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Paper Citation Record · LEDGER

CinePile: A Long Video Question Answering Dataset and Benchmark

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 33 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 33 of 33 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 33 of 33 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:50:03.465772Z

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

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=2026-05-19T11:55:30.048525Z digest=sha256:f52b566633415b63f58bd72d6905d7522f29f39c3cb6be167b7bdcebcb4f1347

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-18T04:02:43.261543Z digest=sha256:4d2434da6aaf349b3fe6468c3f73fb478d27b1194798da0bb61d617ac903713c

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-23T06:01:00.775721Z digest=sha256:a57f592cad2599617a142a7c1ebf8e72d4f22f7e08c50a73a4b80338121dd81e

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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verified exact
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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-11T01:19:59.603343Z digest=sha256:0522791ae6522060434f632612c8f665a0c43bb04b66c34ebbf83bdee61da7ca

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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unresolved
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:e6775635bdfbfe4522317307d5c78b68094cb43ff46fd0840da91c307c407d3d

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=sha256:0c8e413267293aecdb6a79ca344e813b232428a847e6db46f85fbc571df56beb

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:50:03.465772Z digest=sha256:b17fdf030fd362d3255e4b62bd0efc4906128362f70619dd70735c5df80fc78b

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-19T11:36:36.687324Z digest=sha256:a61ead4fdcba6b0ecf7be55bb6d48982c55473f18b7bd28d943f2d75a94a7164

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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no resolver link, observed 2026-08-07T06:00:56.954513Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T06:00:56.954513Z digest=sha256:8bdfc5cd5882eb0a7ee35ddb0561a3127513ad1e075f0c059ecb27f8a2b84c6a

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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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:49:53.273176Z digest=sha256:e4606086abc6e104156e97f0bc486efa79338c9a68231b6cf837703c883edbff

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:d60c5f07065c581617e1eb1bc684c920ba44483f39c6e7f52b8e25a71d265751

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:58:09.654968Z digest=sha256:11254df3ff699b2e696464af6adfcbee4f868b1b4f80109490eaef165a30b135

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=sha256:616f66b5c392d682e7d60c4de08150c24cf9f0706dedc05846f9ef9dc0b9ce58

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=sha256:27e776121f8cec2ee2924350d56256ff5b6c33c39f4c210736705d8cde5465a7

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:d6d12aca142fd1a11c6b7851bbd04a7e2cea90916a80c8e39b9e0a4503d870a4

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:29:24.253829Z digest=sha256:2307d5082ce7aa974d3db12d11f49af0cc5f9a337787ab2ca4857435f1d4c763

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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verified exact
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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-17T20:18:19.580156Z digest=sha256:55b40b5ab07fd5dd9011f32a271864f5bfb56ae052d3c68a3e2c23aca2dc3680

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-16T04:21:29.526008Z digest=sha256:d487f22d989688c730c90711e46b92963e8ad1370b24b73ca3effcf5442b0b5c

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-10T15:23:08.671342Z digest=sha256:63dec5c9d2034cf2507daa68ed6eb0304d284480db211f9219170857a9000238

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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verified exact
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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-11T01:53:01.939765Z digest=sha256:6bb8c4c1fd48cfded56af320322a810bf58c5f274fa0f2f7a756045ffc9942a4

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

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=2026-05-19T16:02:53.887605Z digest=sha256:2b626744dab568b46d2232acbc9c14138b933792f0eccb46a26ae46726d83ad0

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-06-28T19:00:54.718177Z digest=sha256:914ac35feea551604667368eae95a3986d8ea2f12697a49581374a10dacee7e0

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-06-28T10:25:06.594946Z digest=sha256:f252f50b4a66383c776bcdba777e26c98911be237e0b918af931b69c601edd18

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

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=2026-06-28T02:05:47.810096Z digest=sha256:f9df3da00d99461c5b31773fa132dbe655217910ceedca5632f2453a25d635de

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-06-27T09:48:27.652901Z digest=sha256:9b4220899a16a2d71c4ab3c3656b1034a06875183041c0c6a837465600433ff4

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-06-26T00:19:26.153682Z digest=sha256:54ecc98bb061e57b1930e16d46dad10cded65e4c62c15d8da9348a521a92e410

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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metadata mismatch
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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-06-29T04:53:25.259840Z digest=sha256:8647316a3af3a6421f14ea0ae7fc91f19bcc0709f9bb7fb9603db71b90608e11

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-07-03T15:41:03.548799Z digest=sha256:7af71230d77a7ea9a974b330f0cc4464e9e6f2d35a83c786183ae681a0ce1643

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:ce0d0012434dcfb36934d3eb999d8a4a2030fc30e5f53e6fd62c5afe2cba2670

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T16:32:51.325578Z digest=sha256:2d9f773c7fbd20fc09d5cbf3dd759022bf3819c9c9b376476ffa7c2ccc1c636e

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=sha256:87bd74572ed975b45580b1286de410aeb0005bb7cce0d9923486918adae46b80

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=sha256:158c7a61b23069c69abc1877d04632de933867bd814befa4cb0128e6dec9c219

Observation 44b4a782-ef62-4217-b57a-179974c28124 · inbound

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

Reference 74

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no resolver link, observed 2026-08-07T04:24:54.985958Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T04:24:54.985958Z digest=sha256:521047fe136d20bf20e0f632e9b3b6aadab40fb44b5944cb509e5e10ce5496f4