Paper Citation Record · LEDGER

ACORN: Adaptive Contrastive Optimization for Safe and Robust Fine-Grained Robotic Manipulation

As of 18 August 2026, this Paper Citation Record lists 29 of 29 outbound references and 0 inbound Pith citation observations for arXiv:2505.06628.

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

pith.paper-citation-record.v1
2505.06628 v1

Coverage vector

measured 29 of 29 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T22:42:20.806613Z

measured 29 of 29 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+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

29 of 29 outbound references displayed

verified exact0
verified fuzzy16
unresolved13
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 6ff3474e-54ea-498f-aeeb-c16e3f6bd965 · outbound

This paper cites Learning Fine-Grained Bimanual Manipulation with Low-Cost Hardware.

ACORN: Adaptive Contrastive Optimization for Safe and Robust Fine-Grained Robotic Manipulation Learning Fine-Grained Bimanual Manipulation with Low-Cost Hardware

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-15T22:42:20.688639Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9b494bc8-f350-4204-9562-3fe8407d0e89 · outbound

This paper cites Generative adversarial imitation learning,.

ACORN: Adaptive Contrastive Optimization for Safe and Robust Fine-Grained Robotic Manipulation Generative adversarial imitation learning,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:42:21.187266Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 8fb77eab-b7ba-4116-a686-7dd45c87e7dd · outbound

This paper cites Reinforcement learning with augmented data,.

ACORN: Adaptive Contrastive Optimization for Safe and Robust Fine-Grained Robotic Manipulation Reinforcement learning with augmented data,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:42:21.173395Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation a75add6a-84a7-4799-8922-7a1b47bc2f6f · outbound

This paper cites A simple frame- work for contrastive learning of visual representations,.

ACORN: Adaptive Contrastive Optimization for Safe and Robust Fine-Grained Robotic Manipulation A simple frame- work for contrastive learning of visual representations,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:42:21.159297Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 244bb21b-e196-4504-9b84-b65ca5abf932 · outbound

This paper cites Catch the ball: Accurate high-speed motions for mobile manipulators via inverse dynamics learning,.

ACORN: Adaptive Contrastive Optimization for Safe and Robust Fine-Grained Robotic Manipulation Catch the ball: Accurate high-speed motions for mobile manipulators via inverse dynamics learning,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:42:21.144869Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 465998f5-da3a-40ae-acaa-53e463bb5a6f · outbound

This paper cites Robot reinforcement learning on the constraint manifold,.

ACORN: Adaptive Contrastive Optimization for Safe and Robust Fine-Grained Robotic Manipulation Robot reinforcement learning on the constraint manifold,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:42:21.131140Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation f3e7ae21-2c24-4c07-bb38-e3c6a6ebd9aa · outbound

This paper cites Safe control with learned certificates: A survey of neural lyapunov, barrier, and contraction methods for robotics and control,.

ACORN: Adaptive Contrastive Optimization for Safe and Robust Fine-Grained Robotic Manipulation Safe control with learned certificates: A survey of neural lyapunov, barrier, and contraction methods for robotics and control,

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-15T22:42:20.715949Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cd5618c4-0ac1-45b5-8305-857c84154cdc · outbound

This paper cites Reinforcement Learning for Safety-Critical Control under Model Uncertainty, using Control Lyapunov Functions and Control Barrier Functions.

ACORN: Adaptive Contrastive Optimization for Safe and Robust Fine-Grained Robotic Manipulation Reinforcement Learning for Safety-Critical Control under Model Uncertainty, using Control Lyapunov Functions and Control Barrier Functions

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-15T22:42:20.719904Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ac16d501-9f0d-4467-a856-7065f4df7b63 · outbound

This paper cites Context- aware safe reinforcement learning for non-stationary environments,.

ACORN: Adaptive Contrastive Optimization for Safe and Robust Fine-Grained Robotic Manipulation Context- aware safe reinforcement learning for non-stationary environments,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:42:21.108154Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 5c6c17f8-d4d7-47f7-8253-e53b818c589d · outbound

This paper cites Constrained Policy Optimization via Bayesian World Models.

ACORN: Adaptive Contrastive Optimization for Safe and Robust Fine-Grained Robotic Manipulation Constrained Policy Optimization via Bayesian World Models

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-15T22:42:20.728340Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6e3f8171-9c4b-47f2-9a2e-c9d3c7536d57 · outbound

This paper cites Grasping with chopsticks: Combating covariate shift in model-free imitation learning for fine manipulation,.

ACORN: Adaptive Contrastive Optimization for Safe and Robust Fine-Grained Robotic Manipulation Grasping with chopsticks: Combating covariate shift in model-free imitation learning for fine manipulation,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:42:21.094528Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 5d8047c4-93ec-4606-aaa3-a3ba10bf9bbc · outbound

This paper cites CCIL: Continuity-based Data Augmentation for Corrective Imitation Learning.

ACORN: Adaptive Contrastive Optimization for Safe and Robust Fine-Grained Robotic Manipulation CCIL: Continuity-based Data Augmentation for Corrective Imitation Learning

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-15T22:42:20.737041Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ce7920ad-91df-4ebd-add0-00955e998644 · outbound

This paper cites Data efficient behavior cloning for fine manipulation via continuity- based corrective labels,.

ACORN: Adaptive Contrastive Optimization for Safe and Robust Fine-Grained Robotic Manipulation Data efficient behavior cloning for fine manipulation via continuity- based corrective labels,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:42:21.080617Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 82acc8a9-eaeb-4271-936a-491ef45cee4f · outbound

This paper cites An algorithmic perspective on imitation learning,.

ACORN: Adaptive Contrastive Optimization for Safe and Robust Fine-Grained Robotic Manipulation An algorithmic perspective on imitation learning,

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-15T22:42:20.745563Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e47daa12-dd37-436c-be43-615b45bc22ed · outbound

This paper cites Algorithms for inverse reinforcement learning.

ACORN: Adaptive Contrastive Optimization for Safe and Robust Fine-Grained Robotic Manipulation Algorithms for inverse reinforcement learning

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-15T22:42:20.749660Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 64a302d8-34e5-4535-a920-b19e0d7ca777 · outbound

This paper cites Learning an approximate model predictive controller with guarantees,.

ACORN: Adaptive Contrastive Optimization for Safe and Robust Fine-Grained Robotic Manipulation Learning an approximate model predictive controller with guarantees,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:42:21.048219Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 7603f7ef-fc46-4daa-9f40-2465fd6e69b6 · outbound

This paper cites Imitation learning with stability and safety guarantees,.

ACORN: Adaptive Contrastive Optimization for Safe and Robust Fine-Grained Robotic Manipulation Imitation learning with stability and safety guarantees,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:42:21.034192Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 6f2b5d21-5f01-4752-b73e-70706681544a · outbound

This paper cites A reduction of imitation learning and structured prediction to no-regret online learning,.

ACORN: Adaptive Contrastive Optimization for Safe and Robust Fine-Grained Robotic Manipulation A reduction of imitation learning and structured prediction to no-regret online learning,

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-15T22:42:20.761856Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d5f3ca9a-a328-4bca-91d2-31fa9001848d · outbound

This paper cites Efficient reductions for imitation learning,.

ACORN: Adaptive Contrastive Optimization for Safe and Robust Fine-Grained Robotic Manipulation Efficient reductions for imitation learning,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:42:21.011038Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation e126ddaa-03d0-4804-be93-28fde191ded7 · outbound

This paper cites Is imitation learning the route to humanoid robots?.

ACORN: Adaptive Contrastive Optimization for Safe and Robust Fine-Grained Robotic Manipulation Is imitation learning the route to humanoid robots?

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-15T22:42:20.769990Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c7c0475a-e818-44be-aae4-0f832e13a3d5 · outbound

This paper cites End-to-end driving via conditional imitation learning,.

ACORN: Adaptive Contrastive Optimization for Safe and Robust Fine-Grained Robotic Manipulation End-to-end driving via conditional imitation learning,

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-15T22:42:20.774144Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fa7bb8d1-f942-4736-b2a8-7e3591e15aa8 · outbound

This paper cites Models of temporal discounting 1937–2000: An in- terdisciplinary exchange between economics and psychology,.

ACORN: Adaptive Contrastive Optimization for Safe and Robust Fine-Grained Robotic Manipulation Models of temporal discounting 1937–2000: An in- terdisciplinary exchange between economics and psychology,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:42:20.979627Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 65898cd6-959e-4a0d-b056-0f151ba14364 · outbound

This paper cites Reinforcement learning with human teachers: Understanding how people want to teach robots,.

ACORN: Adaptive Contrastive Optimization for Safe and Robust Fine-Grained Robotic Manipulation Reinforcement learning with human teachers: Understanding how people want to teach robots,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:42:20.964011Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation ce157cfa-7ed9-4902-a309-147629c0ed52 · outbound

This paper cites Teachable robots: Understanding human teaching behavior to build more effective robot learners,.

ACORN: Adaptive Contrastive Optimization for Safe and Robust Fine-Grained Robotic Manipulation Teachable robots: Understanding human teaching behavior to build more effective robot learners,

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-15T22:42:20.786068Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 62c37c17-a956-452f-8d55-5d80905a6457 · outbound

This paper cites Dealing with multiple experts and non-stationarity in inverse reinforcement learning: an application to real-life problems,.

ACORN: Adaptive Contrastive Optimization for Safe and Robust Fine-Grained Robotic Manipulation Dealing with multiple experts and non-stationarity in inverse reinforcement learning: an application to real-life problems,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:42:20.940972Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 780dcbff-76d0-45b3-8b13-d0692ab8f613 · outbound

This paper cites One-shot imitation in a non-stationary environment via multi-modal skill,.

ACORN: Adaptive Contrastive Optimization for Safe and Robust Fine-Grained Robotic Manipulation One-shot imitation in a non-stationary environment via multi-modal skill,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:42:20.927093Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 07955483-2970-4938-bdbf-b656ac174cc7 · outbound

This paper cites Imitation learning: Progress, taxonomies and challenges,.

ACORN: Adaptive Contrastive Optimization for Safe and Robust Fine-Grained Robotic Manipulation Imitation learning: Progress, taxonomies and challenges,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:42:20.912823Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 02b43079-ba6b-4fd7-bfda-a7a76ee5a1e1 · outbound

This paper cites Curriculum learning,.

ACORN: Adaptive Contrastive Optimization for Safe and Robust Fine-Grained Robotic Manipulation Curriculum learning,

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-15T22:42:20.802211Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5104a209-c160-4c16-8b76-f21872d571bc · outbound

This paper cites Lerobot: State-of-the-art machine learning for real-world robotics in pytorch,.

ACORN: Adaptive Contrastive Optimization for Safe and Robust Fine-Grained Robotic Manipulation Lerobot: State-of-the-art machine learning for real-world robotics in pytorch,

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-15T22:42:20.806613Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.