Paper Citation Record · LEDGER

VideoLLM: Modeling Video Sequence with Large Language Models

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 27 inbound Pith citation observations for arXiv:2305.13292.

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

pith.paper-citation-record.v1
2305.13292 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 27 of 27 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 27 of 27 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:49:35.547483Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T20:18:57.839456Z

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 c541cc23-02e0-4193-9ac5-4076649b7a59 · inbound

InternVid: A Large-scale Video-Text Dataset for Multimodal Understanding and Generation cites this paper.

InternVid: A Large-scale Video-Text Dataset for Multimodal Understanding and Generation VideoLLM: Modeling Video Sequence with Large Language Models

Reference 36

Resolution: verified exact; arxiv_id, observed 2026-05-15T06:30:22.601941Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 81c23fb6-b03e-401e-be30-7c26780bc04f · inbound

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

A Survey on Deep Learning Techniques for Action Anticipation VideoLLM: Modeling Video Sequence with Large Language Models

Reference 203

Resolution: verified exact; arxiv_id, observed 2026-05-24T06:44:02.395401Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation d701eab2-8540-42d2-8903-ccc673024f4b · inbound

SALMONN: Towards Generic Hearing Abilities for Large Language Models cites this paper.

SALMONN: Towards Generic Hearing Abilities for Large Language Models VideoLLM: Modeling Video Sequence with Large Language Models

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-05-18T02:29:46.398222Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation dfe2ba98-9681-486e-9835-546287e6b040 · inbound

MathVerse: Does Your Multi-modal LLM Truly See the Diagrams in Visual Math Problems? cites this paper.

MathVerse: Does Your Multi-modal LLM Truly See the Diagrams in Visual Math Problems? VideoLLM: Modeling Video Sequence with Large Language Models

Reference 6

Resolution: metadata mismatch; arxiv_id, observed 2026-05-17T01:29:30.137998Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 8f243c46-e496-4bbc-a599-432d3c31c16a · inbound

How Far Are We to GPT-4V? Closing the Gap to Commercial Multimodal Models with Open-Source Suites cites this paper.

How Far Are We to GPT-4V? Closing the Gap to Commercial Multimodal Models with Open-Source Suites VideoLLM: Modeling Video Sequence with Large Language Models

Reference 13

Resolution: verified exact; arxiv_id, observed 2026-05-12T20:58:59.355312Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation ab5faf8c-5e75-43c2-9170-1fa85c9b3b3e · inbound

PLLaVA : Parameter-free LLaVA Extension from Images to Videos for Video Dense Captioning cites this paper.

PLLaVA : Parameter-free LLaVA Extension from Images to Videos for Video Dense Captioning VideoLLM: Modeling Video Sequence with Large Language Models

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-05-15T20:21:57.913457Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 010363d5-1c73-4422-9399-4cab4a8f1a34 · inbound

LLaVA-NeXT-Interleave: Tackling Multi-image, Video, and 3D in Large Multimodal Models cites this paper.

LLaVA-NeXT-Interleave: Tackling Multi-image, Video, and 3D in Large Multimodal Models VideoLLM: Modeling Video Sequence with Large Language Models

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-05-11T06:01:53.863823Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation d481ca96-e0bd-4cfd-809f-c21b49e89785 · inbound

Polymath: A Challenging Multi-modal Mathematical Reasoning Benchmark cites this paper.

Polymath: A Challenging Multi-modal Mathematical Reasoning Benchmark VideoLLM: Modeling Video Sequence with Large Language Models

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-05-23T20:05:47.885048Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation ea33adac-2adf-43ce-9ea8-1726e3a9c4f6 · inbound

Unraveling Spatio-Temporal Foundation Models via the Pipeline Lens: A Comprehensive Review cites this paper.

Unraveling Spatio-Temporal Foundation Models via the Pipeline Lens: A Comprehensive Review VideoLLM: Modeling Video Sequence with Large Language Models

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-07T11:49:35.547483Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 86bdf106-656d-47b7-af83-bd2fd6592189 · inbound

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

Technical Report for Ego4D Long-Term Action Anticipation Challenge 2025 VideoLLM: Modeling Video Sequence with Large Language Models

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-07T11:25:25.106038Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5e2d9d77-a5ee-42a6-8377-2f5e94b38832 · inbound

AV-Reasoner: Improving and Benchmarking Clue-Grounded Audio-Visual Counting for MLLMs cites this paper.

AV-Reasoner: Improving and Benchmarking Clue-Grounded Audio-Visual Counting for MLLMs VideoLLM: Modeling Video Sequence with Large Language Models

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-07T10:27:05.509262Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d0b2b3f3-62bc-4850-aaa8-558c9c09418e · inbound

MINT-CoT: Enabling Interleaved Visual Tokens in Mathematical Chain-of-Thought Reasoning cites this paper.

MINT-CoT: Enabling Interleaved Visual Tokens in Mathematical Chain-of-Thought Reasoning VideoLLM: Modeling Video Sequence with Large Language Models

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-07T10:28:46.876212Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0a03daa1-2d5c-431d-b20d-263c1ca55de5 · inbound

TriPSS: A Tri-Modal Keyframe Extraction Framework Using Perceptual, Structural, and Semantic Representations cites this paper.

TriPSS: A Tri-Modal Keyframe Extraction Framework Using Perceptual, Structural, and Semantic Representations VideoLLM: Modeling Video Sequence with Large Language Models

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-07T11:11:40.910714Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a83717f8-8b63-476c-98ca-bf04eebc46aa · inbound

Bridging Perspectives: A Survey on Cross-view Collaborative Intelligence with Egocentric-Exocentric Vision cites this paper.

Bridging Perspectives: A Survey on Cross-view Collaborative Intelligence with Egocentric-Exocentric Vision VideoLLM: Modeling Video Sequence with Large Language Models

Reference 215

Resolution: unresolved; no resolver link, observed 2026-08-07T06:00:58.649184Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bbb85bc4-a452-4b8e-8689-a4428efd383a · inbound

IntentVCNet: Bridging Spatio-Temporal Gaps for Intention-Oriented Controllable Video Captioning cites this paper.

IntentVCNet: Bridging Spatio-Temporal Gaps for Intention-Oriented Controllable Video Captioning VideoLLM: Modeling Video Sequence with Large Language Models

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-06T14:36:28.824818Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 73726ca9-4546-48a2-8657-49909d9a5b56 · inbound

NeuroVoxel-LM: Language-Aligned 3D Perception via Dynamic Voxelization and Meta-Embedding cites this paper.

NeuroVoxel-LM: Language-Aligned 3D Perception via Dynamic Voxelization and Meta-Embedding VideoLLM: Modeling Video Sequence with Large Language Models

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-06T13:48:01.473477Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7dfa47f3-9922-4b81-8194-46f26f8dda1d · inbound

Bidirectional Action Sequence Learning for Long-term Action Anticipation with Large Language Models cites this paper.

Bidirectional Action Sequence Learning for Long-term Action Anticipation with Large Language Models VideoLLM: Modeling Video Sequence with Large Language Models

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-06T10:13:21.401166Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 367ec431-a646-46d0-a3c7-c31da349848e · inbound

Training-Free Multimodal Large Language Model Orchestration cites this paper.

Training-Free Multimodal Large Language Model Orchestration VideoLLM: Modeling Video Sequence with Large Language Models

Reference 27

Resolution: verified exact; arxiv_id, observed 2026-05-19T00:12:54.074518Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 25faba18-f547-4682-8c3b-082d20a552dd · inbound

Training-Free Multimodal Large Language Model Orchestration cites this paper.

Training-Free Multimodal Large Language Model Orchestration VideoLLM: Modeling Video Sequence with Large Language Models

Reference 27

Resolution: verified exact; arxiv_id, observed 2026-05-25T08:05:30.762307Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation a96d9ce7-a49e-49c9-a47c-9a59b83bc134 · inbound

Time-Scaling State-Space Models for Dense Video Captioning cites this paper.

Time-Scaling State-Space Models for Dense Video Captioning VideoLLM: Modeling Video Sequence with Large Language Models

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-05T10:59:05.132385Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 505e4779-9191-4b37-96e9-7e41a182180c · inbound

Multimodal Large Language Model-Enabled Video Translation: A Role-Oriented Survey cites this paper.

Multimodal Large Language Model-Enabled Video Translation: A Role-Oriented Survey VideoLLM: Modeling Video Sequence with Large Language Models

Reference 33

Resolution: verified exact; arxiv_id, observed 2026-05-11T08:30:57.075105Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation ca07bbee-5094-45c2-b6bd-53e77596f81a · inbound

Scaling Video Understanding via Compact Latent Multi-Agent Collaboration cites this paper.

Scaling Video Understanding via Compact Latent Multi-Agent Collaboration VideoLLM: Modeling Video Sequence with Large Language Models

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-05-11T15:21:09.457612Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 86af773a-8a1e-4a66-8a69-88ca542db661 · inbound

Reasoning-Guided Grounding: Elevating Video Anomaly Detection through Multimodal Large Language Models cites this paper.

Reasoning-Guided Grounding: Elevating Video Anomaly Detection through Multimodal Large Language Models VideoLLM: Modeling Video Sequence with Large Language Models

Reference 44

Resolution: metadata mismatch; arxiv_id, observed 2026-05-10T23:30:51.938785Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation df02794c-9aaf-4d32-856d-c0aa80f3e09f · inbound

An Attribute-Based Measure of Video Complexity cites this paper.

An Attribute-Based Measure of Video Complexity VideoLLM: Modeling Video Sequence with Large Language Models

Reference 7

Resolution: metadata mismatch; arxiv_id, observed 2026-06-28T19:02:34.097031Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation ec893098-6043-4d53-9a47-88dc7f1c0ffb · inbound

InternVideo3: Agentify Foundation Models with Multimodal Contextual Reasoning cites this paper.

InternVideo3: Agentify Foundation Models with Multimodal Contextual Reasoning VideoLLM: Modeling Video Sequence with Large Language Models

Reference 149

Resolution: metadata mismatch; arxiv_id, observed 2026-07-03T10:48:03.063320Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation a924f3ed-4503-416d-899e-a1de50b91659 · inbound

MathVis-Fine: Aligning Visual Supervision with Necessity via Progressive Dependency-Guided Training for Multimodal Mathematical Reasoning cites this paper.

MathVis-Fine: Aligning Visual Supervision with Necessity via Progressive Dependency-Guided Training for Multimodal Mathematical Reasoning VideoLLM: Modeling Video Sequence with Large Language Models

Reference 93

Resolution: metadata mismatch; arxiv_id, observed 2026-07-03T20:18:57.842377Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 204689fb-d777-4c79-b01f-1969c1657c9f · inbound

GMoT: Gated Motion-Aware Tokenization for Fine-Grained Micro-Gesture Video Reasoning with Multimodal LLMs cites this paper.

GMoT: Gated Motion-Aware Tokenization for Fine-Grained Micro-Gesture Video Reasoning with Multimodal LLMs VideoLLM: Modeling Video Sequence with Large Language Models

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-02T04:39:20.337796Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.