Paper Citation Record · LEDGER

Beyond Attention or Similarity: Maximizing Conditional Diversity for Token Pruning in MLLMs

As of 14 August 2026, this Paper Citation Record lists 34 of 34 outbound references and 28 inbound Pith citation observations for arXiv:2506.10967.

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

pith.paper-citation-record.v1
2506.10967 v2

Coverage vector

measured 34 of 34 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T04:20:33.522423Z

measured 62 of 62 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 28 of 28 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T12:49:29.556959Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T15:59:57.457886Z

Reference resolution

34 of 34 outbound references displayed

verified exact0
verified fuzzy4
unresolved30
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation d9580dc0-9e63-41c9-860c-842923ee40f6 · outbound

This paper cites DivPrune: Diversity-based Visual Token Pruning for Large Multimodal Models.

Beyond Attention or Similarity: Maximizing Conditional Diversity for Token Pruning in MLLMs DivPrune: Diversity-based Visual Token Pruning for Large Multimodal Models

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-07T04:20:30.500266Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e25074c2-8e0b-46be-a3d5-4b0e7c0947ca · outbound

This paper cites Tri Dao, Dan Fu, Stefano Ermon, Atri Rudra, and Christopher Ré.

Beyond Attention or Similarity: Maximizing Conditional Diversity for Token Pruning in MLLMs Tri Dao, Dan Fu, Stefano Ermon, Atri Rudra, and Christopher Ré

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:20:35.249313Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation bda22afa-70e1-4b24-b976-6ab55fef2e88 · outbound

This paper cites MiniCPM: Unveiling the Potential of Small Language Models with Scalable Training Strategies.

Beyond Attention or Similarity: Maximizing Conditional Diversity for Token Pruning in MLLMs MiniCPM: Unveiling the Potential of Small Language Models with Scalable Training Strategies

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-07T04:20:31.095679Z

Source-reported events for the cited work

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Observation 75faae6a-b724-4b8b-abd7-d58a1dbf889b · outbound

This paper cites Mistral 7B.

Beyond Attention or Similarity: Maximizing Conditional Diversity for Token Pruning in MLLMs Mistral 7B

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-07T04:20:31.290255Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cb6f6bb3-cb43-4549-877f-ce54049d6d93 · outbound

This paper cites A diagram is worth a dozen images.

Beyond Attention or Similarity: Maximizing Conditional Diversity for Token Pruning in MLLMs A diagram is worth a dozen images

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-07T04:20:31.400104Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0b5a60a5-a5be-480d-9837-88bf333bfa83 · outbound

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

Beyond Attention or Similarity: Maximizing Conditional Diversity for Token Pruning in MLLMs Video-LLaVA: Learning United Visual Representation by Alignment Before Projection

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-07T04:20:31.581672Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 880c77ef-a514-40ae-8dac-e2ee90fdcceb · outbound

This paper cites Microsoft coco: Common objects in context.

Beyond Attention or Similarity: Maximizing Conditional Diversity for Token Pruning in MLLMs Microsoft coco: Common objects in context

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:20:34.975202Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 731567cb-7de2-446a-b222-3b662f87a2da · outbound

This paper cites Multi-Stage Vision Token Dropping: Towards Efficient Multimodal Large Language Model.

Beyond Attention or Similarity: Maximizing Conditional Diversity for Token Pruning in MLLMs Multi-Stage Vision Token Dropping: Towards Efficient Multimodal Large Language Model

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-07T04:20:31.753984Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f46ba898-242d-4dcc-a67e-660f1cd1d0a9 · outbound

This paper cites Feast Your Eyes: Mixture-of-Resolution Adaptation for Multimodal Large Language Models.

Beyond Attention or Similarity: Maximizing Conditional Diversity for Token Pruning in MLLMs Feast Your Eyes: Mixture-of-Resolution Adaptation for Multimodal Large Language Models

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-07T04:20:31.837013Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c8783900-4263-4e24-8bf3-dfdd7c03543e · outbound

This paper cites Less is More: A Simple yet Effective Token Reduction Method for Efficient Multi-modal LLMs.

Beyond Attention or Similarity: Maximizing Conditional Diversity for Token Pruning in MLLMs Less is More: A Simple yet Effective Token Reduction Method for Efficient Multi-modal LLMs

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-07T04:20:32.068161Z

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Unavailable: canonical work link unavailable.

Observation 5d13ddfd-0112-46ce-bfb0-8a3a9baa8099 · outbound

This paper cites Gemma: Open Models Based on Gemini Research and Technology.

Beyond Attention or Similarity: Maximizing Conditional Diversity for Token Pruning in MLLMs Gemma: Open Models Based on Gemini Research and Technology

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-07T04:20:32.245624Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b416dba4-3258-4a0e-ae97-07e441622bd0 · outbound

This paper cites LLaMA: Open and Efficient Foundation Language Models.

Beyond Attention or Similarity: Maximizing Conditional Diversity for Token Pruning in MLLMs LLaMA: Open and Efficient Foundation Language Models

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-07T04:20:32.325718Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e2fd1dc9-808b-4d11-be3a-44643dea61ac · outbound

This paper cites Token Pruning in Multimodal Large Language Models: Are We Solving the Right Problem?.

Beyond Attention or Similarity: Maximizing Conditional Diversity for Token Pruning in MLLMs Token Pruning in Multimodal Large Language Models: Are We Solving the Right Problem?

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-07T04:20:32.526592Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5a32adc7-b150-4ae5-b10a-6b9661ed0910 · outbound

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

Beyond Attention or Similarity: Maximizing Conditional Diversity for Token Pruning in MLLMs PyramidDrop: Accelerating Your Large Vision-Language Models via Pyramid Visual Redundancy Reduction

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-07T04:20:32.613673Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c735d4a5-be86-430e-9d94-702ab8595c14 · outbound

This paper cites Qwen2.5 Technical Report.

Beyond Attention or Similarity: Maximizing Conditional Diversity for Token Pruning in MLLMs Qwen2.5 Technical Report

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-07T04:20:32.701129Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation be676b47-8fa3-4528-acab-1b7fa509bc28 · outbound

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

Beyond Attention or Similarity: Maximizing Conditional Diversity for Token Pruning in MLLMs MM-Vet: Evaluating Large Multimodal Models for Integrated Capabilities

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-07T04:20:32.927138Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fc8edb99-3740-495f-8468-1737e9cc18aa · outbound

This paper cites Video-LLaMA: An Instruction-tuned Audio-Visual Language Model for Video Understanding.

Beyond Attention or Similarity: Maximizing Conditional Diversity for Token Pruning in MLLMs Video-LLaMA: An Instruction-tuned Audio-Visual Language Model for Video Understanding

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-07T04:20:33.004390Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 26b7f326-3691-4767-a429-eddfeaa91aef · outbound

This paper cites Long Context Transfer from Language to Vision.

Beyond Attention or Similarity: Maximizing Conditional Diversity for Token Pruning in MLLMs Long Context Transfer from Language to Vision

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-07T04:20:33.079691Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fe9d77f7-1109-4755-be87-518e9ba954a8 · outbound

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

Beyond Attention or Similarity: Maximizing Conditional Diversity for Token Pruning in MLLMs SparseVLM: Visual Token Sparsification for Efficient Vision-Language Model Inference

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-07T04:20:33.148022Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a8344eeb-4409-476e-8514-35f8472891fe · outbound

This paper cites InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Models.

Beyond Attention or Similarity: Maximizing Conditional Diversity for Token Pruning in MLLMs InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Models

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-07T04:20:33.229755Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c2123e3a-1bd5-40af-9385-258fcf6886da · outbound

This paper cites Appendix B provides some details of the experimental setup, including information about model architectures, evaluation benchmarks, comparison methods and implemen- tation.

Beyond Attention or Similarity: Maximizing Conditional Diversity for Token Pruning in MLLMs Appendix B provides some details of the experimental setup, including information about model architectures, evaluation benchmarks, comparison methods and implemen- tation

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:20:34.643823Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation ac6f7c56-d168-4c80-b242-6bc6aaf2d9a3 · outbound

This paper cites Therefore, the greedy algorithm runs in O(nm2) time.

Beyond Attention or Similarity: Maximizing Conditional Diversity for Token Pruning in MLLMs Therefore, the greedy algorithm runs in O(nm2) time

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:20:34.442063Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 82d897ab-868b-4802-9c48-46acc1b2dfde · outbound

This paper cites an unresolved cited work.

Beyond Attention or Similarity: Maximizing Conditional Diversity for Token Pruning in MLLMs Unresolved cited work

Reference 34

Resolution: unresolved; raw_fallback, observed 2026-08-07T04:20:34.277604Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 80118ccd-ae30-4541-b8f9-194c876cf8b5 · outbound

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

Beyond Attention or Similarity: Maximizing Conditional Diversity for Token Pruning in MLLMs ChartQA: A Benchmark for Question Answering about Charts with Visual and Logical Reasoning

Reference 1975

Resolution: unresolved; no resolver link, observed 2026-08-07T04:20:31.906806Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6e0c639a-dbd6-4e51-b060-7be707b167b8 · outbound

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

Beyond Attention or Similarity: Maximizing Conditional Diversity for Token Pruning in MLLMs LLaVA-OneVision: Easy Visual Task Transfer

Reference 2012

Resolution: unresolved; no resolver link, observed 2026-08-07T04:20:31.510710Z

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Unavailable: canonical work link unavailable.

Observation 9b2a4f8a-0bb3-4df5-b1a9-9275074cf3d4 · outbound

This paper cites Qwen Technical Report.

Beyond Attention or Similarity: Maximizing Conditional Diversity for Token Pruning in MLLMs Qwen Technical Report

Reference 2015

Resolution: unresolved; no resolver link, observed 2026-08-07T04:20:30.562632Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9fccbff3-c235-473c-827c-647ccd7a1c5a · outbound

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

Beyond Attention or Similarity: Maximizing Conditional Diversity for Token Pruning in MLLMs Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution

Reference 2017

Resolution: unresolved; no resolver link, observed 2026-08-07T04:20:32.413526Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 38da4126-715b-4717-a507-f8506b4447bf · outbound

This paper cites LongVILA: Scaling Long-Context Visual Language Models for Long Videos.

Beyond Attention or Similarity: Maximizing Conditional Diversity for Token Pruning in MLLMs LongVILA: Scaling Long-Context Visual Language Models for Long Videos

Reference 2018

Resolution: unresolved; no resolver link, observed 2026-08-07T04:20:30.765313Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8e4ee5fe-b3d4-4fb5-864d-64b5088904fe · outbound

This paper cites Similarity-Aware Token Pruning: Your VLM but Faster.

Beyond Attention or Similarity: Maximizing Conditional Diversity for Token Pruning in MLLMs Similarity-Aware Token Pruning: Your VLM but Faster

Reference 2019

Resolution: unresolved; no resolver link, observed 2026-08-07T04:20:31.175344Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2895cc3f-6db3-47f7-999b-8ece88d84bc0 · outbound

This paper cites Llava-prumerge: Adaptive token reduction for efficient large multimodal models.

Beyond Attention or Similarity: Maximizing Conditional Diversity for Token Pruning in MLLMs Llava-prumerge: Adaptive token reduction for efficient large multimodal models

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-07T04:20:31.982439Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b7ffd2ae-9a9a-4e15-bd0c-5f1fa2a75316 · outbound

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

Beyond Attention or Similarity: Maximizing Conditional Diversity for Token Pruning in MLLMs Video-MME: The First-Ever Comprehensive Evaluation Benchmark of Multi-modal LLMs in Video Analysis

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-07T04:20:30.949286Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 480d693e-9f13-40e3-96a6-4f0a64979a92 · outbound

This paper cites Qwen2.5-VL Technical Report.

Beyond Attention or Similarity: Maximizing Conditional Diversity for Token Pruning in MLLMs Qwen2.5-VL Technical Report

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-07T04:20:30.635629Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8c99589e-8e7b-40ab-8eb9-0c9b25a35eea · outbound

This paper cites Mdp3: A training-free approach for list-wise frame selection in video-llms.

Beyond Attention or Similarity: Maximizing Conditional Diversity for Token Pruning in MLLMs Mdp3: A training-free approach for list-wise frame selection in video-llms

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-07T04:20:32.151078Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fd123cd7-c6c9-4391-93fb-7314899df7ac · outbound

This paper cites InternLM2 Technical Report.

Beyond Attention or Similarity: Maximizing Conditional Diversity for Token Pruning in MLLMs InternLM2 Technical Report

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-07T04:20:30.698008Z

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Unavailable: canonical work link unavailable.

Pith citing papers

Observation 00c809f9-844e-4f80-8722-f6bc21ce394c · 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 Beyond Attention or Similarity: Maximizing Conditional Diversity for Token Pruning in MLLMs

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-06T15:38:45.462835Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d6e1b3bf-d94e-4c4b-959d-e59484535d8d · 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 Beyond Attention or Similarity: Maximizing Conditional Diversity for Token Pruning in MLLMs

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-06T05:37:35.450623Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fb5cc1b2-a8b6-494d-ace8-c05441757435 · inbound

Towards Spatial Trace with Reasoning in Vision-Language Models for Robotics cites this paper.

Towards Spatial Trace with Reasoning in Vision-Language Models for Robotics Beyond Attention or Similarity: Maximizing Conditional Diversity for Token Pruning in MLLMs

Reference 122

Resolution: unresolved; no resolver link, observed 2026-08-03T16:27:34.271065Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2867c7e5-692b-4aee-9976-eee272cbf749 · inbound

HAWK: Head Importance-Aware Visual Token Pruning in Multimodal Models cites this paper.

HAWK: Head Importance-Aware Visual Token Pruning in Multimodal Models Beyond Attention or Similarity: Maximizing Conditional Diversity for Token Pruning in MLLMs

Reference 44

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T07:01:05.867186Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation b952a8a0-3d83-4f70-b36c-5b1ea2f0bffe · inbound

Sink-Token-Aware Pruning for Fine-Grained Video Understanding in Efficient Video LLMs cites this paper.

Sink-Token-Aware Pruning for Fine-Grained Video Understanding in Efficient Video LLMs Beyond Attention or Similarity: Maximizing Conditional Diversity for Token Pruning in MLLMs

Reference 52

Resolution: metadata mismatch; arxiv_id, observed 2026-05-10T00:44:48.417048Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 5e597c98-ab8b-4547-8774-cd44bd08c998 · inbound

RTPrune: Reading-Twice Inspired Token Pruning for Efficient DeepSeek-OCR Inference cites this paper.

RTPrune: Reading-Twice Inspired Token Pruning for Efficient DeepSeek-OCR Inference Beyond Attention or Similarity: Maximizing Conditional Diversity for Token Pruning in MLLMs

Reference 5

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T15:31:08.455532Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 23d1383c-d06e-4817-b8b6-88c678f3ea48 · inbound

RTPrune: Reading-Twice Inspired Token Pruning for Efficient DeepSeek-OCR Inference cites this paper.

RTPrune: Reading-Twice Inspired Token Pruning for Efficient DeepSeek-OCR Inference Beyond Attention or Similarity: Maximizing Conditional Diversity for Token Pruning in MLLMs

Reference 19

Resolution: verified exact; arxiv_id, observed 2026-05-12T03:21:19.376132Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 3490a9f9-7ee5-4a16-8cbe-0a9c697dee77 · inbound

RTPrune: Reading-Twice Inspired Token Pruning for Efficient DeepSeek-OCR Inference cites this paper.

RTPrune: Reading-Twice Inspired Token Pruning for Efficient DeepSeek-OCR Inference Beyond Attention or Similarity: Maximizing Conditional Diversity for Token Pruning in MLLMs

Reference 20

Resolution: verified exact; arxiv_id, observed 2026-05-22T10:31:25.772099Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation c50d254f-c09e-4cd1-872d-b44ea1beec21 · inbound

Focus-then-Context: Subject-Centric Progressive Visual Token Reduction for Vision-Language Models cites this paper.

Focus-then-Context: Subject-Centric Progressive Visual Token Reduction for Vision-Language Models Beyond Attention or Similarity: Maximizing Conditional Diversity for Token Pruning in MLLMs

Reference 3

Resolution: metadata mismatch; arxiv_id, observed 2026-05-21T05:23:58.587932Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 70eb3121-3269-4247-8ead-97d6e6805ba0 · inbound

SAFE-Pruner: Semantic Attention-Guided Future-Aware Token Pruning for Efficient Vision-Language-Action Manipulation cites this paper.

SAFE-Pruner: Semantic Attention-Guided Future-Aware Token Pruning for Efficient Vision-Language-Action Manipulation Beyond Attention or Similarity: Maximizing Conditional Diversity for Token Pruning in MLLMs

Reference 47

Resolution: metadata mismatch; arxiv_id, observed 2026-06-29T08:43:14.998270Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation bb008883-066e-4558-af78-5629603e4af6 · inbound

SAFE-Pruner: Semantic Attention-Guided Future-Aware Token Pruning for Efficient Vision-Language-Action Manipulation cites this paper.

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-02T12:54:43.228543Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fda3f518-4f09-46cc-95a7-8aa849d3982e · inbound

X-Stream: Exploring MLLMs as Multiplexers for Multi-Stream Understanding cites this paper.

X-Stream: Exploring MLLMs as Multiplexers for Multi-Stream Understanding Beyond Attention or Similarity: Maximizing Conditional Diversity for Token Pruning in MLLMs

Reference 61

Resolution: metadata mismatch; arxiv_id, observed 2026-07-01T22:46:18.963802Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation edbc6b09-c160-4a09-9a4a-b6b3f11b6fc7 · inbound

X-Stream: Exploring MLLMs as Multiplexers for Multi-Stream Understanding cites this paper.

X-Stream: Exploring MLLMs as Multiplexers for Multi-Stream Understanding Beyond Attention or Similarity: Maximizing Conditional Diversity for Token Pruning in MLLMs

Reference 64

Resolution: metadata mismatch; arxiv_id, observed 2026-06-30T10:44:36.407579Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 722a29f6-c5a9-4c48-847a-f1da057ebcbd · inbound

TGV-KV: Text-Grounded KV Eviction for Vision-Language Models cites this paper.

TGV-KV: Text-Grounded KV Eviction for Vision-Language Models Beyond Attention or Similarity: Maximizing Conditional Diversity for Token Pruning in MLLMs

Reference 24

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T02:16:26.715894Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation e6a61e6e-7b9c-428d-a4cc-5f379bf31ec5 · inbound

Spectral Evolution-Guided Token Pruning in Multimodal Large Language Models cites this paper.

Spectral Evolution-Guided Token Pruning in Multimodal Large Language Models Beyond Attention or Similarity: Maximizing Conditional Diversity for Token Pruning in MLLMs

Reference 86

Resolution: metadata mismatch; arxiv_id, observed 2026-07-04T15:59:57.459369Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 3d777fc8-3027-41a4-9912-24a5f4ce079e · inbound

TOPS: First-Principles Visual Token Pruning via Constructing Token Optimal Preservation Sets for Efficient MLLM Inference cites this paper.

TOPS: First-Principles Visual Token Pruning via Constructing Token Optimal Preservation Sets for Efficient MLLM Inference Beyond Attention or Similarity: Maximizing Conditional Diversity for Token Pruning in MLLMs

Reference 58

Resolution: metadata mismatch; arxiv_id, observed 2026-07-04T14:09:53.798585Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation e7538e8f-8d90-4758-9d8c-e24379874ebc · 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 Beyond Attention or Similarity: Maximizing Conditional Diversity for Token Pruning in MLLMs

Reference 72

Resolution: metadata mismatch; arxiv_id, observed 2026-07-03T14:48:32.406972Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation af6ec779-02cc-4cd9-9823-eff642eca4cb · inbound

RADIO1D: Elastic Representations for Condensed Vision Modeling cites this paper.

RADIO1D: Elastic Representations for Condensed Vision Modeling Beyond Attention or Similarity: Maximizing Conditional Diversity for Token Pruning in MLLMs

Reference 51

Resolution: unresolved; no resolver link, observed 2026-07-12T01:07:20.766474Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f15b7aa2-54f0-49dc-a303-7d5f893e19aa · inbound

IoU-PD: IoU-Aware Privileged Distillation for Visual Grounding with Multimodal Large Language Models cites this paper.

IoU-PD: IoU-Aware Privileged Distillation for Visual Grounding with Multimodal Large Language Models Beyond Attention or Similarity: Maximizing Conditional Diversity for Token Pruning in MLLMs

Reference 76

Resolution: unresolved; no resolver link, observed 2026-08-01T22:32:25.110039Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ab72c83f-49fb-468a-906a-74a8aca1be14 · inbound

IoU-PD: IoU-Aware Privileged Distillation for Visual Grounding with Multimodal Large Language Models cites this paper.

IoU-PD: IoU-Aware Privileged Distillation for Visual Grounding with Multimodal Large Language Models Beyond Attention or Similarity: Maximizing Conditional Diversity for Token Pruning in MLLMs

Reference 76

Resolution: unresolved; no resolver link, observed 2026-08-04T04:21:09.449182Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1d712359-c0ab-48d8-8081-4f12ab56b5ef · inbound

Structured Redundancy Modeling for Efficient Visual Token Pruning in High-Resolution MLLMs cites this paper.

Structured Redundancy Modeling for Efficient Visual Token Pruning in High-Resolution MLLMs Beyond Attention or Similarity: Maximizing Conditional Diversity for Token Pruning in MLLMs

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-01T03:50:32.506198Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 787a3619-c726-44eb-b279-9170356085bd · inbound

WaveZip: Wavelet-Driven Space-Time Decoupling for Video Token Condensation cites this paper.

WaveZip: Wavelet-Driven Space-Time Decoupling for Video Token Condensation Beyond Attention or Similarity: Maximizing Conditional Diversity for Token Pruning in MLLMs

Reference 35

Resolution: unresolved; no resolver link, observed 2026-07-31T23:59:18.339215Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c940e4a4-e27a-4e34-b139-3498d8d14cc3 · inbound

WaveZip: Wavelet-Driven Space-Time Decoupling for Video Token Condensation cites this paper.

WaveZip: Wavelet-Driven Space-Time Decoupling for Video Token Condensation Beyond Attention or Similarity: Maximizing Conditional Diversity for Token Pruning in MLLMs

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-04T04:01:48.622068Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d99230ee-52b9-41a9-911f-f0300818985a · inbound

SepPrune:A Separator-based Pruning Framework for Efficient Multimodal Large Language Models cites this paper.

SepPrune:A Separator-based Pruning Framework for Efficient Multimodal Large Language Models Beyond Attention or Similarity: Maximizing Conditional Diversity for Token Pruning in MLLMs

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-01T01:26:50.833164Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 814f8c48-6d41-4d5d-8183-f3ad966214e2 · inbound

PhyCheck: Fine-Grained Evidence-Grounded Dataset for Physical Law Understanding in Video-LLMs cites this paper.

PhyCheck: Fine-Grained Evidence-Grounded Dataset for Physical Law Understanding in Video-LLMs Beyond Attention or Similarity: Maximizing Conditional Diversity for Token Pruning in MLLMs

Reference 99

Resolution: unresolved; no resolver link, observed 2026-08-04T13:43:57.677655Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b32330f0-3ef6-43b0-a933-40627f1db851 · inbound

PhyCheck: Fine-Grained Evidence-Grounded Dataset for Physical Law Understanding in Video-LLMs cites this paper.

PhyCheck: Fine-Grained Evidence-Grounded Dataset for Physical Law Understanding in Video-LLMs Beyond Attention or Similarity: Maximizing Conditional Diversity for Token Pruning in MLLMs

Reference 99

Resolution: unresolved; no resolver link, observed 2026-08-07T00:11:49.179772Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9355748a-d097-48c7-a5bc-667d093bcbcd · inbound

Hi-Token: Hierarchical Coordinate Tokenization for Generative Visual Grounding cites this paper.

Hi-Token: Hierarchical Coordinate Tokenization for Generative Visual Grounding Beyond Attention or Similarity: Maximizing Conditional Diversity for Token Pruning in MLLMs

Reference 76

Resolution: unresolved; no resolver link, observed 2026-08-05T18:36:14.731592Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0c2c288f-8d7b-460d-98b2-1fa8c38830dd · inbound

Putting Registers to Work: Task Registers for Token Pruning in Vision Transformers cites this paper.

Putting Registers to Work: Task Registers for Token Pruning in Vision Transformers Beyond Attention or Similarity: Maximizing Conditional Diversity for Token Pruning in MLLMs

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-12T12:49:29.556959Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.