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Paper Citation Record · LEDGER

AdaTP: Attention-Debiased Token Pruning for Video Large Language Models

As of 8 August 2026, this Paper Citation Record lists 39 of 39 outbound references and 0 inbound Pith citation observations for arXiv:2505.20100.

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

pith.paper-citation-record.v1
2505.20100 v1

Coverage vector

measured 39 of 39 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:08:11.296096Z

measured 39 of 39 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 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

39 of 39 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved39
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 71c38705-e07d-4bc7-b2ac-ffdc02face53 · outbound

This paper cites an unresolved cited work.

AdaTP: Attention-Debiased Token Pruning for Video Large Language Models Unresolved cited work

Reference 1

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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=2026-08-07T14:08:07.334198Z digest=sha256:abe247b11a7fa5673b85ffdbf3e376884bafc9faf701cd69c37c8fd78fe1c1ac

Observation 2632c7f6-f7db-4558-b5f4-5fa871d22dc3 · outbound

This paper cites an unresolved cited work.

AdaTP: Attention-Debiased Token Pruning for Video Large Language Models Unresolved cited work

Reference 2

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source=arxiv_source observed=2026-08-07T14:08:07.469918Z digest=sha256:bfcac5400b6d4640b96d434d527516df9c9038644a88fe6fbf4455e9fd59a492

Observation bc8321d9-4ebe-4ec6-9b16-5f6864a728b2 · outbound

This paper cites Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling.

AdaTP: Attention-Debiased Token Pruning for Video Large Language Models Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling

Reference 3

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:08:07.651269Z digest=sha256:b49ac2b5ee05f1eb47d3cb790e67e0e0e536d38629d83ff9e78344a76a80a031

Observation 6254fc63-920a-4b5f-87a6-2df08e1a02d5 · outbound

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

AdaTP: Attention-Debiased Token Pruning for Video Large Language Models Video-MME: The First-Ever Comprehensive Evaluation Benchmark of Multi-modal LLMs in Video Analysis

Reference 4

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source=arxiv_source observed=2026-08-07T14:08:07.824929Z digest=sha256:a85b498c4c1b5383f5874e7b8ac473a0700869ff291e5617673e75b9b72dbeb3

Observation b0622fd0-cdb1-4abe-8054-84a79293f9f5 · outbound

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

AdaTP: Attention-Debiased Token Pruning for Video Large Language Models LLaVA-OneVision: Easy Visual Task Transfer

Reference 5

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source=arxiv_source observed=2026-08-07T14:08:07.940796Z digest=sha256:5a37cb8e41ecd7c62610a4438bca69e2f7c86154e66cf88dcac3fe597ca54dcd

Observation f923c722-715d-4bfb-9910-bc41f5fbb8fd · outbound

This paper cites an unresolved cited work.

AdaTP: Attention-Debiased Token Pruning for Video Large Language Models Unresolved cited work

Reference 6

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:08:08.008568Z digest=sha256:44b4f510949713ad353d0e110d883c810c017eb5f48f4c508ed464c173be909c

Observation 534f4d18-7d34-49ee-85ae-c58f6212dcc6 · outbound

This paper cites Not All Patches are What You Need: Expediting Vision Transformers via Token Reorganizations.

AdaTP: Attention-Debiased Token Pruning for Video Large Language Models Not All Patches are What You Need: Expediting Vision Transformers via Token Reorganizations

Reference 7

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:08:08.089865Z digest=sha256:0c0becc609f39ebaa6e3a12b157ada7f2635958f2f46816489e1f6abd4aec13a

Observation a8546b57-4fee-4192-901d-55c9b19b1f6d · outbound

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

AdaTP: Attention-Debiased Token Pruning for Video Large Language Models Video-LLaVA: Learning United Visual Representation by Alignment Before Projection

Reference 8

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source=arxiv_source observed=2026-08-07T14:08:08.176479Z digest=sha256:55e46642b6f0415d57a214abf06616e770bffbd1cf8c9d03b90a8037009d813c

Observation 1c896fc2-dcc5-492d-9fb8-479e882bc975 · outbound

This paper cites an unresolved cited work.

AdaTP: Attention-Debiased Token Pruning for Video Large Language Models Unresolved cited work

Reference 9

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source=arxiv_source observed=2026-08-07T14:08:08.244315Z digest=sha256:484fd625c611b53bc00185544cbf492cc07754ab2a716d5c613ad99d044b179d

Observation a6e6a82e-f71a-4c19-8fb0-484b227b7c9b · outbound

This paper cites an unresolved cited work.

AdaTP: Attention-Debiased Token Pruning for Video Large Language Models Unresolved cited work

Reference 10

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source=arxiv_source observed=2026-08-07T14:08:08.362280Z digest=sha256:d4956953e01bda7e7bebef391eaf276998f3abb8a3eb7588d616307d5b87492e

Observation 6d01685b-994d-4601-b622-0ab88a9f2b8f · outbound

This paper cites an unresolved cited work.

AdaTP: Attention-Debiased Token Pruning for Video Large Language Models Unresolved cited work

Reference 11

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:08:08.441927Z digest=sha256:bbc6aa207e6e69af17922a4bd243a02d78aa3f5674ed1395491f21666ee146af

Observation 6a74b289-d8f6-4edf-8326-1d43112a9d3a · outbound

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

AdaTP: Attention-Debiased Token Pruning for Video Large Language Models Video-ChatGPT: Towards Detailed Video Understanding via Large Vision and Language Models

Reference 12

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:08:08.604098Z digest=sha256:0f876500bf6ccc5bc2432e0eeda99dbbc842374f62b3648cfa2f3b7fbc1cb43f

Observation 5881e8b5-c92a-453e-9282-cec7857fda4a · outbound

This paper cites Token Pooling in Vision Transformers.

AdaTP: Attention-Debiased Token Pruning for Video Large Language Models Token Pooling in Vision Transformers

Reference 13

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:08:08.722595Z digest=sha256:fd0d210ab8bf9b16699f1c6e3ec2ef3b62c842651dc1d42ccd05c8da8a6be828

Observation 28b71577-081d-48db-9b00-002d3184eb0e · outbound

This paper cites an unresolved cited work.

AdaTP: Attention-Debiased Token Pruning for Video Large Language Models Unresolved cited work

Reference 14

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:08:08.812415Z digest=sha256:5ea88e6a412c98f605796866b63f50807c0f82f30484e50b4ced3d9aecfb2838

Observation 60050535-e83c-40ad-860c-0162b6037cca · outbound

This paper cites an unresolved cited work.

AdaTP: Attention-Debiased Token Pruning for Video Large Language Models Unresolved cited work

Reference 15

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:08:08.931794Z digest=sha256:88f984dc42ea7aa7a2cbebceb5bac5a70c09350cc291be897af41bb91c1ad619

Observation 7efea8a8-b5aa-4968-98cd-7a1618d18b7e · outbound

This paper cites an unresolved cited work.

AdaTP: Attention-Debiased Token Pruning for Video Large Language Models Unresolved cited work

Reference 16

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:08:09.028514Z digest=sha256:b9c5a71f1ffb718a27717b3836af6f5939fb1929a6700668d2963dcb9e8507da

Observation e5a98b9c-3fd7-4452-be25-fa03219ee3e9 · outbound

This paper cites an unresolved cited work.

AdaTP: Attention-Debiased Token Pruning for Video Large Language Models Unresolved cited work

Reference 17

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:08:09.144568Z digest=sha256:c06dd9bc448dd7edfbf3a0dc33e34ba56b1716628b74d67663be9ca8128c883b

Observation 52f69615-1a5e-44bc-b7fc-b0b73babfd78 · outbound

This paper cites TempMe: Video Temporal Token Merging for Efficient Text-Video Retrieval.

AdaTP: Attention-Debiased Token Pruning for Video Large Language Models TempMe: Video Temporal Token Merging for Efficient Text-Video Retrieval

Reference 18

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:08:09.248749Z digest=sha256:fac9df427bc8d5a2d634569db69517535b6ed92f18adf40cc57648affeab3334

Observation 719b3a36-7538-4b16-8b26-79d5f3e9e793 · outbound

This paper cites LLaVA-MLB: Mitigating and Leveraging Attention Bias for Training-Free Video LLMs.

AdaTP: Attention-Debiased Token Pruning for Video Large Language Models LLaVA-MLB: Mitigating and Leveraging Attention Bias for Training-Free Video LLMs

Reference 19

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source=arxiv_source observed=2026-08-07T14:08:09.356278Z digest=sha256:031562118f3a978019a5e6e5471fb8a6879372a0768ebc2a32aa556f1cddb7b5

Observation 3f1acf08-3f3e-4d4d-bf9c-889c2570e0ce · outbound

This paper cites DyCoke: Dynamic Compression of Tokens for Fast Video Large Language Models.

AdaTP: Attention-Debiased Token Pruning for Video Large Language Models DyCoke: Dynamic Compression of Tokens for Fast Video Large Language Models

Reference 20

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source=arxiv_source observed=2026-08-07T14:08:09.432264Z digest=sha256:f8df0a6e626d3b99a31a689f0dbee5aa3291492bb9cd96ec5c0df398b2e58b8d

Observation b65dbd14-f6a8-49b6-92c7-ec607346748e · outbound

This paper cites Gemini: A Family of Highly Capable Multimodal Models.

AdaTP: Attention-Debiased Token Pruning for Video Large Language Models Gemini: A Family of Highly Capable Multimodal Models

Reference 21

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:08:09.546942Z digest=sha256:5c60adebd802e08c4a4db662ff3c7aaf487e6f70859e35c250d8fdcc2ea0da82

Observation 0684c49d-fb94-46a0-b763-5b078f39c65b · outbound

This paper cites [CLS] Token Tells Everything Needed for Training-free Efficient MLLMs.

AdaTP: Attention-Debiased Token Pruning for Video Large Language Models [CLS] Token Tells Everything Needed for Training-free Efficient MLLMs

Reference 22

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:08:09.626063Z digest=sha256:1153364a488f2858fddd1728cf3d2d4a1b75144f87e2cb542d65e8325e89a59c

Observation 4599b744-4add-46b6-865e-7532ca33d6c2 · outbound

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

AdaTP: Attention-Debiased Token Pruning for Video Large Language Models Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution

Reference 23

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:08:09.721510Z digest=sha256:eff7971c27ae8ea9e59959dc3a975a7a3d9ae7caf63bce15b875ab4090d93de5

Observation 4f7f90ef-383e-4577-a8fd-68578ae97ab5 · outbound

This paper cites an unresolved cited work.

AdaTP: Attention-Debiased Token Pruning for Video Large Language Models Unresolved cited work

Reference 24

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source=arxiv_source observed=2026-08-07T14:08:09.823977Z digest=sha256:1716b7677e761f5b246f9686ac6b5d9892c10814c263af4a83cc29bd40c80910

Observation 6a2b4522-d97e-4cef-9d57-7819ff5ce560 · outbound

This paper cites Efficient Streaming Language Models with Attention Sinks.

AdaTP: Attention-Debiased Token Pruning for Video Large Language Models Efficient Streaming Language Models with Attention Sinks

Reference 25

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source=arxiv_source observed=2026-08-07T14:08:09.942396Z digest=sha256:ba57340e2660d19dee6820966a9c37a2567454cd34502fca711c4ce85ecceda4

Observation 309b5d2b-9e37-4f24-ba44-7ec66d766431 · outbound

This paper cites PyramidDrop: Accelerating Your Large Vision-Language Models via Pyramid Visual Redundancy Reduction.

AdaTP: Attention-Debiased Token Pruning for Video Large Language Models PyramidDrop: Accelerating Your Large Vision-Language Models via Pyramid Visual Redundancy Reduction

Reference 26

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source=arxiv_source observed=2026-08-07T14:08:10.024398Z digest=sha256:048f8b59eeacddc8300954d86c641d81803d92fa8f449c5b400b0679dea88ddc

Observation f8ea79b2-886a-4b30-b6aa-f3be6fafe4b8 · outbound

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

AdaTP: Attention-Debiased Token Pruning for Video Large Language Models PLLaVA : Parameter-free LLaVA Extension from Images to Videos for Video Dense Captioning

Reference 27

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:08:10.098876Z digest=sha256:6331b365656e3086e251b8ac20ff6a437432e6b6da617a0e1a4d8d6a4958df68

Observation e9e59250-5ad6-411f-8c5c-3c558679a56d · outbound

This paper cites an unresolved cited work.

AdaTP: Attention-Debiased Token Pruning for Video Large Language Models Unresolved cited work

Reference 28

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source=arxiv_source observed=2026-08-07T14:08:10.209360Z digest=sha256:3759ce290a26f52586dc941ca562605eefc720308f7d9ba916157c124c3c0caf

Observation 997ad8eb-01d5-4ffc-9546-4130bccf413a · outbound

This paper cites an unresolved cited work.

AdaTP: Attention-Debiased Token Pruning for Video Large Language Models Unresolved cited work

Reference 29

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raw_fallback, observed 2026-08-07T14:08:12.075391Z

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=2026-08-07T14:08:10.294540Z digest=sha256:51405fa316531490c53ce111b58e7f27251478a19dbb9e0de1e189a5059564a5

Observation 1ebabf5a-c74d-4111-a3a1-8db4a9fb5a18 · outbound

This paper cites an unresolved cited work.

AdaTP: Attention-Debiased Token Pruning for Video Large Language Models Unresolved cited work

Reference 30

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:08:10.384993Z digest=sha256:1037b292db72054bb216a1a7037622b96cd15c468295eda3880f4777a3645716

Observation 94ea1965-e3a7-4fd4-9eec-5b6d1d628f21 · outbound

This paper cites LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models.

AdaTP: Attention-Debiased Token Pruning for Video Large Language Models LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models

Reference 31

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:08:10.490334Z digest=sha256:924fc8321887c0f12f05787dde82a0d636bd0c80c0aef67343aec4559b65ddf8

Observation a152e2cf-71b3-4838-ae5a-24f22fbedff1 · outbound

This paper cites Beyond Text-Visual Attention: Exploiting Visual Cues for Effective Token Pruning in VLMs.

AdaTP: Attention-Debiased Token Pruning for Video Large Language Models Beyond Text-Visual Attention: Exploiting Visual Cues for Effective Token Pruning in VLMs

Reference 32

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source=arxiv_source observed=2026-08-07T14:08:10.568820Z digest=sha256:b936f0aabb4a3e83a7ea58f5a0325f16b2e75fdaf4f5779280de1a1aa887ff03

Observation f3a496cd-ad53-4c95-84c7-41cd139ded15 · outbound

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

AdaTP: Attention-Debiased Token Pruning for Video Large Language Models LLaVA-Video: Video Instruction Tuning With Synthetic Data

Reference 33

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:08:10.697724Z digest=sha256:7570c1627a9518d93e0f5160af938f45d84fbb0abe51974d8b2ac0f25ee3c799

Observation 68ab79c8-9c58-4478-a77d-c559245a1bea · outbound

This paper cites an unresolved cited work.

AdaTP: Attention-Debiased Token Pruning for Video Large Language Models Unresolved cited work

Reference 34

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:08:10.807603Z digest=sha256:72757a3eb7a62cc8fc285bac10ed639bf52e2369c2d74721017b65b8d8649883

Observation 4ed619fe-2182-414b-afff-bd1a1ca8dd69 · outbound

This paper cites AIM: Adaptive Inference of Multi-Modal LLMs via Token Merging and Pruning.

AdaTP: Attention-Debiased Token Pruning for Video Large Language Models AIM: Adaptive Inference of Multi-Modal LLMs via Token Merging and Pruning

Reference 35

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source=arxiv_source observed=2026-08-07T14:08:10.915558Z digest=sha256:9017e646908e49e0cdd81d1e749e7aa0e678d94603c58d2327cc7ed07edb3e2f

Observation 952ba7ea-fada-4dde-9e84-ad50a5522652 · outbound

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

AdaTP: Attention-Debiased Token Pruning for Video Large Language Models MLVU: Benchmarking Multi-task Long Video Understanding

Reference 36

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source=arxiv_source observed=2026-08-07T14:08:11.015163Z digest=sha256:6f05b9824e50457fa21a677652bd6d2ee6d5ac8166993a0fc39d32674b694e64

Observation 6010160f-7766-4bbb-8aaf-153c129cd9cc · outbound

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

AdaTP: Attention-Debiased Token Pruning for Video Large Language Models MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Models

Reference 37

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:08:11.091612Z digest=sha256:e4898042f7ebf07b8e9b79e5e38fb96f0f301c719bc7e974e65f2962928805f5

Observation 8786fdcd-26d9-4adf-934a-6e0d31b5786c · outbound

This paper cites online" 'onlinestring :=.

AdaTP: Attention-Debiased Token Pruning for Video Large Language Models online" 'onlinestring :=

Reference 38

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no resolver link, observed 2026-08-07T14:08:11.196238Z

Source-reported events for the cited work

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source=arxiv_source observed=2026-08-07T14:08:11.196238Z digest=sha256:bd00fe567557872bceb1640d12eddc5b926ce8f72c9157d7518b703f749c7b17

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This paper cites write newline.

AdaTP: Attention-Debiased Token Pruning for Video Large Language Models write newline

Reference 39

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source=arxiv_source observed=2026-08-07T14:08:11.296096Z digest=sha256:970acfc020c63efe1a9b801d336608ff77db45610c599eab4b7c24e1b5bed926

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