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Paper Citation Record · LEDGER

An Interactive Agent Foundation Model

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 10 inbound Pith citation observations for arXiv:2402.05929.

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

pith.paper-citation-record.v1
2402.05929 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 10 of 10 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 10 of 10 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T23:16:21.273453Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

4
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 3500932c-0663-4050-992d-c5b879870df1 · inbound

AI Safety Landscape for Large Language Models: Taxonomy, State-of-the-art, and Future Directions cites this paper.

AI Safety Landscape for Large Language Models: Taxonomy, State-of-the-art, and Future Directions An Interactive Agent Foundation Model

Reference 194

Resolution
verified exact
arxiv_id, observed 2026-05-23T21:55:50.470802Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-23T21:54:26.670284Z digest=sha256:35399470c67aa3b0b86b8f25723cdb66a355c7a85475658744bbfb3c1ccce132

Observation 2220016b-20fe-4789-bf27-ea7b33ffdb42 · inbound

PathFinder: A Multi-Modal Multi-Agent System for Medical Diagnostic Decision-Making Applied to Histopathology cites this paper.

PathFinder: A Multi-Modal Multi-Agent System for Medical Diagnostic Decision-Making Applied to Histopathology An Interactive Agent Foundation Model

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-07T23:16:21.273453Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T23:16:21.273453Z digest=sha256:4942092592010e5b15ff62aa9908563cd2eecd60f617419e9a3db2a7c4e921fc

Observation f81f283e-8721-44ca-9229-1d6f99bf8266 · inbound

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

Fine-Tuning Vision-Language-Action Models: Optimizing Speed and Success An Interactive Agent Foundation Model

Reference 7

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T04:35:32.356371Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-11T04:35:31.914360Z digest=sha256:0618603adc1b90639f46263ee114616f845e054422bf712d299fda52cc72fee2

Observation 17909101-3ab9-4a3e-bc05-3d069750ddba · inbound

VLAs are Confined yet Capable of Generalizing to Novel Instructions cites this paper.

VLAs are Confined yet Capable of Generalizing to Novel Instructions An Interactive Agent Foundation Model

Reference 8

Resolution
metadata mismatch
arxiv_id, observed 2026-05-22T16:46:47.414504Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-22T16:46:05.993833Z digest=sha256:c399f981b17782846bf419c6e2d98070408be5da59312bf86e6b1631370562db

Observation 30da8fda-d77f-4555-9d9e-467da9e62061 · inbound

Code with Me or for Me? How Increasing AI Automation Transforms Developer Workflows cites this paper.

Code with Me or for Me? How Increasing AI Automation Transforms Developer Workflows An Interactive Agent Foundation Model

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-06T18:34:33.406909Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:34:33.406909Z digest=sha256:3b8ac7fcd3d49eff956bb132be0b5f4a7b805ea4835f8ef83246b45ea4e1fd41

Observation 73db1c92-a3d5-4942-8f57-50df48d22062 · inbound

RoboChemist: Long-Horizon and Safety-Compliant Robotic Chemical Experimentation cites this paper.

RoboChemist: Long-Horizon and Safety-Compliant Robotic Chemical Experimentation An Interactive Agent Foundation Model

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-04T20:10:13.510982Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T20:10:13.510982Z digest=sha256:ab043939a6a2ab9a5f51a3de81d0444b6aa7fc31f17913ea53879370ecf017ee

Observation 3d1783a9-4d88-4de2-bf9d-df13bb04ecb0 · inbound

How can we assess human-agent interactions? Case studies in software agent design cites this paper.

How can we assess human-agent interactions? Case studies in software agent design An Interactive Agent Foundation Model

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-04T10:36:37.077638Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T10:36:37.077638Z digest=sha256:59fac5a29b89b89d8909ccec0ed37a956c37dbdc4332269e6fe77b5f5c28bb7b

Observation 05933f70-a364-41b3-8431-56791115103f · inbound

DyGRO-VLA: Cross-Task Scaling of Vision-Language-Action Models via Dynamic Grouped Residual Optimization cites this paper.

DyGRO-VLA: Cross-Task Scaling of Vision-Language-Action Models via Dynamic Grouped Residual Optimization An Interactive Agent Foundation Model

Reference 55

Resolution
metadata mismatch
arxiv_id, observed 2026-05-20T12:43:17.268063Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-05-20T12:39:50.004269Z digest=sha256:a07fd7163de6e498569788f50bb63e9a473b197a8a544bb505202a4e79269daa

Observation ebf130af-8a70-45d5-9810-35e8acd14b66 · inbound

Prune, Update and Trim: Robust Structured Pruning for Large Language Models cites this paper.

Prune, Update and Trim: Robust Structured Pruning for Large Language Models An Interactive Agent Foundation Model

Reference 4

Resolution
metadata mismatch
arxiv_id, observed 2026-05-20T12:03:15.006119Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-20T12:02:51.571152Z digest=sha256:224780c68e0f82d10867c38d35f14e826e3716d6ed4a5d371c79375aa5079f62

Observation 9fa20b51-cc76-496d-9da2-b0dc2cb9fa46 · inbound

Prune, Update and Trim: Robust Structured Pruning for Large Language Models cites this paper.

Prune, Update and Trim: Robust Structured Pruning for Large Language Models An Interactive Agent Foundation Model

Reference 4

Resolution
unresolved
no resolver link, observed 2026-07-14T18:53:13.849418Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-14T18:53:13.849418Z digest=sha256:69f55ac16e2dc47b22e17278b2a39df5e4120094b16ce3552e5074deb7aa1f25