt: Eliciting Knowledge from Language Models with Automatically Generated Prompts

Reference 20

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Observation c71ef73d-e629-4829-bd77-79b456a154dc · outbound

This paper cites Universal and Transferable Adversarial Attacks on Aligned Language Models.

DEMONSTRATE: Zero-shot Language to Robotic Control via Multi-task Demonstration Learning Universal and Transferable Adversarial Attacks on Aligned Language Models

Reference 21

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Observation 75487985-9309-43ef-b8a0-89b8d87f7ec6 · outbound

This paper cites RLPrompt: Optimizing Discrete Text Prompts with Reinforcement Learning.

DEMONSTRATE: Zero-shot Language to Robotic Control via Multi-task Demonstration Learning RLPrompt: Optimizing Discrete Text Prompts with Reinforcement Learning

Reference 22

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Observation ebf42714-92f7-45b5-b9da-9fa1659ff40b · outbound

This paper cites TEMPERA: Test-Time Prompting via Reinforcement Learning.

DEMONSTRATE: Zero-shot Language to Robotic Control via Multi-task Demonstration Learning TEMPERA: Test-Time Prompting via Reinforcement Learning

Reference 23

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Observation e94a31ee-f064-4793-90d5-443a2b569419 · outbound

This paper cites Prompt programming for large lan- guage models: Beyond the few-shot paradigm,.

DEMONSTRATE: Zero-shot Language to Robotic Control via Multi-task Demonstration Learning Prompt programming for large lan- guage models: Beyond the few-shot paradigm,

Reference 24

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 01353bec-6b4d-4f55-af5d-acb81e9032c2 · outbound

This paper cites Clara: Classifying and disambiguating user commands for reliable interactive robotic agents,.

DEMONSTRATE: Zero-shot Language to Robotic Control via Multi-task Demonstration Learning Clara: Classifying and disambiguating user commands for reliable interactive robotic agents,

Reference 25

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 49696b65-9418-4eff-83f1-80baf1756f76 · outbound

This paper cites Robots that ask for help: Uncertainty alignment for large language model planners,.

DEMONSTRATE: Zero-shot Language to Robotic Control via Multi-task Demonstration Learning Robots that ask for help: Uncertainty alignment for large language model planners,

Reference 26

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation ecfe9329-c46b-429a-a402-b7bc4e7475d0 · outbound

This paper cites Model predictive control,.

DEMONSTRATE: Zero-shot Language to Robotic Control via Multi-task Demonstration Learning Model predictive control,

Reference 27

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation afaedb06-8cd5-464b-a7db-90bbc9df0378 · outbound

This paper cites Maximum entropy inverse rein- forcement learning,.

DEMONSTRATE: Zero-shot Language to Robotic Control via Multi-task Demonstration Learning Maximum entropy inverse rein- forcement learning,

Reference 28

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T16:42:31.281823Z digest=sha256:7493841d925d1f62b97ec347deff58ea7806b0e0f6e591369558b42cee027bdd

Observation ecf803bd-b489-4814-8f38-8889bcbf8a17 · outbound

This paper cites Continuous inverse optimal control with locally optimal examples,.

DEMONSTRATE: Zero-shot Language to Robotic Control via Multi-task Demonstration Learning Continuous inverse optimal control with locally optimal examples,

Reference 29

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T16:42:31.392426Z digest=sha256:95e21758c55e1306cddd68e02e1d4a163c19371fea9c862e2c5fcc6247d77ab7

Observation acf3ae93-eed9-4162-a83c-4e1c0c639cd8 · outbound

This paper cites Learning constraints from demonstrations,.

DEMONSTRATE: Zero-shot Language to Robotic Control via Multi-task Demonstration Learning Learning constraints from demonstrations,

Reference 30

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raw_fallback, observed 2026-08-06T16:42:34.929624Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T16:42:31.468996Z digest=sha256:a7ccadf4ae67a910b41644b7cd2bc340e35f02d9aea5370280c8d09430e1d777

Observation 439522b7-a711-4f8a-83c7-527adfaf4e99 · outbound

This paper cites Learning parametric constraints in high dimensions from demonstrations,.

DEMONSTRATE: Zero-shot Language to Robotic Control via Multi-task Demonstration Learning Learning parametric constraints in high dimensions from demonstrations,

Reference 31

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raw_fallback, observed 2026-08-06T16:42:34.644128Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 751dd310-1bd8-41c1-9650-f88e30389b43 · outbound

This paper cites Sparse spectrum gaussian process regression,.

DEMONSTRATE: Zero-shot Language to Robotic Control via Multi-task Demonstration Learning Sparse spectrum gaussian process regression,

Reference 32

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raw_fallback, observed 2026-08-06T16:42:34.409378Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T16:42:31.601517Z digest=sha256:ab2a43cb6394c0ea86d1696838834f53baf1e975793060b9c83c042c7830e47b

Observation 6a72ea08-830a-4c55-a0e6-ccf7e224ddc2 · outbound

This paper cites Sentence-bert: Sentence embeddings using siamese bert-networks,.

DEMONSTRATE: Zero-shot Language to Robotic Control via Multi-task Demonstration Learning Sentence-bert: Sentence embeddings using siamese bert-networks,

Reference 33

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raw_fallback, observed 2026-08-06T16:42:34.180761Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 2c189990-d810-4c73-b8ae-d2d78aa83c50 · outbound

This paper cites Mpnet: Masked and permuted pre-training for language understanding,.

DEMONSTRATE: Zero-shot Language to Robotic Control via Multi-task Demonstration Learning Mpnet: Masked and permuted pre-training for language understanding,

Reference 34

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raw_fallback, observed 2026-08-06T16:42:33.924767Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T16:42:31.750561Z digest=sha256:f7765aab438dc1553fd7540d3461e9ab42f8c0948a33728b3f65902b623ff917

Observation 29dec18a-f414-4fa8-b74b-a6020a1ffbd1 · outbound

This paper cites Guarantees for Nonlinear Representation Learning: Non-identical Covariates, Dependent Data, Fewer Samples.

DEMONSTRATE: Zero-shot Language to Robotic Control via Multi-task Demonstration Learning Guarantees for Nonlinear Representation Learning: Non-identical Covariates, Dependent Data, Fewer Samples

Reference 35

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:42:31.832082Z digest=sha256:35b6279d13d87ce493491e6506a1b38ba8eb2955edd1a745a6f23916f0d099c2

Observation d884da7b-ea0e-4140-874d-af1a4415cc04 · outbound

This paper cites Smc: Satisfiability modulo convex optimization,.

DEMONSTRATE: Zero-shot Language to Robotic Control via Multi-task Demonstration Learning Smc: Satisfiability modulo convex optimization,

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:42:33.689207Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T16:42:31.946643Z digest=sha256:a568ff86320c5f46955eca84fe7db04439b088024682a69442261f4a52fac41a

Observation 47f6abc5-dd22-43cb-8fb6-afd7b5230be6 · outbound

This paper cites CasADi – A software framework for nonlinear optimization and optimal control,.

DEMONSTRATE: Zero-shot Language to Robotic Control via Multi-task Demonstration Learning CasADi – A software framework for nonlinear optimization and optimal control,

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:42:33.497622Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T16:42:32.055891Z digest=sha256:d90f4ca4ee9bcc649d1598c02e1f49cbcb35e6b6e598079ebfc8ea330bf7e3de

Observation 211e6c87-706f-4e83-af15-0b7f7b8b04c9 · outbound

This paper cites do-mpc: Towards fair nonlinear and robust model predictive control,.

DEMONSTRATE: Zero-shot Language to Robotic Control via Multi-task Demonstration Learning do-mpc: Towards fair nonlinear and robust model predictive control,

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:42:33.255716Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T16:42:32.247517Z digest=sha256:1c5650d9465974ffffbae0b341654585b85c3169451a25305bf4a117f5e61b51

Observation 724d31af-04ba-4815-9315-aeb279a4136c · outbound

This paper cites panda-gym: Open-source goal-conditioned environments for robotic learning.

DEMONSTRATE: Zero-shot Language to Robotic Control via Multi-task Demonstration Learning panda-gym: Open-source goal-conditioned environments for robotic learning

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-06T16:42:32.379013Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:42:32.379013Z digest=sha256:f91c5f1fc7bba1f9b119e6167541ad78a67fbe5dd3a388de24e6f2f844a2ee75

Observation f5f27313-ff6a-4d42-87ab-d30055ef623e · outbound

This paper cites VoxPoser: Composable 3D Value Maps for Robotic Manipulation with Language Models.

DEMONSTRATE: Zero-shot Language to Robotic Control via Multi-task Demonstration Learning VoxPoser: Composable 3D Value Maps for Robotic Manipulation with Language Models

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-06T16:42:32.494295Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:42:32.494295Z digest=sha256:08b6806a94bd1ca03e6deb6168a1c117f4591a42fb3c8fba63c1d7d6bf0d0d4c

Observation 2edab7dc-7a1a-418e-a692-86a8f3d2cb49 · outbound

This paper cites Open x-embodiment: Robotic learning datasets and rt-x models: Open x- embodiment collaboration 0,.

DEMONSTRATE: Zero-shot Language to Robotic Control via Multi-task Demonstration Learning Open x-embodiment: Robotic learning datasets and rt-x models: Open x- embodiment collaboration 0,

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:42:33.090918Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T16:42:32.565645Z digest=sha256:b9a46ae51761390f9cf4c1918fad316b1f14655039a380cf82af630af5341bd1

Pith citing papers

No inbound Pith citation observations are available.