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Paper Citation Record · LEDGER

AntGPT: Can Large Language Models Help Long-term Action Anticipation from Videos?

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2307.16368.

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

pith.paper-citation-record.v1
2307.16368 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 8 of 8 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 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:25:25.203281Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-24T06:44:02.323020Z

Reference resolution

0 of 0 outbound references displayed

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

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation f0d5cc08-ec18-477d-bbef-2494555b90aa · inbound

A Survey on Deep Learning Techniques for Action Anticipation cites this paper.

A Survey on Deep Learning Techniques for Action Anticipation AntGPT: Can Large Language Models Help Long-term Action Anticipation from Videos?

Reference 119

Resolution
verified exact
arxiv_id, observed 2026-05-24T06:44:02.327383Z

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=2026-05-24T06:41:15.508744Z digest=sha256:0d8d0085893cf90d1256cd317f0593be2b11927691692b9455655e1817857af1

Observation 6fdadc9b-f3b4-4b23-8600-317703d6c819 · inbound

Multimodal Chain-of-Thought Reasoning: A Comprehensive Survey cites this paper.

Multimodal Chain-of-Thought Reasoning: A Comprehensive Survey AntGPT: Can Large Language Models Help Long-term Action Anticipation from Videos?

Reference 108

Resolution
verified exact
arxiv_id, observed 2026-05-15T17:18:53.123569Z

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=2026-05-15T17:18:52.996467Z digest=sha256:612bd14724bbd2eb617924d71b22910da4cc5a5cf135eabe361d421aa881492a

Observation 66d0d2c6-928c-4748-b48b-ea4d7f0ec090 · inbound

Technical Report for Ego4D Long-Term Action Anticipation Challenge 2025 cites this paper.

Technical Report for Ego4D Long-Term Action Anticipation Challenge 2025 AntGPT: Can Large Language Models Help Long-term Action Anticipation from Videos?

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-07T11:25:25.203281Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:25:25.203281Z digest=sha256:6d9a7e5e4ba1950d2a8f6b81df71740e3cc88a9705c96f0c69982ea57b9e8c45

Observation 70571645-9ad2-4347-bea0-571aa42e7e8b · inbound

Enhancing Visual Planning with Auxiliary Tasks and Multi-token Prediction cites this paper.

Enhancing Visual Planning with Auxiliary Tasks and Multi-token Prediction AntGPT: Can Large Language Models Help Long-term Action Anticipation from Videos?

Reference 55

Resolution
unresolved
no resolver link, observed 2026-08-06T15:44:49.029086Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:44:49.029086Z digest=sha256:d98da745580b180a3f97cc0212401e696d8f9dddcdfd657d74855245a417978f

Observation 3393aec5-dd79-45f2-be85-34fc78200252 · inbound

GoViG: Goal-Conditioned Visual Navigation Instruction Generation via Multimodal Reasoning cites this paper.

GoViG: Goal-Conditioned Visual Navigation Instruction Generation via Multimodal Reasoning AntGPT: Can Large Language Models Help Long-term Action Anticipation from Videos?

Reference 28

Resolution
metadata mismatch
arxiv_id, observed 2026-05-18T23:02:52.623233Z

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=2026-05-18T23:02:14.913189Z digest=sha256:3c0052c097ea762d39494404d9ee766e5140edc20bbc7e5fc4018b2a7ddf0b6b

Observation cf9cafc5-b8b6-4910-b895-3f3e9fb4fc6d · inbound

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey cites this paper.

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey AntGPT: Can Large Language Models Help Long-term Action Anticipation from Videos?

Reference 153

Resolution
unresolved
no resolver link, observed 2026-08-05T20:28:56.974763Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T20:28:56.974763Z digest=sha256:16b974ba248beeb7aaf7ca00bc6272dd21bf80a2ac0dada37af18c4d0eb53326

Observation fcadcb62-3bcf-4ffa-ba82-33ec3fd0861e · inbound

Rethinking Video Human-Object Interaction: Set Prediction over Time for Unified Detection and Anticipation cites this paper.

Rethinking Video Human-Object Interaction: Set Prediction over Time for Unified Detection and Anticipation AntGPT: Can Large Language Models Help Long-term Action Anticipation from Videos?

Reference 55

Resolution
malformed identifier
arxiv_id, observed 2026-05-11T08:50:58.493713Z

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=2026-05-10T16:28:03.321675Z digest=sha256:b84bc9f7eec6cb6f696fbaed06596dbc8ba835caaffe4f6918633f8209e935c7

Observation 85e51dad-40a6-489e-9561-88c4bb65e5d0 · inbound

Training with (Swap) Regret Loss in a Single-Layer Self-Attention Model: A Case Study on the Probability Simplex cites this paper.

Training with (Swap) Regret Loss in a Single-Layer Self-Attention Model: A Case Study on the Probability Simplex AntGPT: Can Large Language Models Help Long-term Action Anticipation from Videos?

Reference 245

Resolution
unresolved
no resolver link, observed 2026-07-31T23:52:11.799661Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T23:52:11.799661Z digest=sha256:65942acdb81b6ea766a2f28df34bcc9aec28e1c4fdca95a4f91bfef89e5b5df2