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Paper Citation Record · LEDGER

Language Repository for Long Video Understanding

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 10 inbound Pith citation observations for arXiv:2403.14622.

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

pith.paper-citation-record.v1
2403.14622 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 2026-08-07T06:34:17.273281+00:00

measured 10 of 10 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T23:29:26.384824Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T10:48:03.032393Z

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 203814b7-9f3a-4acc-9ebb-9953a9e5bd9f · inbound

InternLM-XComposer-2.5: A Versatile Large Vision Language Model Supporting Long-Contextual Input and Output cites this paper.

InternLM-XComposer-2.5: A Versatile Large Vision Language Model Supporting Long-Contextual Input and Output Language Repository for Long Video Understanding

Reference 60

Resolution
verified exact
arxiv_id, observed 2026-05-17T10:46:28.569002Z

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.

source=pdf_text observed=2026-05-17T10:46:28.447347Z digest=sha256:c51f9a5b527b08c52d73894e53c954ed79f6a329eaff4932657a7d689f1d7781

Observation 0731a994-2002-4fc0-9026-e61e684b35e5 · inbound

MUPA: Towards Multi-Path Agentic Reasoning for Grounded Video Question Answering cites this paper.

MUPA: Towards Multi-Path Agentic Reasoning for Grounded Video Question Answering Language Repository for Long Video Understanding

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-06T23:29:26.384824Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:29:26.384824Z digest=sha256:41a525c40fc1fa9abaaad62570a22d321e81e733e9657f5e94469b6ca3944817

Observation 378dba24-81bd-4297-9f4f-974a00cd3418 · inbound

Temporal Chain of Thought: Long-Video Understanding by Thinking in Frames cites this paper.

Temporal Chain of Thought: Long-Video Understanding by Thinking in Frames Language Repository for Long Video Understanding

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-06T21:06:26.647384Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:06:26.647384Z digest=sha256:a77c5d4c3f2af8723b87d9156e4d57b2ea3b5b34ca338aa40b1c09d0f4a643f3

Observation c5da05aa-da0b-4824-b946-801df598799f · inbound

LeAdQA: LLM-Driven Context-Aware Temporal Grounding for Video Question Answering cites this paper.

LeAdQA: LLM-Driven Context-Aware Temporal Grounding for Video Question Answering Language Repository for Long Video Understanding

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-06T15:53:29.804755Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T15:53:29.804755Z digest=sha256:815cbfc727f847f378f32b09aba55464ff62218dcdf4998c4b9279d03df91a00

Observation 02bd78e0-fb21-4a3a-aa91-739025b936dc · inbound

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

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey Language Repository for Long Video Understanding

Reference 300

Resolution
unresolved
no resolver link, observed 2026-08-05T20:29:12.253371Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T20:29:12.253371Z digest=sha256:aadf34ee592673fb53f1539395e1788a6825c6464a299c3a137ce87ca2b60332

Observation 93e3cbc7-3329-48b7-8fe3-9b30deb89d17 · inbound

Towards Sparse Video Understanding and Reasoning cites this paper.

Towards Sparse Video Understanding and Reasoning Language Repository for Long Video Understanding

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-02T23:33:10.793495Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T23:33:10.793495Z digest=sha256:57f49560f75391cb87a0b3d4fee6a46e292d1ab24330758a39b93c35ebbf02d4

Observation fae420d3-4fca-4572-a022-1281112ef2c7 · inbound

Progressive Video Condensation with MLLM Agent for Long-form Video Understanding cites this paper.

Progressive Video Condensation with MLLM Agent for Long-form Video Understanding Language Repository for Long Video Understanding

Reference 27

Resolution
verified exact
arxiv_id, observed 2026-05-13T20:43:14.874415Z

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.

source=pdf_text observed=2026-05-13T20:40:41.380829Z digest=sha256:e4fd4309a0c4b5578a792dbb0ac40f1aa11f8b23f08da237fd39e98d0c5b5b5c

Observation 0b07c839-57e8-4a8f-ad5a-13c7299fd366 · inbound

Why Do Vision Language Models Struggle To Recognize Human Emotions? cites this paper.

Why Do Vision Language Models Struggle To Recognize Human Emotions? Language Repository for Long Video Understanding

Reference 30

Resolution
metadata mismatch
arxiv_id, observed 2026-05-10T11:05:08.711449Z

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.

source=pdf_text observed=2026-05-10T11:02:51.836285Z digest=sha256:91a5116a4a04355717fbdcde361a1c63300edbebf78bcbc8c078a3eaccd8e71f

Observation d689b70b-4670-4ce6-9430-3a91d56b3fd9 · inbound

Why Do Vision Language Models Struggle To Recognize Human Emotions? cites this paper.

Why Do Vision Language Models Struggle To Recognize Human Emotions? Language Repository for Long Video Understanding

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-02T16:11:28.626096Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T16:11:28.626096Z digest=sha256:4837a1fd00332556ac069915558bf354a91afaea99873fae3a78c2e66a2c0cbb

Observation 7dd8ee88-1ac9-4f25-8b22-94e9d820cc0c · inbound

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

InternVideo3: Agentify Foundation Models with Multimodal Contextual Reasoning Language Repository for Long Video Understanding

Reference 167

Resolution
metadata mismatch
arxiv_id, observed 2026-07-03T10:48:03.033857Z

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.

source=arxiv_source observed=2026-06-27T09:48:27.652901Z digest=sha256:931cccf45e4ec894bb132a9a19211aa83fa415c7025fec0be36595923e51ab10