Paper Citation Record · LEDGER

LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models

As of 11 August 2026, this Paper Citation Record lists 24 of 24 outbound references and 76 inbound Pith citation observations for arXiv:2407.12772.

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

pith.paper-citation-record.v1
2407.12772 v2

Coverage vector

measured 24 of 24 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-17T05:19:22.423762Z

measured 100 of 100 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 76 of 76 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T21:34:35.657096Z

measured 1 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T02:28:24.338817Z

Reference resolution

24 of 24 outbound references displayed

verified exact0
verified fuzzy11
unresolved6
parse uncertain0
malformed identifier0
metadata mismatch7

External citation measurements

1
pith, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation 41a065a0-33ba-4505-96d7-c12348c473d8 · outbound

This paper cites InstructBLIP: Towards General-purpose Vision-Language Models with Instruction Tuning.

LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models InstructBLIP: Towards General-purpose Vision-Language Models with Instruction Tuning

Reference 1

Resolution: metadata mismatch; local_arxiv, observed 2026-05-17T05:19:22.442626Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation ac237b95-9dcc-430d-8a2e-a64a6f60f2d4 · outbound

This paper cites InternLM-XComposer2-4KHD: A Pioneering Large Vision-Language Model Handling Resolutions from 336 Pixels to 4K HD.

LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models InternLM-XComposer2-4KHD: A Pioneering Large Vision-Language Model Handling Resolutions from 336 Pixels to 4K HD

Reference 2

Resolution: metadata mismatch; arxiv_id, observed 2026-05-17T05:19:22.446753Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 4eaf4965-7af9-469c-bf9b-d742213b2150 · outbound

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

LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models MME: A Comprehensive Evaluation Benchmark for Multimodal Large Language Models

Reference 3

Resolution: metadata mismatch; local_arxiv, observed 2026-05-17T05:19:22.453887Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 46622577-559c-4ea9-afda-31666510f829 · outbound

This paper cites Making LLaMA SEE and Draw with SEED Tokenizer.

LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models Making LLaMA SEE and Draw with SEED Tokenizer

Reference 4

Resolution: metadata mismatch; arxiv_id, observed 2026-05-17T05:19:22.459326Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 61f9941a-f4a7-4bd6-99a1-144fd10c0c72 · outbound

This paper cites A Diagram Is Worth A Dozen Images.

LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models A Diagram Is Worth A Dozen Images

Reference 5

Resolution: metadata mismatch; local_arxiv, observed 2026-05-17T05:19:22.463601Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation da6a5df2-38fc-4d4c-9498-99235737c321 · outbound

This paper cites Coresets for Data-efficient Training of Machine Learning Models.

LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models Coresets for Data-efficient Training of Machine Learning Models

Reference 6

Resolution: metadata mismatch; arxiv_id, observed 2026-05-17T05:19:22.468240Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation a858ae38-1d42-40f8-a4b0-022b15c8c58e · outbound

This paper cites tinyBenchmarks: evaluating LLMs with fewer examples.

LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models tinyBenchmarks: evaluating LLMs with fewer examples

Reference 7

Resolution: metadata mismatch; arxiv_id, observed 2026-05-17T05:19:22.473153Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 99525b92-fa84-4b7b-b28d-7c7188b2ea32 · outbound

This paper cites What are the key points in this news story?.

LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models What are the key points in this news story?

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:19:22.476018Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation f0f44743-f5e5-43c0-8f27-41cc25480f27 · outbound

This paper cites What are the factors that led to this event?.

LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models What are the factors that led to this event?

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:19:22.478515Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 3a96d9ad-e6f5-4fc5-b812-2740fede8ed1 · outbound

This paper cites How could you create a new headline that captures the essence of the event differently?.

LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models How could you create a new headline that captures the essence of the event differently?

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:19:22.481198Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 93846a10-9fcd-4507-87b2-4941b3b630a5 · outbound

This paper cites Please present this news in Arabic and output it in markdown format.

LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models Please present this news in Arabic and output it in markdown format

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:19:22.483602Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation c2f125d4-5c36-471f-a3ce-7f7e6e922df5 · outbound

This paper cites an unresolved cited work.

LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models Unresolved cited work

Reference 12

Resolution: unresolved; raw_fallback, observed 2026-05-17T05:19:22.485651Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 407d8bbd-82cb-46f0-b4c0-b6721acb82b8 · outbound

This paper cites However, you should not change the original question's subtask unless the original subtask is not one of these five.

LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models However, you should not change the original question's subtask unless the original subtask is not one of these five

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:19:22.488064Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 5fd5be42-25f9-49ad-9ba7-988414396e6c · outbound

This paper cites an unresolved cited work.

LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models Unresolved cited work

Reference 14

Resolution: unresolved; raw_fallback, observed 2026-05-17T05:19:22.489979Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 97641f0d-0d6d-48e0-9837-50841ceb6d36 · outbound

This paper cites But don't use python−like format.

LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models But don't use python−like format

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:19:22.491916Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation b1524ccc-abb8-46ab-90db-695baa3ae091 · outbound

This paper cites an unresolved cited work.

LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models Unresolved cited work

Reference 16

Resolution: unresolved; raw_fallback, observed 2026-05-17T05:19:22.494384Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 9c4ebe4c-e8df-49a9-9a55-24e8c8704085 · outbound

This paper cites But if you think some words should be in other language, you can keep it in that language.

LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models But if you think some words should be in other language, you can keep it in that language

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:19:22.497093Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation afde4456-461d-4bb1-bd93-9931c860ad57 · outbound

This paper cites an unresolved cited work.

LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models Unresolved cited work

Reference 18

Resolution: unresolved; raw_fallback, observed 2026-05-17T05:19:22.499178Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 38f1f065-e613-4cca-8aef-84769a6ff0c5 · outbound

This paper cites an unresolved cited work.

LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models Unresolved cited work

Reference 19

Resolution: unresolved; raw_fallback, observed 2026-05-17T05:19:22.502067Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 085a2ac6-cff5-4219-98d2-f4d184ffc838 · outbound

This paper cites an unresolved cited work.

LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models Unresolved cited work

Reference 20

Resolution: unresolved; raw_fallback, observed 2026-05-17T05:19:22.504065Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation bda072aa-ad67-4127-b2c9-a50814044507 · outbound

This paper cites Some tips.

LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models Some tips

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:19:22.506116Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation e406d34c-a761-4cdd-82ff-faf783f8f100 · outbound

This paper cites In such cases, you can relax the criteria slightly.

LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models In such cases, you can relax the criteria slightly

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:19:22.508398Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 6762720f-b6fc-4931-9d4f-e91c876f3a3c · outbound

This paper cites Explanation.

LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models Explanation

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:19:22.510562Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 68a4ab78-6909-40d3-9419-bd66816e0b28 · outbound

This paper cites This kind of systemic shift often results in skills becoming obsolete, leading to higher unemployment among professionals who cannot quickly adapt to new technological paradigms.

LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models This kind of systemic shift often results in skills becoming obsolete, leading to higher unemployment among professionals who cannot quickly adapt to new technological paradigms

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:19:22.512802Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Pith citing papers

Observation edaf3815-d97d-40ae-83b6-143507c5c40f · inbound

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

LLaVA-OneVision: Easy Visual Task Transfer LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models

Reference 161

Resolution: verified exact; arxiv_id, observed 2026-05-17T05:19:22.513527Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation fcf13dd4-e536-4b33-b2be-418a60ae91cd · inbound

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

LLaVA-Video: Video Instruction Tuning With Synthetic Data LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models

Reference 165

Resolution: metadata mismatch; arxiv_id, observed 2026-05-17T05:19:22.513527Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 7f8d7f30-ef47-4ce8-b292-ded9b4ed6754 · inbound

Thinking in Space: How Multimodal Large Language Models See, Remember, and Recall Spaces cites this paper.

Thinking in Space: How Multimodal Large Language Models See, Remember, and Recall Spaces LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models

Reference 100

Resolution: verified exact; local_arxiv, observed 2026-05-22T09:27:44.058528Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 31d738d5-6381-4128-8300-1446b21f4267 · inbound

Feedback-Driven Vision-Language Alignment with Minimal Human Supervision cites this paper.

Feedback-Driven Vision-Language Alignment with Minimal Human Supervision LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models

Reference 113

Resolution: unresolved; no resolver link, observed 2026-08-10T21:34:35.657096Z

Source-reported events for the cited work

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Observation 86ea2dec-3ff0-4369-8491-984c2e3211bb · inbound

Advancing General Multimodal Capability of Vision-language Models with Pyramid-descent Visual Position Encoding cites this paper.

Advancing General Multimodal Capability of Vision-language Models with Pyramid-descent Visual Position Encoding LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-10T18:53:21.329427Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8525a6ab-88cd-4869-90a4-a9bd1a23a7bd · inbound

Video-MMMU: Evaluating Knowledge Acquisition from Multi-Discipline Professional Videos cites this paper.

Video-MMMU: Evaluating Knowledge Acquisition from Multi-Discipline Professional Videos LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models

Reference 47

Resolution: verified exact; arxiv_id, observed 2026-05-17T05:19:22.513527Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 5b9854d1-d8a6-4e5e-b9a3-3af0b15ddcbb · inbound

Temporal Preference Optimization for Long-Form Video Understanding cites this paper.

Temporal Preference Optimization for Long-Form Video Understanding LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-10T15:35:30.301738Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 22a8c01b-60d0-4d79-9f99-e02db2c23309 · inbound

Mordal: Automated Pretrained Model Selection for Vision Language Models cites this paper.

Mordal: Automated Pretrained Model Selection for Vision Language Models LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-09T19:46:19.974377Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6dde0cbd-6c00-4a84-a005-0ae1a1f197c0 · inbound

EVEv2: Improved Baselines for Encoder-Free Vision-Language Models cites this paper.

EVEv2: Improved Baselines for Encoder-Free Vision-Language Models LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models

Reference 100

Resolution: unresolved; no resolver link, observed 2026-08-08T14:25:56.014437Z

Source-reported events for the cited work

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Observation ace4d7a1-6410-4a39-b4fc-15bec714d7f4 · inbound

From Visuals to Vocabulary: Establishing Equivalence Between Image and Text Token Through Autoregressive Pre-training in MLLMs cites this paper.

From Visuals to Vocabulary: Establishing Equivalence Between Image and Text Token Through Autoregressive Pre-training in MLLMs LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-07T22:43:59.496502Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c1624128-ec7a-482d-8661-7f01e487293e · inbound

Granite Vision: a lightweight, open-source multimodal model for enterprise Intelligence cites this paper.

Granite Vision: a lightweight, open-source multimodal model for enterprise Intelligence LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models

Reference 103

Resolution: unresolved; no resolver link, observed 2026-08-07T20:06:00.974895Z

Source-reported events for the cited work

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Observation 9959d856-1575-44aa-aef0-cd26b4beca69 · inbound

LMM-R1: Empowering 3B LMMs with Strong Reasoning Abilities Through Two-Stage Rule-Based RL cites this paper.

LMM-R1: Empowering 3B LMMs with Strong Reasoning Abilities Through Two-Stage Rule-Based RL LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models

Reference 91

Resolution: verified exact; arxiv_id, observed 2026-05-17T05:19:22.513527Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation cdfe6a61-b8c6-4b66-8526-ef453138e929 · inbound

Clapper: Compact Learning and Video Representation in VLMs cites this paper.

Clapper: Compact Learning and Video Representation in VLMs LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models

Reference 39

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Source-reported events for the cited work

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Observation a1a68158-024f-4428-8b46-b41501f1b8a0 · inbound

QuickVideo: Real-Time Long Video Understanding with System Algorithm Co-Design cites this paper.

QuickVideo: Real-Time Long Video Understanding with System Algorithm Co-Design LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models

Reference 44

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 541fab43-345b-4c5e-af52-0c0dcbfe5899 · inbound

LLaDA-V: Large Language Diffusion Models with Visual Instruction Tuning cites this paper.

LLaDA-V: Large Language Diffusion Models with Visual Instruction Tuning LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models

Reference 112

Resolution: verified exact; arxiv_id, observed 2026-05-17T05:19:22.513527Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 665b20c0-642a-4749-adce-bb09dbca8641 · inbound

Inference Compute-Optimal Video Vision Language Models cites this paper.

Inference Compute-Optimal Video Vision Language Models LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-07T14:27:45.026613Z

Source-reported events for the cited work

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

AdaTP: Attention-Debiased Token Pruning for Video Large Language Models cites this paper.

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

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-07T14:08:10.490334Z

Source-reported events for the cited work

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Observation b4a2bfdf-d0be-4e4b-bf84-6059ee7d55e2 · inbound

ID-Align: RoPE-Conscious Position Remapping for Dynamic High-Resolution Adaptation in Vision-Language Models cites this paper.

ID-Align: RoPE-Conscious Position Remapping for Dynamic High-Resolution Adaptation in Vision-Language Models LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-07T13:33:58.047950Z

Source-reported events for the cited work

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Observation 154b2e67-dfd9-49d3-8247-306637013fb2 · inbound

Fostering Video Reasoning via Next-Event Prediction cites this paper.

Fostering Video Reasoning via Next-Event Prediction LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-07T13:10:45.965589Z

Source-reported events for the cited work

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Observation c1de9b23-f463-4c5c-a580-d41614ee40de · inbound

Spoken question answering for visual queries cites this paper.

Spoken question answering for visual queries LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models

Reference 48

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Source-reported events for the cited work

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Observation cb348a27-c885-4a0a-9667-9fb0ed96adda · inbound

Mixed-R1: Unified Reward Perspective For Reasoning Capability in Multimodal Large Language Models cites this paper.

Mixed-R1: Unified Reward Perspective For Reasoning Capability in Multimodal Large Language Models LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models

Reference 71

Resolution: unresolved; no resolver link, observed 2026-08-07T12:37:50.123928Z

Source-reported events for the cited work

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Observation 743b0234-2b6f-4c89-a45c-ca3607796007 · inbound

MoDoMoDo: Multi-Domain Data Mixtures for Multimodal LLM Reinforcement Learning cites this paper.

MoDoMoDo: Multi-Domain Data Mixtures for Multimodal LLM Reinforcement Learning LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models

Reference 73

Resolution: unresolved; no resolver link, observed 2026-08-07T12:19:33.786626Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

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

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

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

Source-reported events for the cited work

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Observation 8826dfff-bcbe-4a51-859c-962a6a42fd2b · inbound

FlexSelect: Flexible Token Selection for Efficient Long Video Understanding cites this paper.

FlexSelect: Flexible Token Selection for Efficient Long Video Understanding LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-07T11:59:10.390042Z

Source-reported events for the cited work

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Observation 399f54ee-1809-460e-a0d9-df04827b9876 · inbound

MiMo-VL Technical Report cites this paper.

MiMo-VL Technical Report LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models

Reference 71

Resolution: unresolved; no resolver link, observed 2026-08-07T11:04:14.284762Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 29db3ad9-d287-4e59-8754-7cbb96c444d0 · inbound

DynTok: Dynamic Compression of Visual Tokens for Efficient and Effective Video Understanding cites this paper.

DynTok: Dynamic Compression of Visual Tokens for Efficient and Effective Video Understanding LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-07T10:56:05.407052Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1b5cad25-5993-4d34-a0d1-5e6058d88cee · inbound

VideoMathQA: Benchmarking Mathematical Reasoning via Multimodal Understanding in Videos cites this paper.

VideoMathQA: Benchmarking Mathematical Reasoning via Multimodal Understanding in Videos LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models

Reference 37

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SAVVY: Spatial Awareness via Audio-Visual LLMs through Seeing and Hearing cites this paper.

SAVVY: Spatial Awareness via Audio-Visual LLMs through Seeing and Hearing LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models

Reference 71

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Observation e976c28f-cb3f-4be5-afc5-2c4129af7882 · inbound

Vision-EKIPL: External Knowledge-Infused Policy Learning for Visual Reasoning cites this paper.

Vision-EKIPL: External Knowledge-Infused Policy Learning for Visual Reasoning LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models

Reference 66

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Observation 0b2d9593-f06e-45e2-a843-0a5d394ef7e1 · inbound

FlagEvalMM: A Flexible Framework for Comprehensive Multimodal Model Evaluation cites this paper.

FlagEvalMM: A Flexible Framework for Comprehensive Multimodal Model Evaluation LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models

Reference 47

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Observation 15bd45bc-a1b8-4c77-8dd8-83626e44a128 · inbound

V-JEPA 2: Self-Supervised Video Models Enable Understanding, Prediction and Planning cites this paper.

V-JEPA 2: Self-Supervised Video Models Enable Understanding, Prediction and Planning LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models

Reference 56

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Manager: Aggregating Insights from Unimodal Experts in Two-Tower VLMs and MLLMs cites this paper.

Manager: Aggregating Insights from Unimodal Experts in Two-Tower VLMs and MLLMs LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models

Reference 56

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VGR: Visual Grounded Reasoning cites this paper.

VGR: Visual Grounded Reasoning LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models

Reference 55

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Observation 1805c7fa-a03b-4a40-92f1-0c7d95361a3f · inbound

GreedyPrune: Retenting Critical Visual Token Set for Large Vision Language Models cites this paper.

GreedyPrune: Retenting Critical Visual Token Set for Large Vision Language Models LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models

Reference 47

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Observation ed01f621-792c-4699-afb1-f54e0c1f7f6d · inbound

LaVi: Efficient Large Vision-Language Models via Internal Feature Modulation cites this paper.

LaVi: Efficient Large Vision-Language Models via Internal Feature Modulation LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models

Reference 70

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Observation 3ca77f38-1b04-454e-b51f-3d1e2a2bf5e2 · inbound

MMSearch-R1: Incentivizing LMMs to Search cites this paper.

MMSearch-R1: Incentivizing LMMs to Search LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models

Reference 66

Resolution: verified exact; arxiv_id, observed 2026-05-17T05:19:22.513527Z

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Q-Frame: Query-aware Frame Selection and Multi-Resolution Adaptation for Video-LLMs cites this paper.

Q-Frame: Query-aware Frame Selection and Multi-Resolution Adaptation for Video-LLMs LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models

Reference 36

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VisionThink: Smart and Efficient Vision Language Model via Reinforcement Learning cites this paper.

VisionThink: Smart and Efficient Vision Language Model via Reinforcement Learning LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models

Reference 86

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Observation 20eedbe1-69b8-46a6-adc3-00dd90e4df93 · inbound

EgoPrune: Efficient Token Pruning for Egomotion Video Reasoning in Embodied Agent cites this paper.

EgoPrune: Efficient Token Pruning for Egomotion Video Reasoning in Embodied Agent LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-06T15:38:45.376369Z

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Observation 99f4e4f6-d6ea-447e-b0c2-7f198124978f · inbound

Object-centric Video Question Answering with Visual Grounding and Referring cites this paper.

Object-centric Video Question Answering with Visual Grounding and Referring LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models

Reference 72

Resolution: unresolved; no resolver link, observed 2026-08-06T14:19:39.360265Z

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Observation 932c4614-d28b-4ef2-a0e8-434d0e20d706 · inbound

A Glimpse to Compress: Dynamic Visual Token Pruning for Large Vision-Language Models cites this paper.

A Glimpse to Compress: Dynamic Visual Token Pruning for Large Vision-Language Models LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-06T05:37:35.543694Z

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Fourier Compressor: Frequency-Domain Visual Token Compression for Vision-Language Models cites this paper.

Fourier Compressor: Frequency-Domain Visual Token Compression for Vision-Language Models LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models

Reference 20

Resolution: metadata mismatch; local_arxiv, observed 2026-05-21T22:40:43.085060Z

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Observation 63e2b82f-acc5-4c00-8289-ba68f89b3760 · inbound

Training-free Uncertainty Guidance for Complex Visual Tasks with MLLMs cites this paper.

Training-free Uncertainty Guidance for Complex Visual Tasks with MLLMs LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models

Reference 20

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Observation bf9bcb6f-9776-4003-bce1-4caf79ab00a9 · inbound

CARES: Context-Aware Resolution Selector for VLMs cites this paper.

CARES: Context-Aware Resolution Selector for VLMs LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models

Reference 28

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Observation 28787986-459a-4880-a23e-3f02b73298fa · inbound

Beyond Reasoning Gains: Mitigating General-Capability Forgetting in Large Reasoning Models cites this paper.

Beyond Reasoning Gains: Mitigating General-Capability Forgetting in Large Reasoning Models LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models

Reference 113

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Observation c767cd13-4442-4d46-b57d-9660c9126f67 · inbound

Video Streaming Thinking: VideoLLMs Can Watch and Think Simultaneously cites this paper.

Video Streaming Thinking: VideoLLMs Can Watch and Think Simultaneously LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-02T18:23:40.241140Z

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Observation 7105cd42-cab5-4b37-be49-c3e4845aee6e · inbound

Saliency-R1: Enforcing Interpretable and Faithful Vision-language Reasoning via Saliency-map Alignment Reward cites this paper.

Saliency-R1: Enforcing Interpretable and Faithful Vision-language Reasoning via Saliency-map Alignment Reward LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models

Reference 89

Resolution: verified exact; arxiv_id, observed 2026-05-17T05:19:22.513527Z

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Observation a8e958b3-6d7f-43fb-b5f6-152514e0a3a3 · inbound

Q-Zoom: Query-Aware Adaptive Perception for Efficient Multimodal Large Language Models cites this paper.

Q-Zoom: Query-Aware Adaptive Perception for Efficient Multimodal Large Language Models LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models

Reference 75

Resolution: verified exact; arxiv_id, observed 2026-05-17T05:19:22.513527Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 021f215b-5ac0-45ff-8bbe-e86e3050de45 · inbound

POINTS-Long: Adaptive Dual-Mode Visual Reasoning in MLLMs cites this paper.

POINTS-Long: Adaptive Dual-Mode Visual Reasoning in MLLMs LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models

Reference 113

Resolution: verified exact; arxiv_id, observed 2026-05-17T05:19:22.513527Z

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Observation 2b15b9c2-f787-4df8-89e7-779273ebab8d · inbound

Latent Denoising Improves Visual Alignment in Large Multimodal Models cites this paper.

Latent Denoising Improves Visual Alignment in Large Multimodal Models LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models

Reference 98

Resolution: metadata mismatch; arxiv_id, observed 2026-05-17T05:19:22.513527Z

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Observation 26688c78-7c09-4b62-989d-fbb5ea9ea4f3 · inbound

Make Your LVLM KV Cache More Lightweight cites this paper.

Make Your LVLM KV Cache More Lightweight LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models

Reference 104

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Observation bf4e9218-4dad-4245-9199-d5f63af42156 · inbound

MACS: Modality-Aware Capacity Scaling for Efficient Multimodal MoE Inference cites this paper.

MACS: Modality-Aware Capacity Scaling for Efficient Multimodal MoE Inference LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models

Reference 40

Resolution: metadata mismatch; arxiv_id, observed 2026-05-17T05:19:22.513527Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation cf12b96f-50c3-4149-9f93-35282714eba7 · inbound

TTF: Temporal Token Fusion for Efficient Video-Language Model cites this paper.

TTF: Temporal Token Fusion for Efficient Video-Language Model LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models

Reference 18

Resolution: verified exact; arxiv_id, observed 2026-05-17T05:19:22.513527Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation b425d45b-25d9-4bef-9270-e7c6144f21a2 · inbound

Make Each Token Count: Towards Improving Long-Context Performance with KV Cache Eviction cites this paper.

Make Each Token Count: Towards Improving Long-Context Performance with KV Cache Eviction LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models

Reference 33

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LDDR: Linear-DPP-Based Dynamic-Resolution Frame Sampling for Video MLLMs cites this paper.

LDDR: Linear-DPP-Based Dynamic-Resolution Frame Sampling for Video MLLMs LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models

Reference 43

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Mitigating Mask Prior Drift and Positional Attention Collapse in Large Diffusion Vision-Language Models cites this paper.

Mitigating Mask Prior Drift and Positional Attention Collapse in Large Diffusion Vision-Language Models LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models

Reference 24

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Observation e017fd1d-6aff-4637-954b-26390dba5d66 · inbound

Mitigating Mask Prior Drift and Positional Attention Collapse in Large Diffusion Vision-Language Models cites this paper.

Mitigating Mask Prior Drift and Positional Attention Collapse in Large Diffusion Vision-Language Models LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models

Reference 24

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HEED: Density-Weighted Residual Alignment for Hybrid Vision-Language Model Distillation cites this paper.

HEED: Density-Weighted Residual Alignment for Hybrid Vision-Language Model Distillation LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models

Reference 48

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MGVQ: Synergizing Multi-dimensional Sensitivity-Aware and Gradient-Hessian Fusion for Vector Quantization cites this paper.

MGVQ: Synergizing Multi-dimensional Sensitivity-Aware and Gradient-Hessian Fusion for Vector Quantization LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models

Reference 16

Resolution: metadata mismatch; local_arxiv, observed 2026-07-01T15:05:48.308600Z

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EarlyTom: Early Token Compression Completes Fast Video Understanding cites this paper.

EarlyTom: Early Token Compression Completes Fast Video Understanding LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models

Reference 48

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation b0d9029e-a6ab-4bb5-8edb-ee27f65f0453 · inbound

Constitutional On-Policy Safe Distillation cites this paper.

Constitutional On-Policy Safe Distillation LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models

Reference 50

Resolution: verified exact; local_arxiv, observed 2026-07-02T01:36:25.475965Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation b0c5ba65-a2a4-4f37-85f6-555d4489fb76 · inbound

Benchmarking Visual State Tracking in Multimodal Video Understanding cites this paper.

Benchmarking Visual State Tracking in Multimodal Video Understanding LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models

Reference 62

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Observation 25dea9a0-2b8d-43d4-bc26-20d6e5324640 · inbound

Closed-Form Spectral Regularization for Multi-Task Model Merging cites this paper.

Closed-Form Spectral Regularization for Multi-Task Model Merging LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models

Reference 33

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Observation f58c7104-7043-41d5-b609-a74fcb6bb294 · inbound

AlloSpatial: Agentic Harness Framework for Spatial Reasoning in Foundation Models cites this paper.

AlloSpatial: Agentic Harness Framework for Spatial Reasoning in Foundation Models LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models

Reference 44

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Source-reported events for the cited work

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Embodied-R1.5: Evolving Physical Intelligence via Embodied Foundation Models cites this paper.

Embodied-R1.5: Evolving Physical Intelligence via Embodied Foundation Models LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models

Reference 110

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Natural-Language Temporal Grounding in Hour-Long Videos is a Search Problem: A Benchmark and Empirical Decomposition cites this paper.

Natural-Language Temporal Grounding in Hour-Long Videos is a Search Problem: A Benchmark and Empirical Decomposition LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models

Reference 29

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Source-reported events for the cited work

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Observation d84ed359-c4f1-4ecf-b189-b9f9f51441fe · inbound

DeepInsight: A Unified Evaluation Infrastructure Across the Physical AI Stack cites this paper.

DeepInsight: A Unified Evaluation Infrastructure Across the Physical AI Stack LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models

Reference 23

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Continuous Audio Thinking for Large Audio Language Models cites this paper.

Continuous Audio Thinking for Large Audio Language Models LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models

Reference 61

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Source-reported events for the cited work

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Observation 9dade975-ceed-40d6-bbad-1505b43310fe · inbound

Spectral Query-Key Product Weight Steering for Training-Free VLM Hallucination Mitigation cites this paper.

Spectral Query-Key Product Weight Steering for Training-Free VLM Hallucination Mitigation LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models

Reference 20

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Source-reported events for the cited work

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Observation f951c9da-9086-4aab-ad72-8ca7c16096a0 · inbound

Combating Textual Noise and Redundancy: Entropy-Aware Dense Visual Token Pruning cites this paper.

Combating Textual Noise and Redundancy: Entropy-Aware Dense Visual Token Pruning LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models

Reference 71

Resolution: verified exact; local_arxiv, observed 2026-07-03T14:48:32.411859Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation cc30a3b0-f8c9-4a67-a617-7fb151d37661 · inbound

MentalThink: Shaping Thoughts in Mental SVG World cites this paper.

MentalThink: Shaping Thoughts in Mental SVG World LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models

Reference 163

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Observation a9d82b80-c7ac-41c8-8d1e-595ae626c567 · inbound

TimeThink: Reasoning with Time for Video LLMs cites this paper.

TimeThink: Reasoning with Time for Video LLMs LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models

Reference 64

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Observation ff51fd54-0a23-4d99-b4b1-10d00fe0095c · inbound

SigLIP-HD by Fine-to-Coarse Supervision cites this paper.

SigLIP-HD by Fine-to-Coarse Supervision LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models

Reference 63

Resolution: unresolved; no resolver link, observed 2026-07-13T02:39:58.984385Z

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Unavailable: canonical work link unavailable.

Observation 5c055d66-f9a4-428b-9b63-1a7351e0fd91 · inbound

MIRROR: Learning from the Other View for Multi-Modal Reasoning cites this paper.

MIRROR: Learning from the Other View for Multi-Modal Reasoning LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-01T07:15:04.870137Z

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MM-ShiftKV: Decode-Aware Prefill-Stage KV Selection for Multimodal Large Language Models cites this paper.

MM-ShiftKV: Decode-Aware Prefill-Stage KV Selection for Multimodal Large Language Models LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models

Reference 91

Resolution: unresolved; no resolver link, observed 2026-08-02T11:58:31.210800Z

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Unavailable: canonical work link unavailable.

Observation 6b8813a0-05ca-4779-8278-e01d2d41057c · inbound

Allocation Before Ranking: Decoupled Token Compression for OmniLLMs cites this paper.

Allocation Before Ranking: Decoupled Token Compression for OmniLLMs LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-04T23:23:38.908542Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.