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Paper Citation Record · LEDGER

TUNA: Comprehensive Fine-grained Temporal Understanding Evaluation on Dense Dynamic Videos

As of 9 August 2026, this Paper Citation Record lists 71 of 71 outbound references and 2 inbound Pith citation observations for arXiv:2505.20124.

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

pith.paper-citation-record.v1
2505.20124 v2

Coverage vector

measured 71 of 71 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:03:06.244486Z

measured 73 of 73 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 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:14:40.649758Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T13:46:04.353404Z

Reference resolution

71 of 71 outbound references displayed

  • verified exact2
  • verified fuzzy0
  • unresolved69
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation a2e78cdb-1c50-4de0-aa61-8865a41e9cfc · outbound

This paper cites Understanding Alignment in Multimodal LLMs: A Comprehensive Study.

TUNA: Comprehensive Fine-grained Temporal Understanding Evaluation on Dense Dynamic Videos Understanding Alignment in Multimodal LLMs: A Comprehensive Study

Reference 1

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no resolver link, observed 2026-08-07T14:02:59.199626Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:02:59.199626Z digest=sha256:10108eef1377ec33fb4d1ea7980feaffef9ba7ea1ad93c2529805d5f1bb1004b

Observation 41705b25-296a-4005-860d-dce17fb10c5c · outbound

This paper cites an unresolved cited work.

TUNA: Comprehensive Fine-grained Temporal Understanding Evaluation on Dense Dynamic Videos Unresolved cited work

Reference 2

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no resolver link, observed 2026-08-07T14:02:59.246252Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:02:59.246252Z digest=sha256:29300c711efc3301e0c9b6e1b89f4ccdaaafb40d64ce315d7264176fb1b46d8b

Observation f397b61a-8a5f-4a43-ae33-1993211da792 · outbound

This paper cites an unresolved cited work.

TUNA: Comprehensive Fine-grained Temporal Understanding Evaluation on Dense Dynamic Videos Unresolved cited work

Reference 3

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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=2026-08-07T14:02:59.294091Z digest=sha256:3889132554b53137d93234b92838c5a810c3c89aaa5ba986a4be96527530a265

Observation df306f69-2a36-4e3e-8c23-a42c8f1ee57e · outbound

This paper cites an unresolved cited work.

TUNA: Comprehensive Fine-grained Temporal Understanding Evaluation on Dense Dynamic Videos Unresolved cited work

Reference 4

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no resolver link, observed 2026-08-07T14:02:59.442683Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:02:59.442683Z digest=sha256:6b67af9524968489b13f2e7ba9ad08eb05667cfb46297d0f82a0928589ac2b98

Observation 80e16319-d3dc-4d02-8a36-8145025e4d50 · outbound

This paper cites an unresolved cited work.

TUNA: Comprehensive Fine-grained Temporal Understanding Evaluation on Dense Dynamic Videos Unresolved cited work

Reference 5

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unresolved
no resolver link, observed 2026-08-07T14:02:59.520698Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:02:59.520698Z digest=sha256:70384d48902eb6316f153d3475a53bc9c432cea05112271329bb0b8ca73224d1

Observation 0068b704-aecd-46cc-a8c5-175b3944aa05 · outbound

This paper cites TemporalBench: Benchmarking Fine-grained Temporal Understanding for Multimodal Video Models.

TUNA: Comprehensive Fine-grained Temporal Understanding Evaluation on Dense Dynamic Videos TemporalBench: Benchmarking Fine-grained Temporal Understanding for Multimodal Video Models

Reference 6

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no resolver link, observed 2026-08-07T14:02:59.572640Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:02:59.572640Z digest=sha256:fa44fd29234465395b697282cba8f8370ae25ead867150f496f06154c7619f48

Observation 286408a4-2bf5-439d-b8c2-c1f170a644df · outbound

This paper cites AuroraCap: Efficient, Performant Video Detailed Captioning and a New Benchmark.

TUNA: Comprehensive Fine-grained Temporal Understanding Evaluation on Dense Dynamic Videos AuroraCap: Efficient, Performant Video Detailed Captioning and a New Benchmark

Reference 7

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no resolver link, observed 2026-08-07T14:02:59.661583Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:02:59.661583Z digest=sha256:f021fcbbd7668ed721e0fa5b5cafa8034cb526dbd2a164704a19b40512150a96

Observation a3aa7095-d028-4925-91ae-e2e3f847ba48 · outbound

This paper cites an unresolved cited work.

TUNA: Comprehensive Fine-grained Temporal Understanding Evaluation on Dense Dynamic Videos Unresolved cited work

Reference 8

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no resolver link, observed 2026-08-07T14:02:59.743322Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:02:59.743322Z digest=sha256:a37787e08b89e372e88b4b8e1de63505ef9c850a1637233f263e82d7e86a17db

Observation b07fa147-f2c7-48ef-9f80-c9173bc1072a · outbound

This paper cites ShareGPT4Video: Improving Video Understanding and Generation with Better Captions.

TUNA: Comprehensive Fine-grained Temporal Understanding Evaluation on Dense Dynamic Videos ShareGPT4Video: Improving Video Understanding and Generation with Better Captions

Reference 9

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no resolver link, observed 2026-08-07T14:02:59.821440Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:02:59.821440Z digest=sha256:d4a340ae112e656c29768140d5bf9b43a15c476bc88a63d6be96b4f433350eea

Observation da4f4b77-7c28-4072-a886-c665760fd6c7 · outbound

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

TUNA: Comprehensive Fine-grained Temporal Understanding Evaluation on Dense Dynamic Videos How Far Are We to GPT-4V? Closing the Gap to Commercial Multimodal Models with Open-Source Suites

Reference 10

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:02:59.956644Z digest=sha256:702977d1db69f936ada3cb9f314eb8eeaeff59ace5e165d44d0a83ab9f862bc6

Observation 4626b8e1-9e19-4dcb-8b8b-52c89701e126 · outbound

This paper cites VideoLLaMA 2: Advancing Spatial-Temporal Modeling and Audio Understanding in Video-LLMs.

TUNA: Comprehensive Fine-grained Temporal Understanding Evaluation on Dense Dynamic Videos VideoLLaMA 2: Advancing Spatial-Temporal Modeling and Audio Understanding in Video-LLMs

Reference 11

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no resolver link, observed 2026-08-07T14:03:00.079127Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:03:00.079127Z digest=sha256:720144f948608fc2117ff4a755e8002b00a529e52f18121fce97da5997df2dfc

Observation b4861b3d-5a97-4ec7-9860-a77518a71238 · outbound

This paper cites an unresolved cited work.

TUNA: Comprehensive Fine-grained Temporal Understanding Evaluation on Dense Dynamic Videos Unresolved cited work

Reference 12

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no resolver link, observed 2026-08-07T14:03:00.159794Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:03:00.159794Z digest=sha256:fe92777b01b4621ceb8231f0e374d4dade34e40420129de04217dc463f8f1116

Observation 0efa1912-aefd-4af8-9142-d311875dbf8b · outbound

This paper cites an unresolved cited work.

TUNA: Comprehensive Fine-grained Temporal Understanding Evaluation on Dense Dynamic Videos Unresolved cited work

Reference 13

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unresolved
no resolver link, observed 2026-08-07T14:03:00.270242Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:03:00.270242Z digest=sha256:043df56ee8a4159883653afd68a1ccae007165e7ef8c4e9b8671a3cf36c76585

Observation a19f9c5e-082f-42f2-8df3-e98e009b5aea · outbound

This paper cites Video-MME: The First-Ever Comprehensive Evaluation Benchmark of Multi-modal LLMs in Video Analysis.

TUNA: Comprehensive Fine-grained Temporal Understanding Evaluation on Dense Dynamic Videos Video-MME: The First-Ever Comprehensive Evaluation Benchmark of Multi-modal LLMs in Video Analysis

Reference 14

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no resolver link, observed 2026-08-07T14:03:00.394498Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:03:00.394498Z digest=sha256:b59400d39e7d6e74e96c0304f165cf51686cd6d6f7d12ca77dd17a1da5fad152

Observation 81cb9156-82e7-46a4-b478-d22e37d2b0f9 · outbound

This paper cites MiraData: A Large-Scale Video Dataset with Long Durations and Structured Captions.

TUNA: Comprehensive Fine-grained Temporal Understanding Evaluation on Dense Dynamic Videos MiraData: A Large-Scale Video Dataset with Long Durations and Structured Captions

Reference 15

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no resolver link, observed 2026-08-07T14:03:00.523964Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:03:00.523964Z digest=sha256:5b69a0c49267aeaee09f5c2f70a41aadf7e038b3306b30eaf9d1213332f04ee0

Observation ee1ebd9e-a9c9-45ae-ae6a-38cd48861805 · outbound

This paper cites Modality Curation: Building Universal Embeddings for Advanced Multimodal Information Retrieval.

TUNA: Comprehensive Fine-grained Temporal Understanding Evaluation on Dense Dynamic Videos Modality Curation: Building Universal Embeddings for Advanced Multimodal Information Retrieval

Reference 16

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unresolved
no resolver link, observed 2026-08-07T14:03:00.563577Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:03:00.563577Z digest=sha256:2eeb2e82fd4051e1067031c3aa1f9d2aab66d6f591353df9836e52046cd26693

Observation 88da6a61-1098-458e-aae6-1b954ffffd3a · outbound

This paper cites LLaVA-OneVision: Easy Visual Task Transfer.

TUNA: Comprehensive Fine-grained Temporal Understanding Evaluation on Dense Dynamic Videos LLaVA-OneVision: Easy Visual Task Transfer

Reference 17

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no resolver link, observed 2026-08-07T14:03:00.612315Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:03:00.612315Z digest=sha256:6bfa703335ee7d42418dbcbb9efb88655b0aabae25b6b2767a26951c14ca09ac

Observation 7a3edf5a-335a-46e3-8640-4596701da0cc · outbound

This paper cites an unresolved cited work.

TUNA: Comprehensive Fine-grained Temporal Understanding Evaluation on Dense Dynamic Videos Unresolved cited work

Reference 18

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raw_fallback, observed 2026-08-07T14:03:08.868288Z

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=2026-08-07T14:03:00.700267Z digest=sha256:38a9e5f8fc5db0cd416a535749c25ea3a216d1707677c09d17d232ce06377648

Observation 2c500152-2066-4fa1-bda7-fbb376034dcc · outbound

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

TUNA: Comprehensive Fine-grained Temporal Understanding Evaluation on Dense Dynamic Videos LLaVA-NeXT-Interleave: Tackling Multi-image, Video, and 3D in Large Multimodal Models

Reference 19

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no resolver link, observed 2026-08-07T14:03:00.801599Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:03:00.801599Z digest=sha256:4970e80cd48a419925e6146770c262f3d141ca43cfcfac9f910deeb062bbbd13

Observation 2f28c05f-7e0f-4e68-a8ed-f7965d2fda89 · outbound

This paper cites an unresolved cited work.

TUNA: Comprehensive Fine-grained Temporal Understanding Evaluation on Dense Dynamic Videos Unresolved cited work

Reference 20

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no resolver link, observed 2026-08-07T14:03:00.902430Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:03:00.902430Z digest=sha256:7a168959c29db0689d89d8b5a89ec084551a907e229cf11899dc66dcbf6ae61a

Observation f9f4d8f5-6009-45e4-a19e-944027a23dcf · outbound

This paper cites an unresolved cited work.

TUNA: Comprehensive Fine-grained Temporal Understanding Evaluation on Dense Dynamic Videos Unresolved cited work

Reference 21

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unresolved
raw_fallback, observed 2026-08-07T14:03:08.753423Z

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=2026-08-07T14:03:01.002391Z digest=sha256:a606a2a67f91f4ba2c598fd3b30750d4798a82c4b6930542384d4b118f5c6630

Observation fc66876d-c16b-4d4b-977f-7b397612597f · outbound

This paper cites VideoVista: A Versatile Benchmark for Video Understanding and Reasoning.

TUNA: Comprehensive Fine-grained Temporal Understanding Evaluation on Dense Dynamic Videos VideoVista: A Versatile Benchmark for Video Understanding and Reasoning

Reference 22

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no resolver link, observed 2026-08-07T14:03:01.131871Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:03:01.131871Z digest=sha256:320e75f97a4e31bb9be3a0ab2798d9ec61df8c29630d2237ae44e38ea688343c

Observation ef150987-a2c5-45e0-a3d5-702b85fe7a7c · outbound

This paper cites Video-LLaVA: Learning United Visual Representation by Alignment Before Projection.

TUNA: Comprehensive Fine-grained Temporal Understanding Evaluation on Dense Dynamic Videos Video-LLaVA: Learning United Visual Representation by Alignment Before Projection

Reference 23

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:03:01.247504Z digest=sha256:4934dedabbd76991b5378404db7582ce6eae289bd7d98fabd56babbf4a6effd5

Observation fdc38e7b-2f62-4df1-90fe-f9e2af9676f2 · outbound

This paper cites an unresolved cited work.

TUNA: Comprehensive Fine-grained Temporal Understanding Evaluation on Dense Dynamic Videos Unresolved cited work

Reference 24

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raw_fallback, observed 2026-08-07T14:03:08.613580Z

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=2026-08-07T14:03:01.395106Z digest=sha256:ea2a92e6029ca773a6d8926e773c754b893fbf007780c994b956f286e7c8a0b9

Observation 939917f6-b643-4797-8579-7fd096dd09fa · outbound

This paper cites an unresolved cited work.

TUNA: Comprehensive Fine-grained Temporal Understanding Evaluation on Dense Dynamic Videos Unresolved cited work

Reference 25

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source=arxiv_source observed=2026-08-07T14:03:01.472952Z digest=sha256:365381d232ca1ab0de9ec7a13cdff46668ed42b583ceb607c3f773a61179d333

Observation eaf1a766-f09c-4e41-81bb-9f2a1980feff · outbound

This paper cites an unresolved cited work.

TUNA: Comprehensive Fine-grained Temporal Understanding Evaluation on Dense Dynamic Videos Unresolved cited work

Reference 26

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no resolver link, observed 2026-08-07T14:03:01.537050Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:03:01.537050Z digest=sha256:3035b51de8e075642228eb58fbce3cfb71359d093f1a9ceb99449b3f453a7067

Observation 823e7951-5281-48db-96cf-5fbfa37e4a81 · outbound

This paper cites an unresolved cited work.

TUNA: Comprehensive Fine-grained Temporal Understanding Evaluation on Dense Dynamic Videos Unresolved cited work

Reference 27

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unresolved
no resolver link, observed 2026-08-07T14:03:01.649741Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:03:01.649741Z digest=sha256:b51d909a974cd35e29071a43ec40e2a6506785c7eb5fc8c0f5cf597b6da02f70

Observation 06c314bb-4e5b-4358-8610-210596f6fd2f · outbound

This paper cites Kangaroo: A Powerful Video-Language Model Supporting Long-context Video Input.

TUNA: Comprehensive Fine-grained Temporal Understanding Evaluation on Dense Dynamic Videos Kangaroo: A Powerful Video-Language Model Supporting Long-context Video Input

Reference 28

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no resolver link, observed 2026-08-07T14:03:01.765688Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:03:01.765688Z digest=sha256:bde36e2ecc7191a5d21d9a2a0fe6c1a5cf50dfc3f6d38d2b4324363893dbe09c

Observation 2708f173-e9f6-4777-bc34-1c8c981b00c6 · outbound

This paper cites an unresolved cited work.

TUNA: Comprehensive Fine-grained Temporal Understanding Evaluation on Dense Dynamic Videos Unresolved cited work

Reference 29

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raw_fallback, observed 2026-08-07T14:03:08.460404Z

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=2026-08-07T14:03:01.863307Z digest=sha256:c7f10bd7c9a8b6cf4159d7b2a851858e3eb7c3fbc4b9428972459da6b91eb68c

Observation b0da131c-681c-43d1-b8fb-429e428d7ddc · outbound

This paper cites an unresolved cited work.

TUNA: Comprehensive Fine-grained Temporal Understanding Evaluation on Dense Dynamic Videos Unresolved cited work

Reference 30

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verified exact
doi, observed 2026-08-07T14:03:06.407763Z

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=2026-08-07T14:03:01.985384Z digest=sha256:025faae66241357eabad85618bf8cab51b8fe4fbb510276fe441fd4a0d44759a

Observation f6b2953b-07dd-4141-9b12-7b53440de8a4 · outbound

This paper cites an unresolved cited work.

TUNA: Comprehensive Fine-grained Temporal Understanding Evaluation on Dense Dynamic Videos Unresolved cited work

Reference 31

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raw_fallback, observed 2026-08-07T14:03:08.331787Z

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=2026-08-07T14:03:02.097684Z digest=sha256:5d1d1858d0ae841f27fe0ff8e3a6f23f76e1b322de3f8c406cdfd1eea8007e9e

Observation 1a75c005-db20-4cb0-81a9-836b5db1d00b · outbound

This paper cites TempCompass: Do Video LLMs Really Understand Videos?.

TUNA: Comprehensive Fine-grained Temporal Understanding Evaluation on Dense Dynamic Videos TempCompass: Do Video LLMs Really Understand Videos?

Reference 32

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:03:02.241996Z digest=sha256:060a09ac2d71ef47150d8fd0bf1118d6662d2763eaa9746a0b29cc1c9b3df376

Observation 814615de-d147-4635-acdd-43e0022c6a84 · outbound

This paper cites Video-ChatGPT: Towards Detailed Video Understanding via Large Vision and Language Models.

TUNA: Comprehensive Fine-grained Temporal Understanding Evaluation on Dense Dynamic Videos Video-ChatGPT: Towards Detailed Video Understanding via Large Vision and Language Models

Reference 33

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:03:02.338167Z digest=sha256:20786fb2d69ce4812764ac79877d674bf36e2549cfbda969bad17cab6bbf2e04

Observation f82032cd-ba4f-40fb-82a5-c206f06c27c6 · outbound

This paper cites Foundation Models for Video Understanding: A Survey.

TUNA: Comprehensive Fine-grained Temporal Understanding Evaluation on Dense Dynamic Videos Foundation Models for Video Understanding: A Survey

Reference 34

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:03:02.474751Z digest=sha256:fa8f9174dfa504bac0e8b8153365d83a222fb08d55799dd10fd2d3af8843f6c6

Observation 64c62bc4-45ba-466d-b1f0-16217a8a3487 · outbound

This paper cites an unresolved cited work.

TUNA: Comprehensive Fine-grained Temporal Understanding Evaluation on Dense Dynamic Videos Unresolved cited work

Reference 35

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:03:02.600039Z digest=sha256:3b95dd6406f9c3fedb05d31611e2b44b89a8f329ce7c7ba06271670edcc1249c

Observation 6045837f-b5fc-435c-b5bc-db17e642bb90 · outbound

This paper cites an unresolved cited work.

TUNA: Comprehensive Fine-grained Temporal Understanding Evaluation on Dense Dynamic Videos Unresolved cited work

Reference 36

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raw_fallback, observed 2026-08-07T14:03:08.181720Z

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=2026-08-07T14:03:02.730496Z digest=sha256:a0c374b20b218ff247c40e9faa5ea567c7b39b3465c70a15caf8297c894dcdd0

Observation f193fbcd-8a53-448d-81b8-fe09f3edb86b · outbound

This paper cites Video-Language Understanding: A Survey from Model Architecture, Model Training, and Data Perspectives.

TUNA: Comprehensive Fine-grained Temporal Understanding Evaluation on Dense Dynamic Videos Video-Language Understanding: A Survey from Model Architecture, Model Training, and Data Perspectives

Reference 37

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:03:02.880664Z digest=sha256:d8e9b5fbffa883f1cf121be1c4567e63161a67df480cf2c8c9717475db2f82fc

Observation 6d75305c-4f53-45f0-97b3-b2dc4ef734d6 · outbound

This paper cites an unresolved cited work.

TUNA: Comprehensive Fine-grained Temporal Understanding Evaluation on Dense Dynamic Videos Unresolved cited work

Reference 38

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source=arxiv_source observed=2026-08-07T14:03:03.032042Z digest=sha256:ba0624a1280edbfc389878cd09d34412da263b359595879d5b666af6e957f72a

Observation bcf822f8-01b4-4cdd-a64d-b01db4ae688a · outbound

This paper cites Kosmos-G: Generating Images in Context with Multimodal Large Language Models.

TUNA: Comprehensive Fine-grained Temporal Understanding Evaluation on Dense Dynamic Videos Kosmos-G: Generating Images in Context with Multimodal Large Language Models

Reference 39

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source=arxiv_source observed=2026-08-07T14:03:03.103132Z digest=sha256:dfaa82784db63633ad97a5db6c42beeb785a50b0208219d43d4ac2685285871b

Observation 45cc3515-caa7-461f-ac3c-8ce2ac862378 · outbound

This paper cites an unresolved cited work.

TUNA: Comprehensive Fine-grained Temporal Understanding Evaluation on Dense Dynamic Videos Unresolved cited work

Reference 40

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source=arxiv_source observed=2026-08-07T14:03:03.200373Z digest=sha256:4b590755f0da7f324b931976b085ffa338d82d0c204db8dbbbb294b1b1898182

Observation 20e9437e-6383-4d8d-8bdf-f9ce4e318449 · outbound

This paper cites an unresolved cited work.

TUNA: Comprehensive Fine-grained Temporal Understanding Evaluation on Dense Dynamic Videos Unresolved cited work

Reference 41

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source=arxiv_source observed=2026-08-07T14:03:03.298169Z digest=sha256:d392d4f84328bcaeed5c122a8b80a4f16194511fb9bda7e00494368c420361b9

Observation e206d0a8-c434-41f9-9fbf-de7113a64fd3 · outbound

This paper cites an unresolved cited work.

TUNA: Comprehensive Fine-grained Temporal Understanding Evaluation on Dense Dynamic Videos Unresolved cited work

Reference 42

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source=arxiv_source observed=2026-08-07T14:03:03.381534Z digest=sha256:45a8d3292038eb91a2acb2ded6f719eb1f7408a7ddd5c1f99b8c787ed2afc7bc

Observation 009a03e2-e055-4955-b7cd-101054a0af00 · outbound

This paper cites an unresolved cited work.

TUNA: Comprehensive Fine-grained Temporal Understanding Evaluation on Dense Dynamic Videos Unresolved cited work

Reference 43

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source=arxiv_source observed=2026-08-07T14:03:03.463228Z digest=sha256:f79a88293ee5df6fefd95a4fa72297755fce3ba3294cbf2e5ba4501c3da5d43f

Observation 402c1531-b64c-435c-ad8c-4374b7d67849 · outbound

This paper cites Movie Gen: A Cast of Media Foundation Models.

TUNA: Comprehensive Fine-grained Temporal Understanding Evaluation on Dense Dynamic Videos Movie Gen: A Cast of Media Foundation Models

Reference 44

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source=arxiv_source observed=2026-08-07T14:03:03.532534Z digest=sha256:77a2c5b2da9838e62297dcfc3a3d586625b9716094f2315566bf88ef5a645c06

Observation df2f6b77-c048-4a91-bd1f-0b4b0a405676 · outbound

This paper cites Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context.

TUNA: Comprehensive Fine-grained Temporal Understanding Evaluation on Dense Dynamic Videos Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context

Reference 45

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source=arxiv_source observed=2026-08-07T14:03:03.622919Z digest=sha256:67849563225c097f6e60d62d9a51aa142df771f9777feac9dfe561a7789242c8

Observation 796d7a1c-a07c-4139-af8b-cce63c3964a0 · outbound

This paper cites VELOCITI: Benchmarking Video-Language Compositional Reasoning with Strict Entailment.

TUNA: Comprehensive Fine-grained Temporal Understanding Evaluation on Dense Dynamic Videos VELOCITI: Benchmarking Video-Language Compositional Reasoning with Strict Entailment

Reference 46

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source=arxiv_source observed=2026-08-07T14:03:03.688658Z digest=sha256:95a63b0014c2748aa0a454c2a1b04daf4537eddad2db0aea21a12e3dbf00fa8d

Observation ebbce05a-4324-48b2-8795-b111606f7354 · outbound

This paper cites TOMATO: Assessing Visual Temporal Reasoning Capabilities in Multimodal Foundation Models.

TUNA: Comprehensive Fine-grained Temporal Understanding Evaluation on Dense Dynamic Videos TOMATO: Assessing Visual Temporal Reasoning Capabilities in Multimodal Foundation Models

Reference 47

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source=arxiv_source observed=2026-08-07T14:03:03.750220Z digest=sha256:df1e5835bcec187018e0adfffd7cec27108eabb03dbf744ec3c55e33700b1ec8

Observation e562b6aa-ddbf-4d8b-8895-fcd721069b93 · outbound

This paper cites VidGen-1M: A Large-Scale Dataset for Text-to-video Generation.

TUNA: Comprehensive Fine-grained Temporal Understanding Evaluation on Dense Dynamic Videos VidGen-1M: A Large-Scale Dataset for Text-to-video Generation

Reference 48

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source=arxiv_source observed=2026-08-07T14:03:03.857463Z digest=sha256:f5093d6abcbc61f7d549593707c6ff17a1389d14351e0d26b9b377851aae21c8

Observation 72e2641c-295d-4f6c-9362-3a01008ddd38 · outbound

This paper cites an unresolved cited work.

TUNA: Comprehensive Fine-grained Temporal Understanding Evaluation on Dense Dynamic Videos Unresolved cited work

Reference 49

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source=arxiv_source observed=2026-08-07T14:03:03.973288Z digest=sha256:64b164f2cdc0395b5717a927a30ae209cbfe3d62d0a979eaeb7fbc8c9e3bd34a

Observation 08356e42-bbe9-408a-9ed4-959675dd8a05 · outbound

This paper cites an unresolved cited work.

TUNA: Comprehensive Fine-grained Temporal Understanding Evaluation on Dense Dynamic Videos Unresolved cited work

Reference 50

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source=arxiv_source observed=2026-08-07T14:03:04.045136Z digest=sha256:5d27f74253b6c4637125e7a67616c9071822905cf95e2fe8bb8198c977638972

Observation e152143e-f3e1-440b-be7d-f896473bbd0b · outbound

This paper cites Tarsier: Recipes for Training and Evaluating Large Video Description Models.

TUNA: Comprehensive Fine-grained Temporal Understanding Evaluation on Dense Dynamic Videos Tarsier: Recipes for Training and Evaluating Large Video Description Models

Reference 51

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source=arxiv_source observed=2026-08-07T14:03:04.111822Z digest=sha256:4ebdf53de621e8fdb9ad73e548b7a77b3147284d727970e452bb689084968e80

Observation 8123c0de-d03b-4fec-919f-b86d2ec5268c · outbound

This paper cites Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution.

TUNA: Comprehensive Fine-grained Temporal Understanding Evaluation on Dense Dynamic Videos Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution

Reference 52

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source=arxiv_source observed=2026-08-07T14:03:04.187637Z digest=sha256:5851c2b62811757f15320346de53133b17581a8a7b8d0994ed8a35caa6a1cc21

Observation 2f1cbbcd-3dc2-45c9-9f81-db94517fd77b · outbound

This paper cites an unresolved cited work.

TUNA: Comprehensive Fine-grained Temporal Understanding Evaluation on Dense Dynamic Videos Unresolved cited work

Reference 53

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

source=arxiv_source observed=2026-08-07T14:03:04.271561Z digest=sha256:fa819e384d2108f6a02d124d1b875a71244c298c2af8d8e75fb9054f46b43b86

Observation fcfd79c1-2c4a-41f0-b40b-429b1b89195f · outbound

This paper cites an unresolved cited work.

TUNA: Comprehensive Fine-grained Temporal Understanding Evaluation on Dense Dynamic Videos Unresolved cited work

Reference 54

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source=arxiv_source observed=2026-08-07T14:03:04.374879Z digest=sha256:37ad3761d7c204a76d6e7314edc5db25bb06af8d19a047e19cedf2ec45369657

Observation 265a3136-d705-4abf-b83b-6620edcb1c5b · outbound

This paper cites LVD-2M: A Long-take Video Dataset with Temporally Dense Captions.

TUNA: Comprehensive Fine-grained Temporal Understanding Evaluation on Dense Dynamic Videos LVD-2M: A Long-take Video Dataset with Temporally Dense Captions

Reference 55

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source=arxiv_source observed=2026-08-07T14:03:04.506043Z digest=sha256:477a195eee8115dea645872f775d34da6aaf44312c92848ae9a67fa52b052b2b

Observation 7cee4432-0fb8-4c1c-a2d2-7c0a4a137b7e · outbound

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

TUNA: Comprehensive Fine-grained Temporal Understanding Evaluation on Dense Dynamic Videos PLLaVA : Parameter-free LLaVA Extension from Images to Videos for Video Dense Captioning

Reference 56

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source=arxiv_source observed=2026-08-07T14:03:04.655235Z digest=sha256:8b9726d4dc95ef8925f06dc9ac20ebf32b9aa9e9cca711b2f5e8ac1a44d418e0

Observation 07fee8e3-fcbb-424e-90ab-64d20723cb18 · outbound

This paper cites MiniCPM-V: A GPT-4V Level MLLM on Your Phone.

TUNA: Comprehensive Fine-grained Temporal Understanding Evaluation on Dense Dynamic Videos MiniCPM-V: A GPT-4V Level MLLM on Your Phone

Reference 57

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source=arxiv_source observed=2026-08-07T14:03:04.827954Z digest=sha256:7dddcc115178d319e8b026bcfa68e2bd0702c38884caebd71b6bb6fcfcfcbd8a

Observation 17caf676-8060-4872-a08a-74ceb034ca59 · outbound

This paper cites MM-LLMs: Recent Advances in MultiModal Large Language Models.

TUNA: Comprehensive Fine-grained Temporal Understanding Evaluation on Dense Dynamic Videos MM-LLMs: Recent Advances in MultiModal Large Language Models

Reference 58

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source=arxiv_source observed=2026-08-07T14:03:04.955570Z digest=sha256:b591be637d9204ad58f355ca82b2647f126c88eed0e6c45ebc54023a3675fb66

Observation 5311021e-f9c7-4ee0-ad3b-82cca5cecd7f · outbound

This paper cites Data Metabolism: An Efficient Data Design Schema For Vision Language Model.

TUNA: Comprehensive Fine-grained Temporal Understanding Evaluation on Dense Dynamic Videos Data Metabolism: An Efficient Data Design Schema For Vision Language Model

Reference 59

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verified exact
local_arxiv, observed 2026-08-07T14:03:06.692996Z

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=2026-08-07T14:03:05.067370Z digest=sha256:ff4e0cedd1e9b0796c11bb69890af40603ce8008439e74b344e0cc545188c7ba

Observation a121405d-cc86-4038-9de0-7513e1cfd982 · outbound

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

TUNA: Comprehensive Fine-grained Temporal Understanding Evaluation on Dense Dynamic Videos InternLM-XComposer-2.5: A Versatile Large Vision Language Model Supporting Long-Contextual Input and Output

Reference 60

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source=arxiv_source observed=2026-08-07T14:03:05.169239Z digest=sha256:a9aaceab23faa84ab8490c5393717e4497b5d7175d873810e743b8a686f53316

Observation 2108de4d-6b3d-48a7-8140-aff954899ef2 · outbound

This paper cites Long Context Transfer from Language to Vision.

TUNA: Comprehensive Fine-grained Temporal Understanding Evaluation on Dense Dynamic Videos Long Context Transfer from Language to Vision

Reference 61

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source=arxiv_source observed=2026-08-07T14:03:05.277632Z digest=sha256:20d369f1188c58703916d39b6fc29aba5c76b2c0d381ca17a64c3a00e632141b

Observation c4d6965b-11f5-4237-b7fc-1258b9907527 · outbound

This paper cites Direct Preference Optimization of Video Large Multimodal Models from Language Model Reward.

TUNA: Comprehensive Fine-grained Temporal Understanding Evaluation on Dense Dynamic Videos Direct Preference Optimization of Video Large Multimodal Models from Language Model Reward

Reference 62

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source=arxiv_source observed=2026-08-07T14:03:05.370546Z digest=sha256:13534af8a1a3147be6e7e13fbc90a7474373346eacab308f80fcc03013aec8bc

Observation cb14725c-c296-4ee6-9a97-6465dacc2bbd · outbound

This paper cites BERTScore: Evaluating Text Generation with BERT.

TUNA: Comprehensive Fine-grained Temporal Understanding Evaluation on Dense Dynamic Videos BERTScore: Evaluating Text Generation with BERT

Reference 63

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source=arxiv_source observed=2026-08-07T14:03:05.437658Z digest=sha256:2beb9db131db8b087e9c23acf96e0c1c3880757ccde739a7605488d82b0cf0d4

Observation d8ca32b8-0707-439c-8c3d-198fa2f7a0cb · outbound

This paper cites an unresolved cited work.

TUNA: Comprehensive Fine-grained Temporal Understanding Evaluation on Dense Dynamic Videos Unresolved cited work

Reference 64

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source=arxiv_source observed=2026-08-07T14:03:05.567061Z digest=sha256:92a57664cc469ac2bedb80cb37e676c4a8ccd088a73ab892e3da9cccf83e05d2

Observation b1a20b4b-0c71-4321-a18f-87146e3c31f0 · outbound

This paper cites LLaVA-Video: Video Instruction Tuning With Synthetic Data.

TUNA: Comprehensive Fine-grained Temporal Understanding Evaluation on Dense Dynamic Videos LLaVA-Video: Video Instruction Tuning With Synthetic Data

Reference 65

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source=arxiv_source observed=2026-08-07T14:03:05.687068Z digest=sha256:695537dc5f0f33044565f953e1865736cd5c27d249dda5bcc474fa6f82cd5d55

Observation b0fcf885-c808-484a-984b-460da8e0881b · outbound

This paper cites Multimodal Chain-of-Thought Reasoning in Language Models.

TUNA: Comprehensive Fine-grained Temporal Understanding Evaluation on Dense Dynamic Videos Multimodal Chain-of-Thought Reasoning in Language Models

Reference 66

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:03:05.767363Z digest=sha256:6ed8dce72e9c4b87828c842fd9c22d837ca417fe08e94473b3d31473cc229606

Observation 658e07f5-9c74-4d90-b731-0b39d9dc1f45 · outbound

This paper cites MLVU: Benchmarking Multi-task Long Video Understanding.

TUNA: Comprehensive Fine-grained Temporal Understanding Evaluation on Dense Dynamic Videos MLVU: Benchmarking Multi-task Long Video Understanding

Reference 67

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source=arxiv_source observed=2026-08-07T14:03:05.923132Z digest=sha256:7a0af2fedc31ec478e989b3ffcab8c72600a4ee7f79dca7af5778cdd59e90cce

Observation 54e75afa-a7fe-4b6c-aab9-cedbd134b567 · outbound

This paper cites an unresolved cited work.

TUNA: Comprehensive Fine-grained Temporal Understanding Evaluation on Dense Dynamic Videos Unresolved cited work

Reference 68

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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=2026-08-07T14:03:06.003724Z digest=sha256:cfb0640ba987f4520a3fe3a8ccec1b2650786584cec198cb571542f73cb8feee

Observation b2cca2ff-6b23-4958-abd3-54644a51dca4 · outbound

This paper cites MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Models.

TUNA: Comprehensive Fine-grained Temporal Understanding Evaluation on Dense Dynamic Videos MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Models

Reference 69

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source=arxiv_source observed=2026-08-07T14:03:06.085212Z digest=sha256:3c386eb3b06c87c959dfaa733915c95eec970e1fd9f0f174a960156b6e989e43

Observation 303c9067-77cd-49e0-9bc7-fd9427d2bd23 · outbound

This paper cites online" 'onlinestring :=.

TUNA: Comprehensive Fine-grained Temporal Understanding Evaluation on Dense Dynamic Videos online" 'onlinestring :=

Reference 70

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source=arxiv_source observed=2026-08-07T14:03:06.145059Z digest=sha256:6715e786f7e7f14f1edc53dbc9945dd33d84a78254683a6de4e1ac09765c5fd9

Observation bb7d58e0-a630-4026-8b74-743761450c9b · outbound

This paper cites write newline.

TUNA: Comprehensive Fine-grained Temporal Understanding Evaluation on Dense Dynamic Videos write newline

Reference 71

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source=arxiv_source observed=2026-08-07T14:03:06.244486Z digest=sha256:dc01abec9a3c5d1fdb2a650359de3fefc0d38076c3960d8b75a37ba95b163c6f

Pith citing papers

Observation e0a6ae9e-06f8-4ccb-b4df-16bb641e9b7d · inbound

Modality Curation: Building Universal Embeddings for Advanced Multimodal Information Retrieval cites this paper.

Modality Curation: Building Universal Embeddings for Advanced Multimodal Information Retrieval TUNA: Comprehensive Fine-grained Temporal Understanding Evaluation on Dense Dynamic Videos

Reference 37

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source=pdf_text observed=2026-08-07T14:14:40.649758Z digest=sha256:0313231628401db45ba4f5bb4d8dedbe76710d28b007b95790532fe44df60419

Observation 4a43f467-6b72-4538-8332-b8e9ab49a570 · inbound

Building a Precise Video Language with Human-AI Oversight cites this paper.

Building a Precise Video Language with Human-AI Oversight TUNA: Comprehensive Fine-grained Temporal Understanding Evaluation on Dense Dynamic Videos

Reference 25

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arxiv_id, observed 2026-05-11T13:46:04.355382Z

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=2026-05-10T00:37:31.858728Z digest=sha256:6754897a6fe2c6a9acde21004c77f0c933777dbd617132090c0c4c11e0a3a75d