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Paper Citation Record · LEDGER

EffiVLM-BENCH: A Comprehensive Benchmark for Evaluating Training-Free Acceleration in Large Vision-Language Models

As of 7 August 2026, this Paper Citation Record lists 77 of 77 outbound references and 0 inbound Pith citation observations for arXiv:2506.00479.

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

pith.paper-citation-record.v1
2506.00479 v1

Coverage vector

measured 77 of 77 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:09:11.183706Z

measured 77 of 77 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

77 of 77 outbound references displayed

  • verified exact2
  • verified fuzzy3
  • unresolved72
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f56fb0a5-7b6a-458d-b587-2c0220979ec5 · outbound

This paper cites an unresolved cited work.

EffiVLM-BENCH: A Comprehensive Benchmark for Evaluating Training-Free Acceleration in Large Vision-Language Models Unresolved cited work

Reference 1

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Observation 9c26ac62-efaf-44e5-ad12-3cede73a7382 · outbound

This paper cites an unresolved cited work.

EffiVLM-BENCH: A Comprehensive Benchmark for Evaluating Training-Free Acceleration in Large Vision-Language Models Unresolved cited work

Reference 2

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source=arxiv_source observed=2026-08-07T12:09:02.625316Z digest=sha256:751e5c598c026c83505acd0ccbcd2ba91bc0b3459e008f9f8e907182838e86d9

Observation 00b19a81-e497-47b2-83de-74d6d022971c · outbound

This paper cites Token merging: Your vit but faster.

EffiVLM-BENCH: A Comprehensive Benchmark for Evaluating Training-Free Acceleration in Large Vision-Language Models Token merging: Your vit but faster

Reference 3

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T12:09:02.726098Z digest=sha256:aaf919eaf87f888f6611055ddd662ce1f297238a4bc3ac264553ed4b2576cb50

Observation f7e81d51-b139-4664-b78c-65b990cad2b3 · outbound

This paper cites LLaVA-KD: A Framework of Distilling Multimodal Large Language Models.

EffiVLM-BENCH: A Comprehensive Benchmark for Evaluating Training-Free Acceleration in Large Vision-Language Models LLaVA-KD: A Framework of Distilling Multimodal Large Language Models

Reference 4

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source=arxiv_source observed=2026-08-07T12:09:02.820442Z digest=sha256:acc076ada30bc0ffb500b96b9bf62986e53cd586e7ae0a7cf2ddad413b8f5355

Observation 9919307c-5500-4ba4-983b-81b8f588db1e · outbound

This paper cites PyramidKV: Dynamic KV Cache Compression based on Pyramidal Information Funneling.

EffiVLM-BENCH: A Comprehensive Benchmark for Evaluating Training-Free Acceleration in Large Vision-Language Models PyramidKV: Dynamic KV Cache Compression based on Pyramidal Information Funneling

Reference 5

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source=arxiv_source observed=2026-08-07T12:09:02.889790Z digest=sha256:c3876c8a1517386795501c1117b46eaa444c43b4b796799b4afedf65bbfc0762

Observation b45c0c22-95bf-467a-9f2e-a61f2e07b3b5 · outbound

This paper cites an unresolved cited work.

EffiVLM-BENCH: A Comprehensive Benchmark for Evaluating Training-Free Acceleration in Large Vision-Language Models Unresolved cited work

Reference 6

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Observation 67d9685b-6d5b-432a-a3e2-9e6eb2243803 · outbound

This paper cites ALLaVA: Harnessing GPT4V-Synthesized Data for Lite Vision-Language Models.

EffiVLM-BENCH: A Comprehensive Benchmark for Evaluating Training-Free Acceleration in Large Vision-Language Models ALLaVA: Harnessing GPT4V-Synthesized Data for Lite Vision-Language Models

Reference 7

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Observation ffc00c09-4437-4a0a-9da6-f8bc35463f43 · outbound

This paper cites an unresolved cited work.

EffiVLM-BENCH: A Comprehensive Benchmark for Evaluating Training-Free Acceleration in Large Vision-Language Models Unresolved cited work

Reference 8

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Observation 311932d2-583b-4b36-bfe5-d64663fbeb51 · outbound

This paper cites Are We on the Right Way for Evaluating Large Vision-Language Models?.

EffiVLM-BENCH: A Comprehensive Benchmark for Evaluating Training-Free Acceleration in Large Vision-Language Models Are We on the Right Way for Evaluating Large Vision-Language Models?

Reference 9

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source=arxiv_source observed=2026-08-07T12:09:03.262385Z digest=sha256:3e419a7d09daf15470901493e8f53bb381f4f141498e8cc8d2cad48f0b408d02

Observation 5440017d-14d2-4a21-9b9c-d8b6c051913e · outbound

This paper cites Microsoft COCO Captions: Data Collection and Evaluation Server.

EffiVLM-BENCH: A Comprehensive Benchmark for Evaluating Training-Free Acceleration in Large Vision-Language Models Microsoft COCO Captions: Data Collection and Evaluation Server

Reference 10

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Observation 45b1c30d-60b4-4e2d-9249-f678a1b45626 · outbound

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

EffiVLM-BENCH: A Comprehensive Benchmark for Evaluating Training-Free Acceleration in Large Vision-Language Models Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling

Reference 11

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Observation 3aa2728d-3fec-4f78-a294-8fad8b760c77 · outbound

This paper cites MobileVLM : A Fast, Strong and Open Vision Language Assistant for Mobile Devices.

EffiVLM-BENCH: A Comprehensive Benchmark for Evaluating Training-Free Acceleration in Large Vision-Language Models MobileVLM : A Fast, Strong and Open Vision Language Assistant for Mobile Devices

Reference 12

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Observation ea5b6afa-9964-43cb-adf9-cc7da093ce47 · outbound

This paper cites an unresolved cited work.

EffiVLM-BENCH: A Comprehensive Benchmark for Evaluating Training-Free Acceleration in Large Vision-Language Models Unresolved cited work

Reference 13

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Observation cfa5ad37-f96d-4625-a669-331cb7de822c · outbound

This paper cites an unresolved cited work.

EffiVLM-BENCH: A Comprehensive Benchmark for Evaluating Training-Free Acceleration in Large Vision-Language Models Unresolved cited work

Reference 14

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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=2026-08-07T12:09:03.742644Z digest=sha256:e9ee34c162fabbc80e75cca2d1b8342e41e087d216dd2600c0b3a8e8897cad02

Observation f1e9f16a-d582-48eb-b18c-fde23eb30dc1 · outbound

This paper cites an unresolved cited work.

EffiVLM-BENCH: A Comprehensive Benchmark for Evaluating Training-Free Acceleration in Large Vision-Language Models Unresolved cited work

Reference 15

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T12:09:03.840614Z digest=sha256:87f9a3468e9d8755fad4ef8f04bde438537950b609b7e869e2ff7040d0a83354

Observation 58ca255d-2b00-4c9e-8cb7-7068e9f27fc1 · outbound

This paper cites Molmo and PixMo: Open Weights and Open Data for State-of-the-Art Vision-Language Models.

EffiVLM-BENCH: A Comprehensive Benchmark for Evaluating Training-Free Acceleration in Large Vision-Language Models Molmo and PixMo: Open Weights and Open Data for State-of-the-Art Vision-Language Models

Reference 16

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Observation aab7c8d1-1eb8-462b-a3ac-f2e7918ed958 · outbound

This paper cites an unresolved cited work.

EffiVLM-BENCH: A Comprehensive Benchmark for Evaluating Training-Free Acceleration in Large Vision-Language Models Unresolved cited work

Reference 17

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Observation 33196863-26c8-45e1-8c32-b3d57eb5a418 · outbound

This paper cites GPTQ: Accurate Post-Training Quantization for Generative Pre-trained Transformers.

EffiVLM-BENCH: A Comprehensive Benchmark for Evaluating Training-Free Acceleration in Large Vision-Language Models GPTQ: Accurate Post-Training Quantization for Generative Pre-trained Transformers

Reference 18

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Observation 12fb0c08-b472-4d86-9027-a4accd4e0e3e · outbound

This paper cites MME: A Comprehensive Evaluation Benchmark for Multimodal Large Language Models.

EffiVLM-BENCH: A Comprehensive Benchmark for Evaluating Training-Free Acceleration in Large Vision-Language Models MME: A Comprehensive Evaluation Benchmark for Multimodal Large Language Models

Reference 19

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Observation 657c798b-fb57-45c1-944a-7d1ac31829db · outbound

This paper cites an unresolved cited work.

EffiVLM-BENCH: A Comprehensive Benchmark for Evaluating Training-Free Acceleration in Large Vision-Language Models Unresolved cited work

Reference 20

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 75f8cb19-397f-4d05-a1cd-aa2bfdcfb978 · outbound

This paper cites an unresolved cited work.

EffiVLM-BENCH: A Comprehensive Benchmark for Evaluating Training-Free Acceleration in Large Vision-Language Models Unresolved cited work

Reference 21

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Observation e2cfb951-d60c-40ed-a503-e003e29d048e · outbound

This paper cites Dynamic-LLaVA: Efficient Multimodal Large Language Models via Dynamic Vision-language Context Sparsification.

EffiVLM-BENCH: A Comprehensive Benchmark for Evaluating Training-Free Acceleration in Large Vision-Language Models Dynamic-LLaVA: Efficient Multimodal Large Language Models via Dynamic Vision-language Context Sparsification

Reference 22

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Observation b0975858-64f8-4524-9445-65932fa0b3a0 · outbound

This paper cites an unresolved cited work.

EffiVLM-BENCH: A Comprehensive Benchmark for Evaluating Training-Free Acceleration in Large Vision-Language Models Unresolved cited work

Reference 23

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Observation d56bc46e-ef93-4f45-a84a-fe0b108909f6 · outbound

This paper cites A Diagram Is Worth A Dozen Images.

EffiVLM-BENCH: A Comprehensive Benchmark for Evaluating Training-Free Acceleration in Large Vision-Language Models A Diagram Is Worth A Dozen Images

Reference 24

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Observation 50b7079d-2a18-4360-bdc5-d780251ed9af · outbound

This paper cites an unresolved cited work.

EffiVLM-BENCH: A Comprehensive Benchmark for Evaluating Training-Free Acceleration in Large Vision-Language Models Unresolved cited work

Reference 25

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Observation 8d6e7b60-b348-4a02-ae26-27e5859a82b9 · outbound

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

EffiVLM-BENCH: A Comprehensive Benchmark for Evaluating Training-Free Acceleration in Large Vision-Language Models LLaVA-OneVision: Easy Visual Task Transfer

Reference 26

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Observation 9f5a24b9-6c20-4983-ad8f-d9e2bcdde671 · outbound

This paper cites TokenPacker: Efficient Visual Projector for Multimodal LLM.

EffiVLM-BENCH: A Comprehensive Benchmark for Evaluating Training-Free Acceleration in Large Vision-Language Models TokenPacker: Efficient Visual Projector for Multimodal LLM

Reference 27

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Observation aa089c92-f5ec-4752-a6ee-208d7d71c1ab · outbound

This paper cites Mini-Gemini: Mining the Potential of Multi-modality Vision Language Models.

EffiVLM-BENCH: A Comprehensive Benchmark for Evaluating Training-Free Acceleration in Large Vision-Language Models Mini-Gemini: Mining the Potential of Multi-modality Vision Language Models

Reference 28

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Observation 8986123c-c5a2-47e1-8ac1-afc60ddea231 · outbound

This paper cites SnapKV: LLM Knows What You are Looking for Before Generation.

EffiVLM-BENCH: A Comprehensive Benchmark for Evaluating Training-Free Acceleration in Large Vision-Language Models SnapKV: LLM Knows What You are Looking for Before Generation

Reference 29

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Observation ac921fad-726d-400e-9f44-58e6cc0506de · outbound

This paper cites Perception, Reason, Think, and Plan: A Survey on Large Multimodal Reasoning Models.

EffiVLM-BENCH: A Comprehensive Benchmark for Evaluating Training-Free Acceleration in Large Vision-Language Models Perception, Reason, Think, and Plan: A Survey on Large Multimodal Reasoning Models

Reference 30

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Observation 02c49dd8-33eb-4ec9-a29d-e2a95d0a0a75 · outbound

This paper cites an unresolved cited work.

EffiVLM-BENCH: A Comprehensive Benchmark for Evaluating Training-Free Acceleration in Large Vision-Language Models Unresolved cited work

Reference 31

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source=arxiv_source observed=2026-08-07T12:09:05.435659Z digest=sha256:f68b460e2ac08efc69d05451410c356a9d5fcff63b1e503b207e8d30e99e2caf

Observation 0ef4e4e5-e58d-454d-a874-6e12eace66a4 · outbound

This paper cites an unresolved cited work.

EffiVLM-BENCH: A Comprehensive Benchmark for Evaluating Training-Free Acceleration in Large Vision-Language Models Unresolved cited work

Reference 32

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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=2026-08-07T12:09:05.571066Z digest=sha256:955008aace5592a79b5af7b178b8c60e2173c4485cdd705c4cf8606de77fc622

Observation e919dc04-8a62-40d2-95b5-9f6c2a07ce50 · outbound

This paper cites an unresolved cited work.

EffiVLM-BENCH: A Comprehensive Benchmark for Evaluating Training-Free Acceleration in Large Vision-Language Models Unresolved cited work

Reference 33

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 6c22fad2-d0f7-4780-8135-18e990911e86 · outbound

This paper cites MMBench: Is Your Multi-modal Model an All-around Player?.

EffiVLM-BENCH: A Comprehensive Benchmark for Evaluating Training-Free Acceleration in Large Vision-Language Models MMBench: Is Your Multi-modal Model an All-around Player?

Reference 34

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source=arxiv_source observed=2026-08-07T12:09:05.822627Z digest=sha256:799e3cfe8e9994e2cefa7ce0e882c5a991aec3ec5e7baccf5b024a276553ea41

Observation b08b161d-24b7-43bf-8312-00c114ed167b · outbound

This paper cites an unresolved cited work.

EffiVLM-BENCH: A Comprehensive Benchmark for Evaluating Training-Free Acceleration in Large Vision-Language Models Unresolved cited work

Reference 35

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source=arxiv_source observed=2026-08-07T12:09:06.026445Z digest=sha256:e062d2719d801a03746ecf4840f135d2f4bf3869a44de592b8e1aa6f68902d2d

Observation df08e76c-feda-4625-aff8-133bf071001d · outbound

This paper cites NVILA: Efficient Frontier Visual Language Models.

EffiVLM-BENCH: A Comprehensive Benchmark for Evaluating Training-Free Acceleration in Large Vision-Language Models NVILA: Efficient Frontier Visual Language Models

Reference 36

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:09:06.218354Z digest=sha256:353bc18d3e9c6773f67ff086568ff484f50cf42dbd12b2ac66e4c5eba1522d02

Observation 11a2caad-c4de-467c-9a78-67ee2c14d35f · outbound

This paper cites DeepSeek-VL: Towards Real-World Vision-Language Understanding.

EffiVLM-BENCH: A Comprehensive Benchmark for Evaluating Training-Free Acceleration in Large Vision-Language Models DeepSeek-VL: Towards Real-World Vision-Language Understanding

Reference 37

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no resolver link, observed 2026-08-07T12:09:06.433177Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:09:06.433177Z digest=sha256:e5dabf5d0b06bfcb8bf3955b66cf59a492d0d65fd69fb23f175692a0884d3e90

Observation eea8e480-f364-4e85-aa6d-19af943891c0 · outbound

This paper cites an unresolved cited work.

EffiVLM-BENCH: A Comprehensive Benchmark for Evaluating Training-Free Acceleration in Large Vision-Language Models Unresolved cited work

Reference 38

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unresolved
raw_fallback, observed 2026-08-07T12:09:13.912847Z

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=2026-08-07T12:09:06.593994Z digest=sha256:3d805bb539d981ff17a93975f54545702fcd963564c5b07245496756722be774

Observation da8c2a85-2051-4c3e-bb92-342941a2ceda · outbound

This paper cites $\gamma-$MoD: Exploring Mixture-of-Depth Adaptation for Multimodal Large Language Models.

EffiVLM-BENCH: A Comprehensive Benchmark for Evaluating Training-Free Acceleration in Large Vision-Language Models $\gamma-$MoD: Exploring Mixture-of-Depth Adaptation for Multimodal Large Language Models

Reference 39

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no resolver link, observed 2026-08-07T12:09:06.707034Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:09:06.707034Z digest=sha256:92211985f48d142164e43c75746ad6af69c25bd484d78a93d26531efa0bf52d6

Observation 3259a21a-63af-4a58-8077-6b545e38a270 · outbound

This paper cites ChartQA: A Benchmark for Question Answering about Charts with Visual and Logical Reasoning.

EffiVLM-BENCH: A Comprehensive Benchmark for Evaluating Training-Free Acceleration in Large Vision-Language Models ChartQA: A Benchmark for Question Answering about Charts with Visual and Logical Reasoning

Reference 40

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no resolver link, observed 2026-08-07T12:09:06.790342Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:09:06.790342Z digest=sha256:d9dbc3ea0ec0afc7f5eef31c7aebfed84be9427c4accc8757ea66f7f7c544a59

Observation 7e1f81cd-a1b2-4d68-b093-2d83107fdba0 · outbound

This paper cites DocVQA: A Dataset for VQA on Document Images.

EffiVLM-BENCH: A Comprehensive Benchmark for Evaluating Training-Free Acceleration in Large Vision-Language Models DocVQA: A Dataset for VQA on Document Images

Reference 41

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no resolver link, observed 2026-08-07T12:09:06.849342Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:09:06.849342Z digest=sha256:87658c1bdde4c6c77931b30bea0ae06c6f9fabf68635de5a22138f7b1f9181de

Observation 62e0cd97-5876-42bb-a1f2-5ad3850420cf · outbound

This paper cites an unresolved cited work.

EffiVLM-BENCH: A Comprehensive Benchmark for Evaluating Training-Free Acceleration in Large Vision-Language Models Unresolved cited work

Reference 42

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no resolver link, observed 2026-08-07T12:09:06.996816Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:09:06.996816Z digest=sha256:367b673e4d45b25928463a9a7d7b3b555e425ef5922c0cf258b3ec9c78362e40

Observation 7dad4a3b-d688-4838-bf69-4c55f5f51167 · outbound

This paper cites an unresolved cited work.

EffiVLM-BENCH: A Comprehensive Benchmark for Evaluating Training-Free Acceleration in Large Vision-Language Models Unresolved cited work

Reference 43

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unresolved
raw_fallback, observed 2026-08-07T12:09:13.744307Z

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=2026-08-07T12:09:07.153496Z digest=sha256:2f2628f1a2c160f288dc646eaab8c9f601df6d4528ba0e7046c6e57fa2466e30

Observation b29b7b36-0969-493b-b45d-fef4ece0c31a · outbound

This paper cites Gated Attention for Large Language Models: Non-linearity, Sparsity, and Attention-Sink-Free.

EffiVLM-BENCH: A Comprehensive Benchmark for Evaluating Training-Free Acceleration in Large Vision-Language Models Gated Attention for Large Language Models: Non-linearity, Sparsity, and Attention-Sink-Free

Reference 44

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no resolver link, observed 2026-08-07T12:09:07.284810Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:09:07.284810Z digest=sha256:b9a48add57dd858d30a97f6556e8da34ead6921b358f755010eb76944afda43c

Observation 4aa1e786-45bd-4b27-be5b-431ff7de85b1 · outbound

This paper cites an unresolved cited work.

EffiVLM-BENCH: A Comprehensive Benchmark for Evaluating Training-Free Acceleration in Large Vision-Language Models Unresolved cited work

Reference 45

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no resolver link, observed 2026-08-07T12:09:07.427986Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:09:07.427986Z digest=sha256:88bb6e04d3a9e3820981b1815bdfd2691eac495b8c222080ecd33f6dde25a4bf

Observation 02e740a3-e6a5-40af-9e5b-e2df760632d3 · outbound

This paper cites LLaVA-MoD: Making LLaVA Tiny via MoE Knowledge Distillation.

EffiVLM-BENCH: A Comprehensive Benchmark for Evaluating Training-Free Acceleration in Large Vision-Language Models LLaVA-MoD: Making LLaVA Tiny via MoE Knowledge Distillation

Reference 46

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no resolver link, observed 2026-08-07T12:09:07.514859Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:09:07.514859Z digest=sha256:055c5b860ceedfb0e330674ed0359243c6c7c894067358b7f25fe43f0a231f4a

Observation 87806932-2c6b-47b2-b480-14688314a791 · outbound

This paper cites an unresolved cited work.

EffiVLM-BENCH: A Comprehensive Benchmark for Evaluating Training-Free Acceleration in Large Vision-Language Models Unresolved cited work

Reference 47

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unresolved
no resolver link, observed 2026-08-07T12:09:07.618949Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:09:07.618949Z digest=sha256:d0868ca6ce8802547f35cf2cb38cf4dcc01c3f47f0399b99cf59a4225e633767

Observation 2042abbd-d90d-445f-9c54-2a82c3e8af38 · outbound

This paper cites MovieChat: From Dense Token to Sparse Memory for Long Video Understanding.

EffiVLM-BENCH: A Comprehensive Benchmark for Evaluating Training-Free Acceleration in Large Vision-Language Models MovieChat: From Dense Token to Sparse Memory for Long Video Understanding

Reference 48

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no resolver link, observed 2026-08-07T12:09:07.794518Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:09:07.794518Z digest=sha256:e9cd08db26703c5a31cefe8800c27b48f4af12e02606c95f757d57de3530aaf8

Observation 0195c9a1-0b52-4e98-9abe-f1bd09faac68 · outbound

This paper cites A Simple and Effective Pruning Approach for Large Language Models.

EffiVLM-BENCH: A Comprehensive Benchmark for Evaluating Training-Free Acceleration in Large Vision-Language Models A Simple and Effective Pruning Approach for Large Language Models

Reference 49

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no resolver link, observed 2026-08-07T12:09:07.878549Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:09:07.878549Z digest=sha256:9ac8570eb314a21baae0e15a5bae474795a06ca56d2c4970ade9fa944e224525

Observation 344b9015-776b-4c94-affa-9a911504e288 · outbound

This paper cites ECoFLaP: Efficient Coarse-to-Fine Layer-Wise Pruning for Vision-Language Models.

EffiVLM-BENCH: A Comprehensive Benchmark for Evaluating Training-Free Acceleration in Large Vision-Language Models ECoFLaP: Efficient Coarse-to-Fine Layer-Wise Pruning for Vision-Language Models

Reference 50

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no resolver link, observed 2026-08-07T12:09:08.047002Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:09:08.047002Z digest=sha256:39f081a8f063d11f0ad04ee509a6003d1dd4343bd732ea9a33a7b55baa49291b

Observation 9ff81832-14f7-450c-886e-1bde2af39fc9 · outbound

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

EffiVLM-BENCH: A Comprehensive Benchmark for Evaluating Training-Free Acceleration in Large Vision-Language Models Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context

Reference 51

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no resolver link, observed 2026-08-07T12:09:08.160820Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:09:08.160820Z digest=sha256:52d3d4e582d0447b0f9cd7c864741f357368f0b08f169f7fbb109b69422746a1

Observation 30e50b78-3da5-4559-898c-61b8cf554435 · outbound

This paper cites an unresolved cited work.

EffiVLM-BENCH: A Comprehensive Benchmark for Evaluating Training-Free Acceleration in Large Vision-Language Models Unresolved cited work

Reference 52

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no resolver link, observed 2026-08-07T12:09:08.269554Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:09:08.269554Z digest=sha256:0778b6f1a19a0aa5d863704b7bfd46caedde9ea99ce3a74cfa4e4f8951cd7397

Observation b72f363f-e7cc-4bdb-8aae-8c7ab167779e · outbound

This paper cites Hierarchical multimodal transformers for Multi-Page DocVQA.

EffiVLM-BENCH: A Comprehensive Benchmark for Evaluating Training-Free Acceleration in Large Vision-Language Models Hierarchical multimodal transformers for Multi-Page DocVQA

Reference 53

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no resolver link, observed 2026-08-07T12:09:08.417275Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:09:08.417275Z digest=sha256:c72ee1efef73f13ec779a7eaf015d910a958d4ebd87250816e6cb831b4bb4bbd

Observation 90c47060-c235-431c-96c6-da62c80e40bc · outbound

This paper cites VL-Cache: Sparsity and Modality-Aware KV Cache Compression for Vision-Language Model Inference Acceleration.

EffiVLM-BENCH: A Comprehensive Benchmark for Evaluating Training-Free Acceleration in Large Vision-Language Models VL-Cache: Sparsity and Modality-Aware KV Cache Compression for Vision-Language Model Inference Acceleration

Reference 54

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unresolved
no resolver link, observed 2026-08-07T12:09:08.527752Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:09:08.527752Z digest=sha256:0918def4890c37e89d75be23a10e2c403b172b81be8aa953f070e795df548609

Observation 90f8f698-5f3e-49dd-8346-83e0e5bd9760 · outbound

This paper cites an unresolved cited work.

EffiVLM-BENCH: A Comprehensive Benchmark for Evaluating Training-Free Acceleration in Large Vision-Language Models Unresolved cited work

Reference 55

Resolution
unresolved
raw_fallback, observed 2026-08-07T12:09:13.559711Z

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=2026-08-07T12:09:08.688896Z digest=sha256:26370086ae5bd86c252e52af3492ebec9d91a2fb856a552c86a03f7a84ef8c0f

Observation f3044e37-f678-4b5a-984e-4f836446bc1a · outbound

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

EffiVLM-BENCH: A Comprehensive Benchmark for Evaluating Training-Free Acceleration in Large Vision-Language Models Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution

Reference 56

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unresolved
no resolver link, observed 2026-08-07T12:09:08.800886Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:09:08.800886Z digest=sha256:73c37fb304cff8f0328028b4939ba6c236b6a85c05f1e1e54e53a238f28506d6

Observation 1711006d-f79b-4188-815e-2e6908de78ed · outbound

This paper cites an unresolved cited work.

EffiVLM-BENCH: A Comprehensive Benchmark for Evaluating Training-Free Acceleration in Large Vision-Language Models Unresolved cited work

Reference 57

Resolution
unresolved
raw_fallback, observed 2026-08-07T12:09:13.360928Z

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=2026-08-07T12:09:08.926829Z digest=sha256:1cb77d82f7ee51f273e2dbcdbe4d577809812a0e4f79f6b79ba78dff0ec815a3

Observation 3defe7bf-cf5e-49c7-8324-460f89e2e9a0 · outbound

This paper cites CFSP: An Efficient Structured Pruning Framework for LLMs with Coarse-to-Fine Activation Information.

EffiVLM-BENCH: A Comprehensive Benchmark for Evaluating Training-Free Acceleration in Large Vision-Language Models CFSP: An Efficient Structured Pruning Framework for LLMs with Coarse-to-Fine Activation Information

Reference 58

Resolution
verified exact
local_arxiv, observed 2026-08-07T12:09:11.412685Z

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=2026-08-07T12:09:09.062426Z digest=sha256:da14911c0d1357a89d21fa7f4a945985ed1f97037624fc9640aac766dc367cdb

Observation 399bf6f5-25a4-4e1f-8613-2c2e36431556 · outbound

This paper cites SmartTrim: Adaptive Tokens and Attention Pruning for Efficient Vision-Language Models.

EffiVLM-BENCH: A Comprehensive Benchmark for Evaluating Training-Free Acceleration in Large Vision-Language Models SmartTrim: Adaptive Tokens and Attention Pruning for Efficient Vision-Language Models

Reference 59

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no resolver link, observed 2026-08-07T12:09:09.213401Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:09:09.213401Z digest=sha256:5792c318b227b82e65ca6ae30682ccb528d67b82f3f2c0cb266fbd5760d2ce16

Observation 02d43063-5dfa-4778-8c3a-a58d4b5a1cd2 · outbound

This paper cites Distilled Dual-Encoder Model for Vision-Language Understanding.

EffiVLM-BENCH: A Comprehensive Benchmark for Evaluating Training-Free Acceleration in Large Vision-Language Models Distilled Dual-Encoder Model for Vision-Language Understanding

Reference 60

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verified exact
local_arxiv, observed 2026-08-07T12:09:11.842112Z

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=2026-08-07T12:09:09.309361Z digest=sha256:676a22bb41eefd9eed281d38349698f5af996b2edefab26ce04d62a4cbd11db4

Observation 15fb7c56-bd39-48f3-9a26-0a0acb1656b7 · outbound

This paper cites https://x.ai/blog/grok-1.5v Grok-1.5 vision preview.

EffiVLM-BENCH: A Comprehensive Benchmark for Evaluating Training-Free Acceleration in Large Vision-Language Models https://x.ai/blog/grok-1.5v Grok-1.5 vision preview

Reference 61

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verified fuzzy
raw_fallback, observed 2026-08-07T12:09:13.215592Z

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=2026-08-07T12:09:09.399595Z digest=sha256:66a1bcaedef1145c3a0a296da411a4de3b5f3f5dddc566c95465fe7cb7030bcf

Observation 27c69028-80a4-487e-94fb-5e1f195dfea1 · outbound

This paper cites an unresolved cited work.

EffiVLM-BENCH: A Comprehensive Benchmark for Evaluating Training-Free Acceleration in Large Vision-Language Models Unresolved cited work

Reference 62

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unresolved
raw_fallback, observed 2026-08-07T12:09:13.071841Z

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=2026-08-07T12:09:09.489451Z digest=sha256:e90ac97bc084efa5cd2e43ef6a5e27452d359ffe28b9fe1e6db76b01422b72b3

Observation 58a8b3e5-1e7e-43d0-8ef3-2fef8cc8e629 · outbound

This paper cites McAuley, and Furu Wei.

EffiVLM-BENCH: A Comprehensive Benchmark for Evaluating Training-Free Acceleration in Large Vision-Language Models McAuley, and Furu Wei

Reference 63

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verified fuzzy
raw_fallback, observed 2026-08-07T12:09:12.876667Z

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=2026-08-07T12:09:09.615671Z digest=sha256:558c0447110f6b26b3a5e01a26fd99909c42a2a118f751def97a824d740e9c67

Observation c2ca67bb-415e-46f5-98e8-32e0ef0a2cc3 · outbound

This paper cites Aguvis: Unified Pure Vision Agents for Autonomous GUI Interaction.

EffiVLM-BENCH: A Comprehensive Benchmark for Evaluating Training-Free Acceleration in Large Vision-Language Models Aguvis: Unified Pure Vision Agents for Autonomous GUI Interaction

Reference 64

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no resolver link, observed 2026-08-07T12:09:09.701180Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:09:09.701180Z digest=sha256:56805ba376745b725b61b155e302aedcf58402901b5b23e3dba8ba70e6d9d7fd

Observation 4ba0e51a-3a24-43a1-a20c-9cccf4b082c0 · outbound

This paper cites ThinK: Thinner Key Cache by Query-Driven Pruning.

EffiVLM-BENCH: A Comprehensive Benchmark for Evaluating Training-Free Acceleration in Large Vision-Language Models ThinK: Thinner Key Cache by Query-Driven Pruning

Reference 65

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no resolver link, observed 2026-08-07T12:09:09.833693Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:09:09.833693Z digest=sha256:e800ba5b6fb0b378c48d4ffdbaad7903a819b514aa6b2a8101780be28c15ab44

Observation 2420936d-638a-4630-8d16-5e4ab2adae8c · outbound

This paper cites an unresolved cited work.

EffiVLM-BENCH: A Comprehensive Benchmark for Evaluating Training-Free Acceleration in Large Vision-Language Models Unresolved cited work

Reference 66

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no resolver link, observed 2026-08-07T12:09:09.933170Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:09:09.933170Z digest=sha256:fb92f0c111afd1a33d3db8bb991c4dff296766c88c713332ed92fcce8202717a

Observation cd372c72-0a39-4af6-b4f3-f4bd6e731079 · outbound

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

EffiVLM-BENCH: A Comprehensive Benchmark for Evaluating Training-Free Acceleration in Large Vision-Language Models MiniCPM-V: A GPT-4V Level MLLM on Your Phone

Reference 67

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no resolver link, observed 2026-08-07T12:09:10.058321Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:09:10.058321Z digest=sha256:fc56d36eb87ea176d9b2b376c23035117574ddf47ea4b49c58c1a3d0f9b751cc

Observation d3466021-9e02-4e90-a8f3-43e92a6c9323 · outbound

This paper cites MQuant: Unleashing the Inference Potential of Multimodal Large Language Models via Full Static Quantization.

EffiVLM-BENCH: A Comprehensive Benchmark for Evaluating Training-Free Acceleration in Large Vision-Language Models MQuant: Unleashing the Inference Potential of Multimodal Large Language Models via Full Static Quantization

Reference 68

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no resolver link, observed 2026-08-07T12:09:10.222780Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:09:10.222780Z digest=sha256:f5cb2c6e0cc694d031a156610619f95b12115084b6217231154dd332acc6241c

Observation cb5ab091-1f00-4d56-95e7-a340c096b845 · outbound

This paper cites MM-Vet: Evaluating Large Multimodal Models for Integrated Capabilities.

EffiVLM-BENCH: A Comprehensive Benchmark for Evaluating Training-Free Acceleration in Large Vision-Language Models MM-Vet: Evaluating Large Multimodal Models for Integrated Capabilities

Reference 69

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no resolver link, observed 2026-08-07T12:09:10.352718Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:09:10.352718Z digest=sha256:089f1dac609bc32e95109e8262f1356f7605cf8ea5eb78a65beb02b4e99bbc43

Observation 0716cfb9-65bc-4e23-b196-aee7c58bf29d · outbound

This paper cites an unresolved cited work.

EffiVLM-BENCH: A Comprehensive Benchmark for Evaluating Training-Free Acceleration in Large Vision-Language Models Unresolved cited work

Reference 70

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unresolved
raw_fallback, observed 2026-08-07T12:09:12.700814Z

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=2026-08-07T12:09:10.533866Z digest=sha256:a737c7db4710513048714a8028701b709853b72a1a3ca96fa414598c8566a3a6

Observation f780789c-d041-484f-bd98-f944e3e6b659 · outbound

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

EffiVLM-BENCH: A Comprehensive Benchmark for Evaluating Training-Free Acceleration in Large Vision-Language Models LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models

Reference 71

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unresolved
no resolver link, observed 2026-08-07T12:09:10.660378Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:09:10.660378Z digest=sha256:f2e069dd32c2599ace8322d3a57b78b33ee51fc572bd88ea4790c80b37e6d710

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This paper cites SparseVLM: Visual Token Sparsification for Efficient Vision-Language Model Inference.

EffiVLM-BENCH: A Comprehensive Benchmark for Evaluating Training-Free Acceleration in Large Vision-Language Models SparseVLM: Visual Token Sparsification for Efficient Vision-Language Model Inference

Reference 72

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EffiVLM-BENCH: A Comprehensive Benchmark for Evaluating Training-Free Acceleration in Large Vision-Language Models Unresolved cited work

Reference 73

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This paper cites an unresolved cited work.

EffiVLM-BENCH: A Comprehensive Benchmark for Evaluating Training-Free Acceleration in Large Vision-Language Models Unresolved cited work

Reference 74

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Observation aad67730-e1de-47b9-a1a6-e10607ef4bdf · outbound

This paper cites TinyLLaVA: A Framework of Small-scale Large Multimodal Models.

EffiVLM-BENCH: A Comprehensive Benchmark for Evaluating Training-Free Acceleration in Large Vision-Language Models TinyLLaVA: A Framework of Small-scale Large Multimodal Models

Reference 75

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EffiVLM-BENCH: A Comprehensive Benchmark for Evaluating Training-Free Acceleration in Large Vision-Language Models online" 'onlinestring :=

Reference 76

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Observation 898f31ce-4c8e-42e4-9173-a1ae1186bb00 · outbound

This paper cites write newline.

EffiVLM-BENCH: A Comprehensive Benchmark for Evaluating Training-Free Acceleration in Large Vision-Language Models write newline

Reference 77

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Pith citing papers

No inbound Pith citation observations are available.