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Paper Citation Record · LEDGER

Adaptation of Generalist Robot Policies with Minimal Data

As of 16 August 2026, this Paper Citation Record lists 61 of 61 outbound references and 0 inbound Pith citation observations for arXiv:2608.11363.

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

pith.paper-citation-record.v1
2608.11363 v1

Coverage vector

measured 61 of 61 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T14:18:49.466221Z

measured 61 of 61 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

61 of 61 outbound references displayed

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  • verified fuzzy7
  • unresolved50
  • parse uncertain0
  • malformed identifier3
  • metadata mismatch0

External citation measurements

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Outbound references

Observation d2d59de3-dff4-4ed1-9e1d-dd615f5ab0d2 · outbound

This paper cites From Imitation to Refinement -- Residual RL for Precise Assembly.

Adaptation of Generalist Robot Policies with Minimal Data From Imitation to Refinement -- Residual RL for Precise Assembly

Reference 1

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source=pdf_text observed=2026-08-15T14:18:47.581330Z digest=sha256:e2db624bd7ff047ed39fbe8a9f12dd58c8c0c04b63be6e9a5b4f5865983f6c42

Observation ffb0d440-7a5e-462b-a7c1-f7f47716e27b · outbound

This paper cites Residual off-policy rl for finetuning behavior cloning policies, 2025.

Adaptation of Generalist Robot Policies with Minimal Data Residual off-policy rl for finetuning behavior cloning policies, 2025

Reference 2

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source=pdf_text observed=2026-08-15T14:18:47.625562Z digest=sha256:82ef851ea6f2daf1ede2d52144a01c7177dacc498f50c619c9607180d7fd0c8a

Observation e5dd80fd-5be6-4a0d-b139-5490428dff10 · outbound

This paper cites Efficient Online Reinforcement Learning with Offline Data.

Adaptation of Generalist Robot Policies with Minimal Data Efficient Online Reinforcement Learning with Offline Data

Reference 3

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source=pdf_text observed=2026-08-15T14:18:47.631297Z digest=sha256:5e1830d54a85640919bfd7ccf890d9b87bc03521d7cb2c096f9d27b71f60bd49

Observation dfc27b98-e8ad-4c93-b03e-3bda47c1694a · outbound

This paper cites $\pi_0$: A Vision-Language-Action Flow Model for General Robot Control.

Adaptation of Generalist Robot Policies with Minimal Data $\pi_0$: A Vision-Language-Action Flow Model for General Robot Control

Reference 4

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source=pdf_text observed=2026-08-15T14:18:47.709763Z digest=sha256:469b078ae32c3b4263318422cf019f7dee2fd4ac5f080c9c68eddb5fc5868ca6

Observation 19cfe6fe-6314-4811-950f-0fc602e911f9 · outbound

This paper cites RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control.

Adaptation of Generalist Robot Policies with Minimal Data RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control

Reference 5

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source=pdf_text observed=2026-08-15T14:18:47.714515Z digest=sha256:0b0fcd203710b083d46853f825c924759beffda758d0d51fd1b172d27cfd1e41

Observation 2d591859-3b39-448f-bca3-9dfdba9cfb04 · outbound

This paper cites RT-1: Robotics Transformer for Real-World Control at Scale.

Adaptation of Generalist Robot Policies with Minimal Data RT-1: Robotics Transformer for Real-World Control at Scale

Reference 6

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source=pdf_text observed=2026-08-15T14:18:47.718571Z digest=sha256:c842663748c3eb8c94a93e9df8422de4543e46653510993bad94ce7b55876cc0

Observation 371356fd-3eff-42f7-ac40-dceb42c589ff · outbound

This paper cites Language models are few-shot learners.

Adaptation of Generalist Robot Policies with Minimal Data Language models are few-shot learners

Reference 7

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source=pdf_text observed=2026-08-15T14:18:47.809316Z digest=sha256:98b821047e005a69293c5670da46b2a7b750815a1a708c28fad827e5bba22867

Observation 8142044c-e9fc-4c21-aaaa-65f370aa0c6d · outbound

This paper cites Emerging Properties in Self-Supervised Vision Transformers.

Adaptation of Generalist Robot Policies with Minimal Data Emerging Properties in Self-Supervised Vision Transformers

Reference 8

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source=pdf_text observed=2026-08-15T14:18:47.814914Z digest=sha256:335dbfc34ed755a9b91ebbc5871132f16e16dcda586ae9b30a24cfb4aa426bfc

Observation a2712e93-6726-4f5f-a7f2-c50ed3de7581 · outbound

This paper cites Causal confusion in imitation learning.

Adaptation of Generalist Robot Policies with Minimal Data Causal confusion in imitation learning

Reference 9

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source=pdf_text observed=2026-08-15T14:18:47.879273Z digest=sha256:3ccbb02b4d629cb5c24ad92aa10d08326d72189e30eb5a9e7168270c4c8a512a

Observation a19d1fb8-0b8d-4314-853b-29fe9cc380ef · outbound

This paper cites BERT: Pre-training of deep bidirectional transformers for language understanding.

Adaptation of Generalist Robot Policies with Minimal Data BERT: Pre-training of deep bidirectional transformers for language understanding

Reference 10

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source=pdf_text observed=2026-08-15T14:18:47.906923Z digest=sha256:199a32cfd7e5dfcb49c21ea3a309b02b1a9f48777339230645a687af69dde79f

Observation 44fcc2b5-fc10-49e6-84f1-abdf3f47816c · outbound

This paper cites EXPO: Stable Reinforcement Learning with Expressive Policies.

Adaptation of Generalist Robot Policies with Minimal Data EXPO: Stable Reinforcement Learning with Expressive Policies

Reference 11

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source=pdf_text observed=2026-08-15T14:18:47.911705Z digest=sha256:0a25bcf546b01d36400a9f1cd86e632923288ea8617c365c8b0e0dabc54277c7

Observation 7a33053a-e99b-4aff-b368-028aa7ab6bb5 · outbound

This paper cites One-Shot Imitation Learning.

Adaptation of Generalist Robot Policies with Minimal Data One-Shot Imitation Learning

Reference 12

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source=pdf_text observed=2026-08-15T14:18:48.012561Z digest=sha256:2a5c570a39038c9cdf47c18bc38d33211dabede3b1ef8f2703f3b02ff8fff8ce

Observation a434c255-ed5a-4f7e-978c-744346feb2a1 · outbound

This paper cites One-Shot Visual Imitation Learning via Meta-Learning.

Adaptation of Generalist Robot Policies with Minimal Data One-Shot Visual Imitation Learning via Meta-Learning

Reference 13

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source=pdf_text observed=2026-08-15T14:18:48.063115Z digest=sha256:d4a85b46e6a24a41520832e7067d340262829bb295e0e2289ce327df479a9d0e

Observation cb1ab642-0863-4956-862a-f3232ae76c35 · outbound

This paper cites A minimalist approach to offline reinforcement learning,.

Adaptation of Generalist Robot Policies with Minimal Data A minimalist approach to offline reinforcement learning,

Reference 14

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source=pdf_text observed=2026-08-15T14:18:48.107607Z digest=sha256:a6c1650ecd32a856e29c2607b704764e7a059bf70434ae8f63676765b2a9384d

Observation 526274dd-3e0b-4d21-b315-7afc49e5f538 · outbound

This paper cites Addressing Function Approximation Error in Actor-Critic Methods.

Adaptation of Generalist Robot Policies with Minimal Data Addressing Function Approximation Error in Actor-Critic Methods

Reference 15

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source=pdf_text observed=2026-08-15T14:18:48.159594Z digest=sha256:ff00e3cc8fa8aa12949cfd2f892dc818793e4660f978488d44f87ff48486aeca

Observation 16041ca8-a6dc-49ad-a75f-9b7e89a93b0c · outbound

This paper cites Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor.

Adaptation of Generalist Robot Policies with Minimal Data Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor

Reference 16

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source=pdf_text observed=2026-08-15T14:18:48.166704Z digest=sha256:364c2704381a42ab1ae21fa831c310adce6ab90a6eff3b01bc644c9bb1f076ec

Observation 99af61fe-e5c2-4e1d-bc49-0bf3a6bbfa90 · outbound

This paper cites Teach a Robot to FISH: Versatile Imitation from One Minute of Demonstrations.

Adaptation of Generalist Robot Policies with Minimal Data Teach a Robot to FISH: Versatile Imitation from One Minute of Demonstrations

Reference 17

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source=pdf_text observed=2026-08-15T14:18:48.262038Z digest=sha256:d44a702b2972485a94711d6b806806ecc6feb0879659e2bd5122d376fc7d8346

Observation 379ac8cd-2111-4833-b9ba-e3cf61e3b845 · outbound

This paper cites LoRA: Low-Rank Adaptation of Large Language Models.

Adaptation of Generalist Robot Policies with Minimal Data LoRA: Low-Rank Adaptation of Large Language Models

Reference 18

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source=pdf_text observed=2026-08-15T14:18:48.268930Z digest=sha256:d29a0b603801e4d146c856c225d8e6f15c66ffe7817f262f9bebfd071e3ff1a7

Observation 11549360-2aaa-4b05-9814-b85366f6f68e · outbound

This paper cites Imitation Bootstrapped Reinforcement Learning.

Adaptation of Generalist Robot Policies with Minimal Data Imitation Bootstrapped Reinforcement Learning

Reference 19

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source=pdf_text observed=2026-08-15T14:18:48.327281Z digest=sha256:cc41093d3f003b419ac7e5ab50d483b2815d04e14be8b0259c5f077a3f2ecfc0

Observation ea8b0b21-1d12-4121-9a33-231096fc8b7b · outbound

This paper cites $\pi_{0.5}$: a Vision-Language-Action Model with Open-World Generalization.

Adaptation of Generalist Robot Policies with Minimal Data $\pi_{0.5}$: a Vision-Language-Action Model with Open-World Generalization

Reference 20

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source=pdf_text observed=2026-08-15T14:18:48.332342Z digest=sha256:f3c80bbb03c3977992aac450720028d4250f8e4739e879c3dc77bc38ea431918

Observation 3e50373e-d61d-4f67-97a3-733adb3bb4c7 · outbound

This paper cites Fine-Tuning Vision-Language-Action Models: Optimizing Speed and Success.

Adaptation of Generalist Robot Policies with Minimal Data Fine-Tuning Vision-Language-Action Models: Optimizing Speed and Success

Reference 21

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source=pdf_text observed=2026-08-15T14:18:48.419080Z digest=sha256:7cfd94f01b30e5c5d3687b6dd5871906dc09cb7491a497c2e9d4913b26e57137

Observation bea1e437-42e4-42ca-8d23-9b037facdbe1 · outbound

This paper cites Offline Reinforcement Learning with Implicit Q-Learning.

Adaptation of Generalist Robot Policies with Minimal Data Offline Reinforcement Learning with Implicit Q-Learning

Reference 22

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source=pdf_text observed=2026-08-15T14:18:48.425371Z digest=sha256:85e98b675fdffadbcca570ada651ad030e3dfa18ad06c6cf2d74dc8bf68095aa

Observation cc07b852-5de6-4c64-96d9-5f408a3308cd · outbound

This paper cites Pre-Training for Robots: Offline RL Enables Learning New Tasks from a Handful of Trials.

Adaptation of Generalist Robot Policies with Minimal Data Pre-Training for Robots: Offline RL Enables Learning New Tasks from a Handful of Trials

Reference 23

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source=pdf_text observed=2026-08-15T14:18:48.431134Z digest=sha256:109bd367b47128a0be0bd49eef73747cefc01630cca588a4c53cf812cdd812cb

Observation 62ead38a-436e-43f5-9c4e-24d15d039175 · outbound

This paper cites LIBERO: Benchmarking Knowledge Transfer for Lifelong Robot Learning.

Adaptation of Generalist Robot Policies with Minimal Data LIBERO: Benchmarking Knowledge Transfer for Lifelong Robot Learning

Reference 24

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source=pdf_text observed=2026-08-15T14:18:48.486860Z digest=sha256:8fda7f1cd9376eaacdf42560dcdb62a3b75c071ed311fcaf4188b865a04b817c

Observation becd48b7-16c0-43b4-9b1f-a2ba0c1eda03 · outbound

This paper cites Few-shot parameter-efficient fine-tuning is better and cheaper than in-context learning,.

Adaptation of Generalist Robot Policies with Minimal Data Few-shot parameter-efficient fine-tuning is better and cheaper than in-context learning,

Reference 25

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source=pdf_text observed=2026-08-15T14:18:48.492603Z digest=sha256:dd67dcb1aa7aab35e743976a71a832b246a4280ccc424f7957e7014dd7937631

Observation 7854f3c6-0821-42fa-892d-74017b898ea1 · outbound

This paper cites SERL: A Software Suite for Sample-Efficient Robotic Reinforcement Learning.

Adaptation of Generalist Robot Policies with Minimal Data SERL: A Software Suite for Sample-Efficient Robotic Reinforcement Learning

Reference 26

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source=pdf_text observed=2026-08-15T14:18:48.605585Z digest=sha256:41eccf8f9343a9eb858a00b5101b2a647748a09d559d3278fe97b408082ddea8

Observation ade8d8dd-59e8-4d12-b661-e9019c6d7f85 · outbound

This paper cites Policy Agnostic RL: Offline RL and Online RL Fine-Tuning of Any Class and Backbone.

Adaptation of Generalist Robot Policies with Minimal Data Policy Agnostic RL: Offline RL and Online RL Fine-Tuning of Any Class and Backbone

Reference 27

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source=pdf_text observed=2026-08-15T14:18:48.614940Z digest=sha256:33dd5794bff33d097317a0188be1707542efc827b83143a911235787e2c4cbe8

Observation 563fd47d-7b06-4cb3-bc5e-fde2868d5aea · outbound

This paper cites Cal-ql: Calibrated offline rl pre-training for efficient online fine-tuning,.

Adaptation of Generalist Robot Policies with Minimal Data Cal-ql: Calibrated offline rl pre-training for efficient online fine-tuning,

Reference 28

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-15T14:18:48.674912Z digest=sha256:c3b49b089475da1dc86fbeb150e2429c51547adc7ad2284f48ca398f0ceeb79b

Observation 4f57c9bc-df85-46b2-af56-98275fb3781d · outbound

This paper cites Robocasa365: A large- scale simulation framework for training and benchmarking generalist robots, 2026.

Adaptation of Generalist Robot Policies with Minimal Data Robocasa365: A large- scale simulation framework for training and benchmarking generalist robots, 2026

Reference 29

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source=pdf_text observed=2026-08-15T14:18:48.772669Z digest=sha256:818cd8ba1f9d0fbf433cf1b6911072c3f5a245834798379d59e0072139ec0e93

Observation 9cbc696c-95c1-4448-8d40-e4c9632b1613 · outbound

This paper cites Keypoint Action Tokens Enable In-Context Imitation Learning in Robotics.

Adaptation of Generalist Robot Policies with Minimal Data Keypoint Action Tokens Enable In-Context Imitation Learning in Robotics

Reference 30

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source=pdf_text observed=2026-08-15T14:18:48.821772Z digest=sha256:5218beaf5b955508016be7794e07f5b7305b1189037369ac853d83495d63ef44

Observation f76fbef3-3a08-4de1-9376-e884ec0d969a · outbound

This paper cites Much ado about noising: Dispelling the myths of generative robotic control, 2026.

Adaptation of Generalist Robot Policies with Minimal Data Much ado about noising: Dispelling the myths of generative robotic control, 2026

Reference 31

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source=pdf_text observed=2026-08-15T14:18:48.828912Z digest=sha256:a7d622fddc037d9b9f5e70cb5ea4ae9eb89582453468d1b503993e709bda3368

Observation 202e891e-1e7a-4dc9-a203-503cde2e9e67 · outbound

This paper cites OGPO: Sample Efficient Full-Finetuning of Generative Control Policies.

Adaptation of Generalist Robot Policies with Minimal Data OGPO: Sample Efficient Full-Finetuning of Generative Control Policies

Reference 32

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local_arxiv, observed 2026-08-15T14:18:49.830279Z

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source=pdf_text observed=2026-08-15T14:18:48.877194Z digest=sha256:a936381ce36b4c17b9d01c2aeedfd07e0ab5668c6b0cffd92cd7057fce2c72e0

Observation 7bb5dd2d-2719-49ef-a534-13019b5b6099 · outbound

This paper cites Learning Transferable Visual Models From Natural Language Supervision.

Adaptation of Generalist Robot Policies with Minimal Data Learning Transferable Visual Models From Natural Language Supervision

Reference 33

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source=pdf_text observed=2026-08-15T14:18:48.882367Z digest=sha256:87fe2d8c5d16811a4f8ffb067c142a1be0ea0819c7cd0b145102c111c5a2c512

Observation 4e6290d2-d37e-4ca2-b505-b67daf5a74ee · outbound

This paper cites Diffusion Policy Policy Optimization.

Adaptation of Generalist Robot Policies with Minimal Data Diffusion Policy Policy Optimization

Reference 34

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source=pdf_text observed=2026-08-15T14:18:48.889668Z digest=sha256:f2a5bb2cdbc8adadd8eed53d0a9d367aac87f6106e5fd7f2304b0611ec0e7ebb

Observation 3fe86093-37d7-4d1f-8af9-7882b8955f8c · outbound

This paper cites From Prior to Pro: Efficient Skill Mastery via Distribution Contractive RL Finetuning.

Adaptation of Generalist Robot Policies with Minimal Data From Prior to Pro: Efficient Skill Mastery via Distribution Contractive RL Finetuning

Reference 36

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source=pdf_text observed=2026-08-15T14:18:48.974668Z digest=sha256:b35f1042bc00764b1622c66cf09865de3f9a8cf0339a793274fab51281b09ee5

Observation 1f8c658b-de06-4750-8d8a-2867e5bbc758 · outbound

This paper cites Octo: An Open-Source Generalist Robot Policy.

Adaptation of Generalist Robot Policies with Minimal Data Octo: An Open-Source Generalist Robot Policy

Reference 37

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source=pdf_text observed=2026-08-15T14:18:48.979655Z digest=sha256:2eb1406e2ecda902f6ba4ca2c742e4d2209e7f40d1acb6ac18cf9c3443d2dc9e

Observation 49f722ad-5424-4c3f-a4c2-c53d2b8f9e96 · outbound

This paper cites Instant policy: In-context imitation learning via graph diffusion,.

Adaptation of Generalist Robot Policies with Minimal Data Instant policy: In-context imitation learning via graph diffusion,

Reference 38

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verified fuzzy
raw_fallback, observed 2026-08-15T14:18:51.562903Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-15T14:18:49.035761Z digest=sha256:e4a9d0d10229d19e7258827b1074a1e0a6b7f9cc64008adf25014957908a1974

Observation ae7ea45b-dd15-46c2-9cc1-034163b52939 · outbound

This paper cites Steering Your Diffusion Policy with Latent Space Reinforcement Learning.

Adaptation of Generalist Robot Policies with Minimal Data Steering Your Diffusion Policy with Latent Space Reinforcement Learning

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-15T14:18:49.049248Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T14:18:49.049248Z digest=sha256:72836822199079701bf882d11cca44be686086da6a085690c02125f13a72e15f

Observation 456b9199-b326-4175-bc6a-755f4f27bfe5 · outbound

This paper cites RL Token: Bootstrapping Online RL with Vision-Language-Action Models.

Adaptation of Generalist Robot Policies with Minimal Data RL Token: Bootstrapping Online RL with Vision-Language-Action Models

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-15T14:18:49.113642Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T14:18:49.113642Z digest=sha256:92c3676301554befebe5d5d0a79f37607cdbb0f446e8c66b694f6f77a1b2b2e2

Observation 21940322-246e-4b1c-8234-750908d9700c · outbound

This paper cites World Action Models are Zero-shot Policies.

Adaptation of Generalist Robot Policies with Minimal Data World Action Models are Zero-shot Policies

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-15T14:18:49.119773Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T14:18:49.119773Z digest=sha256:d562c04a66bcc7ef56b9e6aaf8d977c7d2198d252e13494a2b29911cafeb3766

Observation c2fd2877-bdea-4da8-ad51-481ae82e707e · outbound

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

Adaptation of Generalist Robot Policies with Minimal Data Learning Fine-Grained Bimanual Manipulation with Low-Cost Hardware

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-15T14:18:49.125335Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T14:18:49.125335Z digest=sha256:6ca3ce048d5867f698837bd9dc1d011b7e347dd36c2678f8aec49845c41cb380

Observation 6be05a0b-b142-4d13-8387-de8bf92f0f86 · outbound

This paper cites LIBERO-PRO: Towards Robust and Fair Evaluation of Vision-Language-Action Models Beyond Memorization.

Adaptation of Generalist Robot Policies with Minimal Data LIBERO-PRO: Towards Robust and Fair Evaluation of Vision-Language-Action Models Beyond Memorization

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-15T14:18:49.177808Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T14:18:49.177808Z digest=sha256:9bbe90ceb00802b0ccd493d45922bc79594046c5889b53d246959ac9b685d75d

Observation 4f2593d6-f2cd-4636-9564-1503e6d0e416 · outbound

This paper cites Efficient Online Reinforcement Learning Fine-Tuning Need Not Retain Offline Data.

Adaptation of Generalist Robot Policies with Minimal Data Efficient Online Reinforcement Learning Fine-Tuning Need Not Retain Offline Data

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-15T14:18:49.202062Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T14:18:49.202062Z digest=sha256:c5eb62dd5494d10b372f6b472ecf115e4ed09169e9018faaed087a331c4dc0c5

Observation a9563c02-4494-4e24-9567-2f23f427e2fb · outbound

This paper cites an unresolved cited work.

Adaptation of Generalist Robot Policies with Minimal Data Unresolved cited work

Reference 49

Resolution
unresolved
raw_fallback, observed 2026-08-15T14:18:51.547066Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-15T14:18:49.207134Z digest=sha256:98d1fb44d7f8eb4d229e9168d59cf611ab642af026e3b4038408eaebc22382aa

Observation 848fbd74-6ddb-4dd7-a944-5185ac6da6d6 · outbound

This paper cites an unresolved cited work.

Adaptation of Generalist Robot Policies with Minimal Data Unresolved cited work

Reference 50

Resolution
unresolved
raw_fallback, observed 2026-08-15T14:18:51.455074Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-15T14:18:49.212758Z digest=sha256:e9ac1c72fba68e02c78dc82827ebb5b6b1eb1ec854ec8d20d6987a751f350a85

Observation 1691892f-18cf-4e2a-b1f3-2444c12c473a · outbound

This paper cites an unresolved cited work.

Adaptation of Generalist Robot Policies with Minimal Data Unresolved cited work

Reference 51

Resolution
unresolved
raw_fallback, observed 2026-08-15T14:18:51.368484Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-15T14:18:49.261247Z digest=sha256:b1e25f6003f98c3abe9bb1e0f3df206c9cd6df791d48e20ca1f7109c7468d9bf

Observation a578a947-282e-4703-b9e7-376e4d5610ec · outbound

This paper cites an unresolved cited work.

Adaptation of Generalist Robot Policies with Minimal Data Unresolved cited work

Reference 52

Resolution
unresolved
raw_fallback, observed 2026-08-15T14:18:51.349505Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-15T14:18:49.267400Z digest=sha256:200b98dfebf37775335afc71a5692ed059d7d6c2cbc16608daab2c5b9753d935

Observation bc68c8b3-7ac5-4101-ae61-35b30deefc86 · outbound

This paper cites an unresolved cited work.

Adaptation of Generalist Robot Policies with Minimal Data Unresolved cited work

Reference 53

Resolution
unresolved
raw_fallback, observed 2026-08-15T14:18:51.294633Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-15T14:18:49.273776Z digest=sha256:c45d49eb12815044ec8c53dcd0c1022a0e5e22e09197ba470d54559422a8d6d5

Observation ddc76809-9685-454e-9a8a-c41b1ffadbb3 · outbound

This paper cites an unresolved cited work.

Adaptation of Generalist Robot Policies with Minimal Data Unresolved cited work

Reference 54

Resolution
unresolved
raw_fallback, observed 2026-08-15T14:18:51.137581Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-15T14:18:49.280796Z digest=sha256:2f4425eaba18b9cd63a33f9fd4a29d877dea3e89c422298ce1bde958e095aa0c

Observation c93fc242-5726-4f73-bdaf-09bce24cb3e5 · outbound

This paper cites an unresolved cited work.

Adaptation of Generalist Robot Policies with Minimal Data Unresolved cited work

Reference 55

Resolution
unresolved
raw_fallback, observed 2026-08-15T14:18:51.029136Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-15T14:18:49.331263Z digest=sha256:0262269ca356d9be09260a0f84d29311d09bb6f098d3006b8dd22db7d4ed2277

Observation c4e5a30f-5d0d-4891-9768-4e39fa1012a8 · outbound

This paper cites an unresolved cited work.

Adaptation of Generalist Robot Policies with Minimal Data Unresolved cited work

Reference 56

Resolution
unresolved
raw_fallback, observed 2026-08-15T14:18:50.916624Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-15T14:18:49.353077Z digest=sha256:bd46d751a4ef303d46a804f2359ec0aa60685d4de1a65f9a2cdbe3adf8202e45

Observation ec8916a0-f62b-41b3-a50a-2897e501483b · outbound

This paper cites an unresolved cited work.

Adaptation of Generalist Robot Policies with Minimal Data Unresolved cited work

Reference 57

Resolution
unresolved
raw_fallback, observed 2026-08-15T14:18:50.736607Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-15T14:18:49.359751Z digest=sha256:b516cca6b0d2dc2284a0db2b2c88fd78f920b7ec3f8ed15eb25e33a407baac98

Observation 037d79fd-aef8-4a53-91f3-e68f440551f4 · outbound

This paper cites The environment provides two camera views: anagentview third-person camera and arobot0_eye_in_hand wrist camera, both rendered at224×224 pixels.

Adaptation of Generalist Robot Policies with Minimal Data The environment provides two camera views: anagentview third-person camera and arobot0_eye_in_hand wrist camera, both rendered at224×224 pixels

Reference 58

Resolution
malformed identifier
raw_fallback, observed 2026-08-15T14:18:50.670196Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-15T14:18:49.365883Z digest=sha256:cb3e1267969d12a9d9e4d88a4adcc176c9cb51b2267435f8c1a7ce58e3eaeb8d

Observation f9b96d75-9d40-4c71-8edb-a60087595ef2 · outbound

This paper cites an unresolved cited work.

Adaptation of Generalist Robot Policies with Minimal Data Unresolved cited work

Reference 59

Resolution
unresolved
raw_fallback, observed 2026-08-15T14:18:50.650680Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-15T14:18:49.422133Z digest=sha256:29052700e8ae3a2084564255e1f6649146c939a02afc7ab3c381c43ac60714a0

Observation 065b2a31-1e7d-4d22-956e-83049b5ad771 · outbound

This paper cites an unresolved cited work.

Adaptation of Generalist Robot Policies with Minimal Data Unresolved cited work

Reference 60

Resolution
unresolved
raw_fallback, observed 2026-08-15T14:18:50.499971Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-15T14:18:49.453608Z digest=sha256:cb77af99a8cb9cdfe2b6d0f53dbdb139a42349471ec1d292ec2bc8bf805619eb

Observation 687da93d-e840-4758-bf7c-809abfed138c · outbound

This paper cites an unresolved cited work.

Adaptation of Generalist Robot Policies with Minimal Data Unresolved cited work

Reference 61

Resolution
unresolved
raw_fallback, observed 2026-08-15T14:18:50.481311Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-15T14:18:49.460663Z digest=sha256:9e638f08878f23003b68146ca8a9687828b4e5a05edfe2f2bdc387ff5a696345

Observation f7475807-4e85-4590-bf59-f67cf3b1d219 · outbound

This paper cites put both moka pots on the stove.

Adaptation of Generalist Robot Policies with Minimal Data put both moka pots on the stove

Reference 62

Resolution
malformed identifier
raw_fallback, observed 2026-08-15T14:18:50.417637Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-15T14:18:49.466221Z digest=sha256:da05bb4596edd9c13f99f68677963349e33fef959609e083270ce79508eed307

Observation 61b10ed1-9ae2-45d1-8141-b71daf5abac4 · outbound

This paper cites A Minimalist Approach to Offline Reinforcement Learning.

Adaptation of Generalist Robot Policies with Minimal Data A Minimalist Approach to Offline Reinforcement Learning

Reference 2021

Resolution
unresolved
no resolver link, observed 2026-08-15T14:18:48.122903Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T14:18:48.122903Z digest=sha256:51814d38ef24fcd8e53d1a08d15f1c193eb2d079b6bc66e2a4527eb60df35fc2

Observation 193cefd7-3f0f-42e8-9787-cddafb633b3a · outbound

This paper cites Few-Shot Parameter-Efficient Fine-Tuning is Better and Cheaper than In-Context Learning.

Adaptation of Generalist Robot Policies with Minimal Data Few-Shot Parameter-Efficient Fine-Tuning is Better and Cheaper than In-Context Learning

Reference 2022

Resolution
unresolved
no resolver link, observed 2026-08-15T14:18:48.502339Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T14:18:48.502339Z digest=sha256:c1c2a57b7a1198bb063b9b05c7c2f23236d690eb7f178813215ce9df4536d3ca

Observation ddf1f8fd-8ac0-4cd9-b3fb-66f404bbb26a · outbound

This paper cites Cal-QL: Calibrated Offline RL Pre-Training for Efficient Online Fine-Tuning.

Adaptation of Generalist Robot Policies with Minimal Data Cal-QL: Calibrated Offline RL Pre-Training for Efficient Online Fine-Tuning

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-08-15T14:18:48.684751Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T14:18:48.684751Z digest=sha256:cefd7246056ce541a82bbf67dfc627e0db955c21b75eddf127096a2ece6ef992

Observation 60080b21-aa3a-4ccf-9acd-37534f92d017 · outbound

This paper cites Instant Policy: In-Context Imitation Learning via Graph Diffusion.

Adaptation of Generalist Robot Policies with Minimal Data Instant Policy: In-Context Imitation Learning via Graph Diffusion

Reference 2025

Resolution
unresolved
no resolver link, observed 2026-08-15T14:18:49.041973Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T14:18:49.041973Z digest=sha256:34da647f35530550a8d33ada182a060e3a073c67898417e5083dd029d85bc181

Pith citing papers

No inbound Pith citation observations are available.