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Paper Citation Record · LEDGER

CinePile: A Long Video Question Answering Dataset and Benchmark

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 35 inbound Pith citation observations for arXiv:2405.08813.

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

pith.paper-citation-record.v1
2405.08813 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 35 of 35 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 35 of 35 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T22:47:39.286819Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T16:39:58.360487Z

Reference resolution

0 of 0 outbound references displayed

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External citation measurements

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Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 43df5068-94b9-4c18-8e5f-65237f2ace4d · inbound

LVBench: An Extreme Long Video Understanding Benchmark cites this paper.

LVBench: An Extreme Long Video Understanding Benchmark CinePile: A Long Video Question Answering Dataset and Benchmark

Reference 31

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arxiv_id, observed 2026-05-19T11:55:30.092244Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-19T11:55:30.048525Z digest=sha256:d97e369628ee2804cce1d11ddf2d3552550a1a7df54392f993741d78d46dc4e0

Observation f9b9e478-9dbf-4b84-83e1-faebb67969f9 · inbound

VideoChat-Flash: Hierarchical Compression for Long-Context Video Modeling cites this paper.

VideoChat-Flash: Hierarchical Compression for Long-Context Video Modeling CinePile: A Long Video Question Answering Dataset and Benchmark

Reference 43

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arxiv_id, observed 2026-05-18T04:02:43.474946Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-18T04:02:43.261543Z digest=sha256:cdb2228829fa649c2e6d158474db441d8d8b789a0a0afd08b2dd74da5c46464e

Observation 5dabb5b7-c2a8-4ec9-8511-aa8ed3599b17 · inbound

LLaVA-Octopus: Unlocking Instruction-Driven Adaptive Projector Fusion for Video Understanding cites this paper.

LLaVA-Octopus: Unlocking Instruction-Driven Adaptive Projector Fusion for Video Understanding CinePile: A Long Video Question Answering Dataset and Benchmark

Reference 58

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arxiv_id, observed 2026-05-23T06:02:37.664985Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-23T06:01:00.775721Z digest=sha256:41dc0bc0eac6cf96bd3e6df62968cff76e1d85c563a9d0725a4e2bd614f3cd0a

Observation ef357ce6-3b40-45fc-a870-f1986d9cc78c · inbound

VideoLLaMA 3: Frontier Multimodal Foundation Models for Image and Video Understanding cites this paper.

VideoLLaMA 3: Frontier Multimodal Foundation Models for Image and Video Understanding CinePile: A Long Video Question Answering Dataset and Benchmark

Reference 99

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arxiv_id, observed 2026-05-11T01:19:59.716306Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-11T01:19:59.603343Z digest=sha256:cf720951916b61b225496de1c7000d67a58ebb2d3ba2633d31a9b96eb2fe1df4

Observation ba1cb269-c287-4983-b8a5-afd2497a9b36 · inbound

Ola: Pushing the Frontiers of Omni-Modal Language Model cites this paper.

Ola: Pushing the Frontiers of Omni-Modal Language Model CinePile: A Long Video Question Answering Dataset and Benchmark

Reference 57

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no resolver link, observed 2026-08-08T22:47:39.286819Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T22:47:39.286819Z digest=sha256:049782a1d0927e39ee1165345d6fb19d3f970b10966a03ed04cc57bf3ffe88c5

Observation b2beb961-e52e-4d7a-b0c9-53ffdea1b977 · inbound

ScaleLong: A Multi-Timescale Benchmark for Long Video Understanding cites this paper.

ScaleLong: A Multi-Timescale Benchmark for Long Video Understanding CinePile: A Long Video Question Answering Dataset and Benchmark

Reference 21

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no resolver link, observed 2026-08-07T12:40:45.721408Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:40:45.721408Z digest=sha256:5c00f30be14c666d0275503ed1d211091424d5d6514af072b54c3360baeac2f8

Observation e84b1fe9-e717-4a68-9c0a-7c2ab8456258 · inbound

ReFoCUS: Reinforcement-guided Frame Optimization for Contextual Understanding cites this paper.

ReFoCUS: Reinforcement-guided Frame Optimization for Contextual Understanding CinePile: A Long Video Question Answering Dataset and Benchmark

Reference 39

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no resolver link, observed 2026-08-07T11:51:28.722460Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:51:28.722460Z digest=sha256:0d7d126be8824dff8d689fe6d08bc3badaf63db525efe6c4a59e3e39418886ee

Observation b5a9eed2-063f-4369-83c6-f8cdb5c0e94f · inbound

Vid-SME: Membership Inference Attacks against Large Video Understanding Models cites this paper.

Vid-SME: Membership Inference Attacks against Large Video Understanding Models CinePile: A Long Video Question Answering Dataset and Benchmark

Reference 37

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no resolver link, observed 2026-08-07T12:50:03.465772Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:50:03.465772Z digest=sha256:68276437eca97c53098201ad03cd42507f0ce74b9754c80b2cb35baa299e243a

Observation f00b55dd-fc36-4de5-9f00-9b8018792999 · inbound

SIV-Bench: A Video Benchmark for Social Interaction Understanding and Reasoning cites this paper.

SIV-Bench: A Video Benchmark for Social Interaction Understanding and Reasoning CinePile: A Long Video Question Answering Dataset and Benchmark

Reference 40

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arxiv_id, observed 2026-05-19T11:37:15.669903Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-19T11:36:36.687324Z digest=sha256:5f71c874f5c984c299a844e3a44c6b2be510204b983e6f6cb3ed316050339561

Observation 13e2c0fb-30ac-409e-9f52-7726c30ad6ae · inbound

Movie Facts and Fibs (MF$^2$): A Benchmark for Long Movie Understanding cites this paper.

Movie Facts and Fibs (MF$^2$): A Benchmark for Long Movie Understanding CinePile: A Long Video Question Answering Dataset and Benchmark

Reference 44

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source=pdf_text observed=2026-08-07T06:00:56.954513Z digest=sha256:1fad19cb35315ea2ceddedc6c687203534f8bb85cfb758c3f060bb00fb2d4e25

Observation a55a95d4-5a08-4bdb-a540-3c8398416327 · inbound

MAGNET: A Multi-agent Framework for Finding Audio-Visual Needles by Reasoning over Multi-Video Haystacks cites this paper.

MAGNET: A Multi-agent Framework for Finding Audio-Visual Needles by Reasoning over Multi-Video Haystacks CinePile: A Long Video Question Answering Dataset and Benchmark

Reference 13

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no resolver link, observed 2026-08-07T05:49:53.273176Z

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source=pdf_text observed=2026-08-07T05:49:53.273176Z digest=sha256:80ab0dc55aefae8223c6a5534dee5248841429a38ef1b52fb5b65d57494dfdaf

Observation c327895c-27f6-407b-a9e4-89b92372a249 · inbound

ARGUS: Hallucination and Omission Evaluation in Video-LLMs cites this paper.

ARGUS: Hallucination and Omission Evaluation in Video-LLMs CinePile: A Long Video Question Answering Dataset and Benchmark

Reference 48

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no resolver link, observed 2026-08-07T05:41:39.746918Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:41:39.746918Z digest=sha256:2ed8317c641ba7b6d3a2f16f255eff2e474b7e977e2521a06a3912c02f953cd5

Observation bf3a7020-ca82-45ec-a2de-6bcdbce815e5 · inbound

Ming-Omni: A Unified Multimodal Model for Perception and Generation cites this paper.

Ming-Omni: A Unified Multimodal Model for Perception and Generation CinePile: A Long Video Question Answering Dataset and Benchmark

Reference 28

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no resolver link, observed 2026-08-07T04:58:09.654968Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:58:09.654968Z digest=sha256:5ec06768dc1acea87db7b7d009527d7bb0f11b2d85391b735677ef883c79e969

Observation e967bfc9-8471-4deb-8a98-736eb0df26c4 · inbound

CausalVQA: A Physically Grounded Causal Reasoning Benchmark for Video Models cites this paper.

CausalVQA: A Physically Grounded Causal Reasoning Benchmark for Video Models CinePile: A Long Video Question Answering Dataset and Benchmark

Reference 32

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no resolver link, observed 2026-08-07T04:45:01.238009Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:45:01.238009Z digest=sha256:19c0ba815c9ddfa57cdb4994138e1f81140aa45b2e7eeef21e023e037b61df2f

Observation 2bce9224-a4cb-41a3-853a-88f33fd1a58b · inbound

VRBench: A Benchmark for Multi-Step Reasoning in Long Narrative Videos cites this paper.

VRBench: A Benchmark for Multi-Step Reasoning in Long Narrative Videos CinePile: A Long Video Question Answering Dataset and Benchmark

Reference 53

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no resolver link, observed 2026-08-07T04:22:55.969084Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:22:55.969084Z digest=sha256:1e4f49f324bc42b03fab972a57b04b5962946ed2f9535805360a006935c64c94

Observation b7754035-5226-457d-a5d6-8fd86eda5e15 · inbound

LaVi: Efficient Large Vision-Language Models via Internal Feature Modulation cites this paper.

LaVi: Efficient Large Vision-Language Models via Internal Feature Modulation CinePile: A Long Video Question Answering Dataset and Benchmark

Reference 52

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no resolver link, observed 2026-08-06T23:42:13.831606Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:42:13.831606Z digest=sha256:2a9ee20a2827faa10b0ed291f03f8617e8597fd4afe5958795acaf80d1463536

Observation 69c68b6f-8159-423e-891e-37fa0df608fe · 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 CinePile: A Long Video Question Answering Dataset and Benchmark

Reference 23

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no resolver link, observed 2026-08-06T23:29:24.253829Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:29:24.253829Z digest=sha256:e64244f7738537579d8ea314261462e4e5f1c687d2bad3f8c295989c78bf5666

Observation 5874399a-af36-4487-a27e-be0706e94262 · inbound

AVATAAR: Agentic Video Answering via Temporal Adaptive Alignment and Reasoning cites this paper.

AVATAAR: Agentic Video Answering via Temporal Adaptive Alignment and Reasoning CinePile: A Long Video Question Answering Dataset and Benchmark

Reference 5

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arxiv_id, observed 2026-05-17T20:20:11.806042Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-17T20:18:19.580156Z digest=sha256:5e5fdc3e390fccd400d0ddfa1ef2cdca43b57bacc68ee11d09678dd3f0fadea5

Observation 7a6d0514-8517-4d50-b4ce-a376a0e6a49a · inbound

Molmo2: Open Weights and Data for Vision-Language Models with Video Understanding and Grounding cites this paper.

Molmo2: Open Weights and Data for Vision-Language Models with Video Understanding and Grounding CinePile: A Long Video Question Answering Dataset and Benchmark

Reference 123

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arxiv_id, observed 2026-05-16T04:21:29.765977Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-16T04:21:29.526008Z digest=sha256:391c58a230e788e5944b371966270beaf27672e6004e839f9c5ce75e87b12ae3

Observation b71dd5a6-0085-4564-9835-e73ec935a775 · inbound

POINTS-Long: Adaptive Dual-Mode Visual Reasoning in MLLMs cites this paper.

POINTS-Long: Adaptive Dual-Mode Visual Reasoning in MLLMs CinePile: A Long Video Question Answering Dataset and Benchmark

Reference 66

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arxiv_id, observed 2026-05-11T10:41:03.971483Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-10T15:23:08.671342Z digest=sha256:62120abcf6887d27c4ec20ddaed0b97a0427c6cbc5a34c3b59919d5418aa9ded

Observation 0d59c559-8d60-46a4-a31e-61588e821c5d · inbound

TraceAV-Bench: Benchmarking Multi-Hop Trajectory Reasoning over Long Audio-Visual Videos cites this paper.

TraceAV-Bench: Benchmarking Multi-Hop Trajectory Reasoning over Long Audio-Visual Videos CinePile: A Long Video Question Answering Dataset and Benchmark

Reference 73

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arxiv_id, observed 2026-05-11T04:15:56.091351Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-11T01:53:01.939765Z digest=sha256:83b9a1c3d4319dbcd2861e8445e65879ba6746df94a95c1a3d1839804c70efbe

Observation c756b4a3-52a9-4442-9fb9-d230b541a974 · inbound

Minerva-Ego: Spatiotemporal Hints for Egocentric Video Understanding cites this paper.

Minerva-Ego: Spatiotemporal Hints for Egocentric Video Understanding CinePile: A Long Video Question Answering Dataset and Benchmark

Reference 37

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arxiv_id, observed 2026-05-19T16:03:08.077787Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-19T16:02:53.887605Z digest=sha256:45ea13c30ae90f26c0cc1615c6607124f57b9995e8bea4e340489e0e601f88df

Observation 8b2b92ad-b280-454c-816d-b0984260e524 · inbound

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

An Attribute-Based Measure of Video Complexity CinePile: A Long Video Question Answering Dataset and Benchmark

Reference 41

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arxiv_id, observed 2026-06-28T19:02:34.112901Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-28T19:00:54.718177Z digest=sha256:471383759113cb238f3223993e792aeef4d62322dcfc687d27be5ea52c4d19e7

Observation d5ef4b2a-3c61-4236-8094-edfdcae0ee85 · inbound

VidMsg: A Benchmark for Implicit Message Inference in Short Videos cites this paper.

VidMsg: A Benchmark for Implicit Message Inference in Short Videos CinePile: A Long Video Question Answering Dataset and Benchmark

Reference 32

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arxiv_id, observed 2026-07-02T02:56:30.072053Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-28T10:25:06.594946Z digest=sha256:5a29a7ca9b9835905490f1df8f02168f56c2d66b1e6b8fb9877db266b1c9b333

Observation de21a677-beb4-497e-9fec-9d79c92fbe3d · inbound

StoryVideoQA: Scaling Deep Video Understanding with a Large-Scale, Multi-Genre and Auto-Generated Dataset cites this paper.

StoryVideoQA: Scaling Deep Video Understanding with a Large-Scale, Multi-Genre and Auto-Generated Dataset CinePile: A Long Video Question Answering Dataset and Benchmark

Reference 25

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arxiv_id, observed 2026-07-02T12:36:56.175154Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-28T02:05:47.810096Z digest=sha256:5b228213285bf599fba35a1de89b2e55cbdc43aa21befec4147a159e03d19972

Observation ea758d1e-6bc5-4a94-be91-d8e6a4490dcd · inbound

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

InternVideo3: Agentify Foundation Models with Multimodal Contextual Reasoning CinePile: A Long Video Question Answering Dataset and Benchmark

Reference 298

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arxiv_id, observed 2026-07-03T10:48:03.100934Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-06-27T09:48:27.652901Z digest=sha256:d352ffe2a3ec6319110f3319b2dff4c62db8746ff6788ca55f55e0c0992c00ab

Observation 26eb1072-5e44-415f-8087-f415ad638a38 · inbound

video-SALMONN-R$^3$: Learning to ReWatch, ReAsk, and ReAnswer for Efficient Video Understanding cites this paper.

video-SALMONN-R$^3$: Learning to ReWatch, ReAsk, and ReAnswer for Efficient Video Understanding CinePile: A Long Video Question Answering Dataset and Benchmark

Reference 48

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arxiv_id, observed 2026-07-04T16:39:58.362180Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-26T00:19:26.153682Z digest=sha256:d8c546ba1d3926e2a843eb628cd63db863bf2482de6e387642b833efb27c189b

Observation ea3ab46a-aa52-49e5-a6e4-b087c3833377 · inbound

Video-MME-Logical: A Controlled Diagnostic Benchmark for Video Temporal-Logical Reasoning cites this paper.

Video-MME-Logical: A Controlled Diagnostic Benchmark for Video Temporal-Logical Reasoning CinePile: A Long Video Question Answering Dataset and Benchmark

Reference 14

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arxiv_id, observed 2026-06-29T19:13:52.928268Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-06-29T04:53:25.259840Z digest=sha256:786ef0e66bd987a8d4cbe87f7764db881c8f71ce5a6b94d5be95f5ef33f446d5

Observation bcf308be-2c98-45ea-9815-632c2360ed4f · inbound

LongEgoRefer: A Benchmark for Long-Form Egocentric Video Referring Expression Comprehension cites this paper.

LongEgoRefer: A Benchmark for Long-Form Egocentric Video Referring Expression Comprehension CinePile: A Long Video Question Answering Dataset and Benchmark

Reference 37

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arxiv_id, observed 2026-07-03T15:48:35.009088Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-07-03T15:41:03.548799Z digest=sha256:be197f8dfb9ab007be2f02dd76b803cc6feb7761be5c6c66c47d6db2ca05742f

Observation 63fe83c7-4305-4236-8c2d-31689e10f41c · inbound

VideoChat3: Fully Open Video MLLM for Efficient and Generalist Video Understanding cites this paper.

VideoChat3: Fully Open Video MLLM for Efficient and Generalist Video Understanding CinePile: A Long Video Question Answering Dataset and Benchmark

Reference 51

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no resolver link, observed 2026-08-02T00:44:45.027159Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T00:44:45.027159Z digest=sha256:ad1fb9696de87510f7216e4a72e377b9025f02546593497ef4dad4bb8d50fa67

Observation ad1eaa7f-5f72-46f1-90ab-976ec2efaa86 · inbound

RynnBrain 1.1: Towards More Capable and Generalizable Embodied Foundation Model cites this paper.

RynnBrain 1.1: Towards More Capable and Generalizable Embodied Foundation Model CinePile: A Long Video Question Answering Dataset and Benchmark

Reference 56

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no resolver link, observed 2026-08-01T16:32:51.325578Z

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source=pdf_text observed=2026-08-01T16:32:51.325578Z digest=sha256:f20c90a35497b44165bdfab2eca873d4b03a062cfb156966e449baba94ca10d5

Observation a3e89658-a477-4b0e-8a6a-13ebfc5b7c3a · inbound

RynnBrain 1.1: Towards More Capable and Generalizable Embodied Foundation Model cites this paper.

RynnBrain 1.1: Towards More Capable and Generalizable Embodied Foundation Model CinePile: A Long Video Question Answering Dataset and Benchmark

Reference 56

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no resolver link, observed 2026-08-03T01:57:33.221572Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T01:57:33.221572Z digest=sha256:25a5b1eb923d6fa026c08dc8902341d8d51f56aab81a7f57940db9b96c6ed92d

Observation 9b02b645-9ae3-4301-bf5b-badd6dea3b76 · inbound

Reading Between the Frames: Interpreting Implicit and Non-literal Meaning in Social Media Videos cites this paper.

Reading Between the Frames: Interpreting Implicit and Non-literal Meaning in Social Media Videos CinePile: A Long Video Question Answering Dataset and Benchmark

Reference 37

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no resolver link, observed 2026-08-06T13:26:49.688571Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T13:26:49.688571Z digest=sha256:6aaade20744cbabfd782fc608f9a33be7807cdccb86e47a2f7b8613060428c2e

Observation 076c26d2-d334-4f85-ace0-5774c15b4a2e · inbound

Evidence-Driven Dynamic Visual Selector for Efficient Long Video Understanding cites this paper.

Evidence-Driven Dynamic Visual Selector for Efficient Long Video Understanding CinePile: A Long Video Question Answering Dataset and Benchmark

Reference 15

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no resolver link, observed 2026-08-07T23:42:35.029043Z

Source-reported events for the cited work

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The Low Frequency Trap: Video Language Models Fail at Simple Event Bookkeeping cites this paper.

The Low Frequency Trap: Video Language Models Fail at Simple Event Bookkeeping CinePile: A Long Video Question Answering Dataset and Benchmark

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