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Paper Citation Record · LEDGER

Robotic Programmer: Video Instructed Policy Code Generation for Robotic Manipulation

As of 11 August 2026, this Paper Citation Record lists 35 of 35 outbound references and 1 inbound Pith citation observation for arXiv:2501.04268.

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

pith.paper-citation-record.v1
2501.04268 v1

Coverage vector

measured 35 of 35 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T21:41:29.112544Z

measured 36 of 36 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-04T19:45:35.363677Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

35 of 35 outbound references displayed

  • verified exact1
  • verified fuzzy7
  • unresolved27
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 6fb90d2b-618e-4ae5-b0c5-8dd8d7483186 · outbound

This paper cites GPT-4 Technical Report.

Robotic Programmer: Video Instructed Policy Code Generation for Robotic Manipulation GPT-4 Technical Report

Reference 1

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source=pdf_text observed=2026-08-10T21:41:28.980655Z digest=sha256:b547822838db92aa484026e961a7dbc1ef89eb926be69e29f510d37ca3c5c478

Observation 3869a079-948c-4346-8e61-cd69fa38da74 · outbound

This paper cites LLaMA: Open and Efficient Foundation Language Models.

Robotic Programmer: Video Instructed Policy Code Generation for Robotic Manipulation LLaMA: Open and Efficient Foundation Language Models

Reference 2

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source=pdf_text observed=2026-08-10T21:41:28.985320Z digest=sha256:84b1a8ea9fb29a32e515dc5303d4d3dd0df1cbda3f1d6cce63e1e9d8749dc73b

Observation db453c77-7842-449e-8aad-968d3c912f7a · outbound

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

Robotic Programmer: Video Instructed Policy Code Generation for Robotic Manipulation RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control

Reference 3

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source=pdf_text observed=2026-08-10T21:41:28.989604Z digest=sha256:3e9512babf46a9c2daf21f48e33077e12ef4ff08b578cddb36eacb538ff7720c

Observation 47b9eb13-c563-4a63-956f-75232caed42c · outbound

This paper cites Open X-Embodiment: Robotic Learning Datasets and RT-X Models.

Robotic Programmer: Video Instructed Policy Code Generation for Robotic Manipulation Open X-Embodiment: Robotic Learning Datasets and RT-X Models

Reference 4

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source=pdf_text observed=2026-08-10T21:41:28.993607Z digest=sha256:2db55fe9d33ff8a853ae2a20e6065d1ad8a8713d445878dd47d8dfaf826c1f17

Observation d661c040-ec41-46c1-93b0-40ce955272fb · outbound

This paper cites OpenVLA: An Open-Source Vision-Language-Action Model.

Robotic Programmer: Video Instructed Policy Code Generation for Robotic Manipulation OpenVLA: An Open-Source Vision-Language-Action Model

Reference 5

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source=pdf_text observed=2026-08-10T21:41:28.998003Z digest=sha256:27aff46fec46364f518a63991abaa39fcdc696a87564166f4e933a5b780b6970

Observation ed1f390e-9632-400f-bf15-fbc908bf2afb · outbound

This paper cites RoboCodeX: Multimodal Code Generation for Robotic Behavior Synthesis.

Robotic Programmer: Video Instructed Policy Code Generation for Robotic Manipulation RoboCodeX: Multimodal Code Generation for Robotic Behavior Synthesis

Reference 6

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source=pdf_text observed=2026-08-10T21:41:29.002367Z digest=sha256:8faf197e9a8e24726a0c7f601f7ca2ef57de54172c10a7e7825874a1638317a2

Observation 68bf88ad-4625-4114-8f2c-f23a39440796 · outbound

This paper cites Affordances from human videos as a versatile representation for robotics,.

Robotic Programmer: Video Instructed Policy Code Generation for Robotic Manipulation Affordances from human videos as a versatile representation for robotics,

Reference 7

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source=pdf_text observed=2026-08-10T21:41:29.007105Z digest=sha256:fed7d521a96145f7b985ad61b189172e3eb86a20a3c7dcc5f5cac3f0f774194f

Observation f72d63e7-b15c-450a-9e38-ff8e05d4aaf3 · outbound

This paper cites DROID: A Large-Scale In-The-Wild Robot Manipulation Dataset.

Robotic Programmer: Video Instructed Policy Code Generation for Robotic Manipulation DROID: A Large-Scale In-The-Wild Robot Manipulation Dataset

Reference 8

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source=pdf_text observed=2026-08-10T21:41:29.010743Z digest=sha256:210c54f094d6f5710e83d5bd2a3a8dad62e036d7f376e286e02a411446e0d2d7

Observation 292e346e-3465-47c8-89be-e1214bd629fe · outbound

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

Robotic Programmer: Video Instructed Policy Code Generation for Robotic Manipulation Perceiver-actor: A multi- task transformer for robotic manipulation,

Reference 9

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source=pdf_text observed=2026-08-10T21:41:29.014589Z digest=sha256:2a84c42fecf6f7721be7d9434c2bb338a074ae63714e7e3c8fe3a7411f833a98

Observation 10064ce0-b93e-4e1c-82f3-e99e3d2e8a6a · outbound

This paper cites Procedures as a representation for data in a computer program for understanding natural language,.

Robotic Programmer: Video Instructed Policy Code Generation for Robotic Manipulation Procedures as a representation for data in a computer program for understanding natural language,

Reference 10

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verified fuzzy
raw_fallback, observed 2026-08-10T21:41:29.453109Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T21:41:29.018775Z digest=sha256:15529ef2cb1d2faa7abf17361f5a521411e84ae6c1348b50acf36aa250b9f88f

Observation ce1b9580-8e74-4493-b982-fa48da29165f · outbound

This paper cites Attention is all you need,.

Robotic Programmer: Video Instructed Policy Code Generation for Robotic Manipulation Attention is all you need,

Reference 11

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source=pdf_text observed=2026-08-10T21:41:29.022495Z digest=sha256:e7ee68cff3a81b7157f6846d5fc8129f8df2aa35065307ef090f9d0494b675f6

Observation 12f5dfcb-78e4-491c-a70e-382036a456c4 · outbound

This paper cites SAM-E: leveraging visual foundation model with sequence imitation for embodied manipulation,.

Robotic Programmer: Video Instructed Policy Code Generation for Robotic Manipulation SAM-E: leveraging visual foundation model with sequence imitation for embodied manipulation,

Reference 12

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verified fuzzy
raw_fallback, observed 2026-08-10T21:41:29.434657Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T21:41:29.025796Z digest=sha256:128afd1b426ae9499a8d1136d08d0e9f51b3ca018c13a4042627b4333a326ebd

Observation 660aedeb-4eb8-470a-9b07-344a75dbed69 · outbound

This paper cites LLARVA: Vision-Action Instruction Tuning Enhances Robot Learning.

Robotic Programmer: Video Instructed Policy Code Generation for Robotic Manipulation LLARVA: Vision-Action Instruction Tuning Enhances Robot Learning

Reference 13

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source=pdf_text observed=2026-08-10T21:41:29.028549Z digest=sha256:b40ce8ede65b3e9aaecded25c5a23ca6f967717178cb9b4f1e6ff2764d775426

Observation 60177fda-ce6a-4e19-9507-8eb88406b64f · outbound

This paper cites Do as i can, not as i say: Grounding language in robotic affordances,.

Robotic Programmer: Video Instructed Policy Code Generation for Robotic Manipulation Do as i can, not as i say: Grounding language in robotic affordances,

Reference 14

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source=pdf_text observed=2026-08-10T21:41:29.031899Z digest=sha256:f0ea9624072360690ed34dd0c718094dbe025e28ffc6702bf12333558072036b

Observation 470bab7c-b039-4cd8-a351-7b4b98cca623 · outbound

This paper cites Palm-e: An embodied multimodal language model,.

Robotic Programmer: Video Instructed Policy Code Generation for Robotic Manipulation Palm-e: An embodied multimodal language model,

Reference 15

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verified fuzzy
raw_fallback, observed 2026-08-10T21:41:29.417089Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T21:41:29.034811Z digest=sha256:00971ccfd0b27b78b1731628052fbba2f4eb78ea45c5132847b4b98d30fbcfe7

Observation db498ecc-3bce-4a31-9ade-f57f1cd39200 · outbound

This paper cites Inner monologue: Embodied reasoning through planning with language models,.

Robotic Programmer: Video Instructed Policy Code Generation for Robotic Manipulation Inner monologue: Embodied reasoning through planning with language models,

Reference 16

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verified fuzzy
raw_fallback, observed 2026-08-10T21:41:29.406070Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T21:41:29.038276Z digest=sha256:677a871540a58a348f499bd3c99ce96411687513e0095b2d136aabb14e363cdd

Observation 0bc258fc-4a04-42e3-8027-ec4223a36a7a · outbound

This paper cites Progprompt: Generating situated robot task plans using large language models,.

Robotic Programmer: Video Instructed Policy Code Generation for Robotic Manipulation Progprompt: Generating situated robot task plans using large language models,

Reference 17

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source=pdf_text observed=2026-08-10T21:41:29.041799Z digest=sha256:0809a404409dd60f584a1831f4f1369af34dd2d9d5897616a9dfb2143d8a67a1

Observation 6adce849-cb42-479e-b717-5f3ddc5e7aad · outbound

This paper cites Code as policies: Language model programs for em- bodied control,.

Robotic Programmer: Video Instructed Policy Code Generation for Robotic Manipulation Code as policies: Language model programs for em- bodied control,

Reference 18

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source=pdf_text observed=2026-08-10T21:41:29.045359Z digest=sha256:2819c0b821ce7fc51e5ddd49ed6e6fa054f50a08929816d7962a51f8c08c1b91

Observation f68a8b5c-2e1c-4b8d-aeba-a6f229672c15 · outbound

This paper cites Instruct2Act: Mapping Multi-modality Instructions to Robotic Actions with Large Language Model.

Robotic Programmer: Video Instructed Policy Code Generation for Robotic Manipulation Instruct2Act: Mapping Multi-modality Instructions to Robotic Actions with Large Language Model

Reference 19

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source=pdf_text observed=2026-08-10T21:41:29.048861Z digest=sha256:76ec72fb583beb6150ec48a70bd35da5f5f76155dccf08a0454ef54d475e9c23

Observation 5a8259fa-870c-48c6-b7a1-55bdea75b977 · outbound

This paper cites V oxposer: Composable 3d value maps for robotic manipulation with language models,.

Robotic Programmer: Video Instructed Policy Code Generation for Robotic Manipulation V oxposer: Composable 3d value maps for robotic manipulation with language models,

Reference 20

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verified fuzzy
raw_fallback, observed 2026-08-10T21:41:29.381669Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T21:41:29.053200Z digest=sha256:d54d7bab1a3f0e475ec684944329602666c4368ae2edd3a0d9bb2114ec339df3

Observation 5e7aa795-a971-4249-9c47-6a16304b606f · outbound

This paper cites A unified approach for motion and force control of robot manipulators: The operational space formulation,.

Robotic Programmer: Video Instructed Policy Code Generation for Robotic Manipulation A unified approach for motion and force control of robot manipulators: The operational space formulation,

Reference 21

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source=pdf_text observed=2026-08-10T21:41:29.060589Z digest=sha256:9c702b0736bfd0e03332476e50e3ea9861108b4f8667e4f871046646ac1d1a90

Observation 7f366ea8-965c-4ec6-8af6-f14bc8428162 · outbound

This paper cites Gemini: A Family of Highly Capable Multimodal Models.

Robotic Programmer: Video Instructed Policy Code Generation for Robotic Manipulation Gemini: A Family of Highly Capable Multimodal Models

Reference 22

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source=pdf_text observed=2026-08-10T21:41:29.064366Z digest=sha256:fc27878cf8691ebd6c38a804332612e9053943b6e6467cc76d7cde2afb8b7b64

Observation 111a0ff9-f63e-459e-b718-2b5230286614 · outbound

This paper cites DeepSeek-Coder-V2: Breaking the Barrier of Closed-Source Models in Code Intelligence.

Robotic Programmer: Video Instructed Policy Code Generation for Robotic Manipulation DeepSeek-Coder-V2: Breaking the Barrier of Closed-Source Models in Code Intelligence

Reference 23

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source=pdf_text observed=2026-08-10T21:41:29.068019Z digest=sha256:193880613365a97e98c196d752a2874ffee661a9e5d62897b16467d9f29fdd61

Observation 50d27ec6-ad19-47a2-84d4-f22845275ad0 · outbound

This paper cites Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection.

Robotic Programmer: Video Instructed Policy Code Generation for Robotic Manipulation Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection

Reference 24

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source=pdf_text observed=2026-08-10T21:41:29.072377Z digest=sha256:fd1953fdcc836197d75155bc59d9f3e74ac6a522dcf763aec033dd8a9220b53b

Observation ae2ba194-cde6-4fdd-9d7c-4da4a51c3d0a · outbound

This paper cites Anygrasp: Robust and efficient grasp perception in spatial and temporal domains,.

Robotic Programmer: Video Instructed Policy Code Generation for Robotic Manipulation Anygrasp: Robust and efficient grasp perception in spatial and temporal domains,

Reference 25

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source=pdf_text observed=2026-08-10T21:41:29.076249Z digest=sha256:0254791b4f01e6090c088401832519fb7976657e82afe65fb62b5206e0a60883

Observation 180e5c0b-4ee9-469d-ab78-b51dec654545 · outbound

This paper cites Sigmoid loss for language image pre-training,.

Robotic Programmer: Video Instructed Policy Code Generation for Robotic Manipulation Sigmoid loss for language image pre-training,

Reference 26

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source=pdf_text observed=2026-08-10T21:41:29.081223Z digest=sha256:1ca173d5e97799c2828864efc72388532981fa66331d109eabe9cb41897fc718

Observation 771933c7-dafa-41fa-88af-7d6ad9a83200 · outbound

This paper cites Qwen Technical Report.

Robotic Programmer: Video Instructed Policy Code Generation for Robotic Manipulation Qwen Technical Report

Reference 27

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source=pdf_text observed=2026-08-10T21:41:29.084545Z digest=sha256:f20cc0b8a33230f2e40014b96b92ba411d1be5d52d522d48b84211b507e5f042

Observation 9579e9e4-e829-4182-a043-e8d9ccf98a58 · outbound

This paper cites Improved baselines with visual instruction tuning,.

Robotic Programmer: Video Instructed Policy Code Generation for Robotic Manipulation Improved baselines with visual instruction tuning,

Reference 28

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source=pdf_text observed=2026-08-10T21:41:29.088657Z digest=sha256:47cce92489dd9d6639638c1ac1c639db61fff6b88fa484d3e1fe18297c357632

Observation b7a4cc7a-395c-425e-9659-5b80a508e7e8 · outbound

This paper cites ShareGPT4V: Improving Large Multi-Modal Models with Better Captions.

Robotic Programmer: Video Instructed Policy Code Generation for Robotic Manipulation ShareGPT4V: Improving Large Multi-Modal Models with Better Captions

Reference 29

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source=pdf_text observed=2026-08-10T21:41:29.092175Z digest=sha256:1586e03f94e8860528733a8fbf6b70b84ce871834ca9bd099d7f6b6a13eb78f9

Observation 1de3cfa0-5196-436e-88dc-9a81ca17992f · outbound

This paper cites Hello gpt-4o,.

Robotic Programmer: Video Instructed Policy Code Generation for Robotic Manipulation Hello gpt-4o,

Reference 30

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verified fuzzy
raw_fallback, observed 2026-08-10T21:41:29.342956Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T21:41:29.095920Z digest=sha256:099000716a9923c6a5ce81d781ea7aa59ea6ff434b272a39d35cae26f6367182

Observation 2ec0a5df-d036-4f09-9778-8878d320dc82 · outbound

This paper cites Rlbench: The robot learning benchmark & learning environment,.

Robotic Programmer: Video Instructed Policy Code Generation for Robotic Manipulation Rlbench: The robot learning benchmark & learning environment,

Reference 31

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source=pdf_text observed=2026-08-10T21:41:29.099256Z digest=sha256:4680babb666d704186f5c15f500a6cf14c03efb319813c570270de0ab2c32b53

Observation 77cb5c18-dc1f-46c8-a4dd-9f513e975c2c · outbound

This paper cites Libero: Benchmarking knowledge transfer for lifelong robot learning,.

Robotic Programmer: Video Instructed Policy Code Generation for Robotic Manipulation Libero: Benchmarking knowledge transfer for lifelong robot learning,

Reference 32

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verified fuzzy
raw_fallback, observed 2026-08-10T21:41:29.324865Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T21:41:29.102694Z digest=sha256:7f39886c93ed09a395495ac5408fad11efad423ed3d73d3b2c7203368aea4468

Observation 09c8ba23-f31d-4202-8cec-97d33df5802a · outbound

This paper cites DeepSeek-Coder: When the Large Language Model Meets Programming -- The Rise of Code Intelligence.

Robotic Programmer: Video Instructed Policy Code Generation for Robotic Manipulation DeepSeek-Coder: When the Large Language Model Meets Programming -- The Rise of Code Intelligence

Reference 33

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source=pdf_text observed=2026-08-10T21:41:29.106545Z digest=sha256:68e2cb7beb49f316c4e440f69d75ef5da991abd227f5e73d4035a99136986187

Observation 2b60002d-451a-4fc8-8c94-b988ec4e5314 · outbound

This paper cites V-rep: A versatile and scalable robot simulation framework,.

Robotic Programmer: Video Instructed Policy Code Generation for Robotic Manipulation V-rep: A versatile and scalable robot simulation framework,

Reference 34

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source=pdf_text observed=2026-08-10T21:41:29.109656Z digest=sha256:9c69964f4a33073e06be6ed3383c8b5e2a853c794a660266352a310b0c69f8bd

Observation 3a38a98b-3902-45d7-a273-a6dc5f20c29a · outbound

This paper cites PyRep: Bringing V-REP to Deep Robot Learning.

Robotic Programmer: Video Instructed Policy Code Generation for Robotic Manipulation PyRep: Bringing V-REP to Deep Robot Learning

Reference 35

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verified exact
local_arxiv, observed 2026-08-10T21:41:29.149865Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T21:41:29.112544Z digest=sha256:3ab48208b867a6c8de3706735ac4ea7fc4c37c459b6d47c413684000c5f8f7d1

Pith citing papers

Observation f872bd4a-802a-454b-8444-8af47739562e · inbound

Weights or Skills? A Survey of Robot-Learning Techniques: from Action-Predicting Weights to Robots that Write their Own Skills cites this paper.

Weights or Skills? A Survey of Robot-Learning Techniques: from Action-Predicting Weights to Robots that Write their Own Skills Robotic Programmer: Video Instructed Policy Code Generation for Robotic Manipulation

Reference 273

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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