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Paper Citation Record · LEDGER

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

As of 9 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 2026-08-08T06:32:00.761636+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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raw_fallback, observed 2026-08-07T14:08:12.301984Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T14:08:07.334198Z digest=sha256:5a52c2280e84b23f4320defb5631abd866d4b21fce123b1cfa6e2d6574199a15

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=sha256:48e5362b05b3475dd0f39f974db6194ab301829bb8643cd13ecc80ad94cf1ab3

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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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:08:07.651269Z digest=sha256:dd9279d2b40759e7ea46b1ea9df62ebf2861b3b3c8d1bac60124c9e4f49094c9

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-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:08:07.824929Z digest=sha256:0ef90ef152104fda8db62e82dd86d69e28062f6245bb5d153eacbfd6de7e524e

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-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:08:07.940796Z digest=sha256:714162d34e83b0b14046bdfcde6d2fd67302b34abf027f99e08cbaf25a64b138

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=sha256:9fb7d8fe4e1c5d95969b0d384f171279aea365de5509ebdefddcafec81ea14de

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=sha256:6801c2aac02a72bac47440d1090fc6ff2a6807ba6c416389e54e6884a2f2ad11

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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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:08:08.176479Z digest=sha256:7aeedd180459893d5686d74b8ef4be1b49c95e49fc4949ed6170ff172a41f09e

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=sha256:38dc6beb3774b6cc877d2790c53bc874d16eb47c5a182332a7d363de25f26886

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=sha256:168afb1be6946ebd06b50a466de10e6278fb800c8c78a95d4fcfe987d28dc87a

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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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:08:08.441927Z digest=sha256:3bd509ac712d76d676fb231f94cc409fc795793c83f10191ac1ef2e337e632d9

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=sha256:10bc214544bab12dddbee143777a64a2fce0e89cd4e80b9519d54261a35f3116

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=sha256:2d962d28a8d1061d7cb576cbcc919c4e20ed951305218a760e901978c815121e

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:bc794a4b542dec778e089f3559cb26456de1aedd356991d5c76bbd57ac31a92e

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=sha256:69ed0e0d6b8f13371380ce4f0aec6b18a0c33921a4d79ac08976ee15821fe938

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:e829fc1a2b11310027cc080dbbd8b94546767ab1e5b3ee43a2648629d6001cf2

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=sha256:71a5cef91d30b2c4808e54ba3c78b9123a9d14c52553eda1ba90b85b1132a74e

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=sha256:0eaa32dcf6026a2c80dcf64e7990b51de1b060cc6bbbc5eed623497712c8b8ff

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-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:08:09.356278Z digest=sha256:563269c38d51a91a9a6221aa8233453dc2e488093d1c9e887d4da2cff8c10082

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-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:08:09.432264Z digest=sha256:8b1e26c8c59e19ad39ddf4f096c8a4fc6f2a99fae461ee275c1d631f51fdb969

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=sha256:749a04a8e5415ef4ac9acbc5755ecc9c2292fb899ca31eeb96eda65264960b52

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=sha256:9fa6cd2beb91198b2a866600ee1e4f943ef3a14e348f33fc83b46fd56e66d38a

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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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:08:09.721510Z digest=sha256:0a63e521a93d5920d7469a35219d0f09def4ad5a33b6be234076376ed895f1fd

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=sha256:07751e86b47c0bc40e56abce0a3a77c7d380328dfb2cd5c60cede9b8a1f3ecd2

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=sha256:8e0f50d92e6527be3a7c199e6795f1839338822c787e706bb443bcdd7ffa8c01

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=sha256:7d217bee664178d56a1595da869d4260ce26267cc68449e1cc59ab65e6bb4ee2

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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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:08:10.098876Z digest=sha256:ee128d28de22f7ef40220e7f866d160c0c07525542a5be36ac832d6df1e88f7e

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:b026216553a2a16ee98c3c3d55c4ef296ea8f0e2e325b481773e78825904009c

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T14:08:10.294540Z digest=sha256:cf34e80622b7a0c3a45ee610766af717b1da0ce61714ecd5e3328530f69da68c

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:f4b4bdbb1941963b7996edfc18cb2f791ddfc21d0fd9539728c4c963a93f67d8

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=sha256:52dbe0bfee5208ad8e2bcdc19925c3f19c8c666f71dcb2f392b411a45266740b

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:f4d60198e39fd0be87d51738dece77b944ff487ddb980f5c9e35e0e5f5bbe62d

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=sha256:175c4c5cd792c098c837b4a2cecfad367db371cc5ca614b33bc3a53b1dd7ee03

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=sha256:2fcb61600ef24ffd9d22206493c4eef02aa8737556f4f81a2c4a01f86fcf164c

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-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:08:10.915558Z digest=sha256:0da395324581d6bd48eb93450209c90e69b7ffe83e5b1d8b443f34299df8a053

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-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:08:11.015163Z digest=sha256:e6089793b7b85cdb8b95c53ab8f99d45d4f17804a2cf3e953abb77b7d1f470d4

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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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:08:11.091612Z digest=sha256:f1ada2dab7dbc008adea3cd06dce814dbebfc60b31ce8e8cc9fbb7cd631ed062

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=sha256:87ecf0d6b9c42e88b28d567b18eab294fdbd7f28725adaaed2eb7c025a033dbf

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:eebf30bb3ff86c54cb02cc87b43b1be4037429c516c891893f462ad471b13406

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