Paper Citation Record · LEDGER

FrameFusion: Combining Similarity and Importance for Video Token Reduction on Large Vision Language Models

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 10 inbound Pith citation observations for arXiv:2501.01986.

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

pith.paper-citation-record.v1
2501.01986 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 10 of 10 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 10 of 10 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T10:56:05.308899Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-18T18:36:44.180127Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation a916a4f9-d205-473b-b4f7-13df30d1a489 · 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 FrameFusion: Combining Similarity and Importance for Video Token Reduction on Large Vision Language Models

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-07T10:56:05.308899Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ca7d1ebe-c8c2-49ed-9433-75b741fd4dc1 · inbound

PAROAttention: Pattern-Aware ReOrdering for Efficient Sparse and Quantized Attention in Visual Generation Models cites this paper.

PAROAttention: Pattern-Aware ReOrdering for Efficient Sparse and Quantized Attention in Visual Generation Models FrameFusion: Combining Similarity and Importance for Video Token Reduction on Large Vision Language Models

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-06T23:51:05.316975Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e842939a-c212-4e01-b7fd-dfc93bcc6dee · inbound

Multi-Granular Spatio-Temporal Token Merging for Training-Free Acceleration of Video LLMs cites this paper.

Multi-Granular Spatio-Temporal Token Merging for Training-Free Acceleration of Video LLMs FrameFusion: Combining Similarity and Importance for Video Token Reduction on Large Vision Language Models

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-06T18:32:46.455680Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6c4cd2ce-78b2-4a17-a86d-c31cafcbcdc1 · inbound

Video Parallel Scaling: Aggregating Diverse Frame Subsets for VideoLLMs cites this paper.

Video Parallel Scaling: Aggregating Diverse Frame Subsets for VideoLLMs FrameFusion: Combining Similarity and Importance for Video Token Reduction on Large Vision Language Models

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-05-18T18:36:44.182879Z

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.

Observation f2b099df-6088-4428-8865-d4a635427214 · inbound

Token Reduction via Local and Global Contexts Optimization for Efficient Video Large Language Models cites this paper.

Token Reduction via Local and Global Contexts Optimization for Efficient Video Large Language Models FrameFusion: Combining Similarity and Importance for Video Token Reduction on Large Vision Language Models

Reference 16

Resolution: verified exact; arxiv_id, observed 2026-05-15T18:26:26.952439Z

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.

Observation f1fb8254-03a9-498b-8f29-a67fafa8698c · inbound

ForestPrune: High-ratio Visual Token Compression for Video Multimodal Large Language Models via Spatial-Temporal Forest Modeling cites this paper.

ForestPrune: High-ratio Visual Token Compression for Video Multimodal Large Language Models via Spatial-Temporal Forest Modeling FrameFusion: Combining Similarity and Importance for Video Token Reduction on Large Vision Language Models

Reference 13

Resolution: verified exact; arxiv_id, observed 2026-05-15T00:58:25.578048Z

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.

Observation e751a35f-1465-4842-b509-70896a92690c · inbound

AdaSpark: Adaptive Sparsity for Efficient Long-Video Understanding cites this paper.

AdaSpark: Adaptive Sparsity for Efficient Long-Video Understanding FrameFusion: Combining Similarity and Importance for Video Token Reduction on Large Vision Language Models

Reference 12

Resolution: verified exact; arxiv_id, observed 2026-05-11T06:56:04.303398Z

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.

Observation 283bf54e-4e36-456a-8fb0-281b24c26d04 · inbound

VLMaxxing through FrameMogging Training-Free Anti-Recomputation for Video Vision-Language Models cites this paper.

VLMaxxing through FrameMogging Training-Free Anti-Recomputation for Video Vision-Language Models FrameFusion: Combining Similarity and Importance for Video Token Reduction on Large Vision Language Models

Reference 12

Resolution: verified exact; arxiv_id, observed 2026-05-11T23:11:13.939144Z

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.

Observation d7ea209d-850e-41a8-a95d-ce6317404937 · inbound

OTT-Vid: Optimal Transport Temporal Token Compression for Video Large Language Models cites this paper.

OTT-Vid: Optimal Transport Temporal Token Compression for Video Large Language Models FrameFusion: Combining Similarity and Importance for Video Token Reduction on Large Vision Language Models

Reference 14

Resolution: verified exact; arxiv_id, observed 2026-05-13T05:52:22.314857Z

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.

Observation e387f156-1e65-4a9d-a278-1fd740ff47d1 · inbound

OmniRefine: Alignment-Aware Cooperative Compression for Efficient Omnimodal Large Language Models cites this paper.

OmniRefine: Alignment-Aware Cooperative Compression for Efficient Omnimodal Large Language Models FrameFusion: Combining Similarity and Importance for Video Token Reduction on Large Vision Language Models

Reference 15

Resolution: verified exact; arxiv_id, observed 2026-05-13T04:52:16.246111Z

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.