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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=sha256:2de97e676c2ccfb91418ab95d8885f7a2c2d09baea23fe3282a65035c07470ec

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-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:08:07.469918Z digest=sha256:bb264251c35e5419405c905f4f255308014d4f3fce59a31fbc52340e688ec53d

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:ae20db559b2309af99efc235abcda62773f92652e3caf228673c2abe8e34e39b

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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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:08:07.824929Z digest=sha256:64072a4a12e31287e3e104318410647a6c84c0e5940d731f7563b92ea11df414

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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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:08:07.940796Z digest=sha256:006e04fc75c1aabfba4b5d68a201ab1396d5507867cb2dc697f8410ad6b7000d

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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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:08:08.008568Z digest=sha256:423cbb0d588c22b6323c299d504801c5fd2c9944f16552bd13e9ef5b1af7da36

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=sha256:3f6e52fa9283d9faa84f2582e8db9eee3df561ba011083d95eba9ce78e4e8361

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=sha256:9e9e9d5b5f5ec26911e3a813a38a7a6513ca4fb49ac04f663ddad61f4764abd9

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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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:08:08.244315Z digest=sha256:f6a233e8bc9cf50b67ab5e1533df537bd52883b08badd41ff18d67da0cfe6e78

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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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:08:08.362280Z digest=sha256:13a76ec2812c7dd9efd518a1fb826a475bc76402567144cd600e478a549f987f

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:b0e091e6dd8525417a9e8d5c2752d68c16421b5f3fd8fd8fd64ebbfeed2dbb07

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=sha256:70490cde0fe610daf30b23f8e23d1bab4a023313bd8f145012eab02537d35f5c

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=sha256:6e5b7fa6bcc3b4ebd24b1bb078ac71028c9cf2a19d35033cd29f5a9420b9d02f

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:b6d80d25dcd5f16cd7bd49d9be9122dae6c1683efd96867bb3c4ea5b62da1ac2

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=sha256:98f8af06fdbc89b0484d988b73fa52e72e1f248fec0272f0e8d41f57e6414cf1

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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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:08:09.028514Z digest=sha256:6b7da961576ab49647bb7c4c6b12efc8bd846b5a7334058f3313c98247e94713

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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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:08:09.144568Z digest=sha256:c82c1aff304fad48d611e1eb0d8956af2eefec7929bb10e1949d6a82c2e8abbd

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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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:08:09.248749Z digest=sha256:2f5e452e5632cf68d1cc37791bf66e00a44ecec0b3122f09aa86eb212757d92e

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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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:08:09.356278Z digest=sha256:3748f10f73490599b5624465a7e63bc712d3fb313fe335be7e66754e56874d78

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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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:08:09.432264Z digest=sha256:e489781f93bd0a008bf10a8e4ad4a47e031ca6953c44558fa3104e595b0748a1

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=sha256:47453a5f681c936816ac9dec531023c4d496cd8347e4aa1cac92d9c575c501e0

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:d0c01e0994d0dd1d6fc84440737270a05ce1a9837af807248bb7b6132fed15eb

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=sha256:0b77c7d67bf3c895dd8d1a189bea59ca7b044e996dafb5411239d217b3536566

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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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:08:09.823977Z digest=sha256:cf51717598fb1e71d0ef959cdfe1d5304f6c8cd65fc842b741b54edad827ca1f

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-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:08:09.942396Z digest=sha256:097bde8d43a4beb72f1bfbeacb0d68b4d381713b4ac7f7e883934465a1c915b0

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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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:08:10.024398Z digest=sha256:ec817872b2b5f8ac8fee5f26dd10913e15f715af225616d92fec47b232fcd702

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=sha256:3c6b5763ecfc2b8f19efdd6de4ccc1d0aebba86075ea71f789d5cd56026aa01e

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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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:08:10.209360Z digest=sha256:baed800f557d2f024ff92d886a401e7fb0054a7100b537474d5f1c736a1c4a0a

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:ba6f4db46f40498b53c8fff433c0774d2481a1d7e95cbb121399c2a9f71bcb4e

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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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:08:10.384993Z digest=sha256:a473dc252f2cea56d2c88e412ac7a50beb197578d2c01e03f3ca1349e5ab8e7d

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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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:08:10.490334Z digest=sha256:c7f83664054e5dae9f1ba6697348d9d352d357ef16bf87326b33bcadb68c2901

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-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:08:10.568820Z digest=sha256:f23f67f36990433389ba06842e675a7379aee1ba55a3b2f6f12c739b448a6b4b

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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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:08:10.697724Z digest=sha256:2de617d540d1e8e22298361bcc84d5d65b5f007b16ff204b052d5953070faa84

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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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:08:10.807603Z digest=sha256:13e5df63de8555ff39fecb15d1b07df7eadb8fe4fd936809333790fa24cc9ea6

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:d5c08276da16fb6a63151f8474827cbb48a573855ae610a0b808e09d8e9b90b6

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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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:08:11.015163Z digest=sha256:c09e0ac45bfe9456e09a9c1674a41533355ba1cf84586074988e79b5e278b132

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:b5076be4c1c6c2204b45a0078a5230e3b2e551ba5da569807ca49a4b8b64a727

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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unresolved
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source=arxiv_source observed=2026-08-07T14:08:11.196238Z digest=sha256:2efc349630d47c49421e6723ea5215a899f0dadecb61172d0157ab34dbe8ceb2

Observation af24ddb6-0af2-402c-9f88-22bada028561 · outbound

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=sha256:0c497db9217dfcc24d616919551b2ee493bf0359dfb33f1b4b0464079fdb2f7f

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