Paper Citation Record · LEDGER

PruneVid: Visual Token Pruning for Efficient Video Large Language Models

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 11 inbound Pith citation observations for arXiv:2412.16117.

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

pith.paper-citation-record.v1
2412.16117 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 11 of 11 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 11 of 11 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T00:11:49.166898Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-15T19:16:31.884188Z

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 d1096a89-6bc4-4e70-b5cf-9ab2e5fed281 · inbound

LLaVA-Scissor: Token Compression with Semantic Connected Components for Video LLMs cites this paper.

LLaVA-Scissor: Token Compression with Semantic Connected Components for Video LLMs PruneVid: Visual Token Pruning for Efficient Video Large Language Models

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-06T22:24:27.055696Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d544c777-c601-45fb-a23e-d49639e58b38 · 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 PruneVid: Visual Token Pruning for Efficient Video Large Language Models

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-06T18:32:46.995554Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f29c4805-84c0-4a34-92c7-6508dc49d3ec · inbound

MMG-Vid: Maximizing Marginal Gains at Segment-level and Token-level for Efficient Video LLMs cites this paper.

MMG-Vid: Maximizing Marginal Gains at Segment-level and Token-level for Efficient Video LLMs PruneVid: Visual Token Pruning for Efficient Video Large Language Models

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-05T14:41:15.535604Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 747571fc-405e-4119-b757-877208d82e2e · inbound

TrajTok: Learning Trajectory Tokens enables better Video Understanding cites this paper.

TrajTok: Learning Trajectory Tokens enables better Video Understanding PruneVid: Visual Token Pruning for Efficient Video Large Language Models

Reference 25

Resolution: verified exact; arxiv_id, observed 2026-05-15T19:16:31.888882Z

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 59c2e359-e839-46af-bc6a-e64c09bff64c · inbound

TrajTok: Learning Trajectory Tokens enables better Video Understanding cites this paper.

TrajTok: Learning Trajectory Tokens enables better Video Understanding PruneVid: Visual Token Pruning for Efficient Video Large Language Models

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-02T20:38:38.325046Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 352f6555-5169-49e5-ab23-c28f34d52a3b · 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 PruneVid: Visual Token Pruning for Efficient Video Large Language Models

Reference 17

Resolution: verified exact; arxiv_id, observed 2026-05-15T18:26:26.984952Z

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 bf580084-5077-475c-b446-9c4c0ed3c70b · inbound

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

POINTS-Long: Adaptive Dual-Mode Visual Reasoning in MLLMs PruneVid: Visual Token Pruning for Efficient Video Large Language Models

Reference 29

Resolution: verified exact; arxiv_id, observed 2026-05-11T10:41:03.942336Z

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 391ab039-e668-49f0-92e4-cdc6a8d5e4a1 · inbound

Spectral Origins of the Self-Correction Blind Spot in Autoregressive Generation cites this paper.

Spectral Origins of the Self-Correction Blind Spot in Autoregressive Generation PruneVid: Visual Token Pruning for Efficient Video Large Language Models

Reference 8

Resolution: unresolved; no resolver link, observed 2026-07-14T15:30:23.485228Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6037976b-5fc2-4d7c-a168-9c15f12ab2bd · inbound

CRAFT: Compression via Recursive Adaptive Fusion of Video Tokens for Vision-Language Models cites this paper.

CRAFT: Compression via Recursive Adaptive Fusion of Video Tokens for Vision-Language Models PruneVid: Visual Token Pruning for Efficient Video Large Language Models

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-04T23:46:51.557165Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c93e8ec9-6253-41fa-a4c4-35e752a53ea7 · 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 PruneVid: Visual Token Pruning for Efficient Video Large Language Models

Reference 97

Resolution: unresolved; no resolver link, observed 2026-08-04T13:43:57.501524Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d9ce454e-6fdf-4a22-84c6-d681f1f16dce · 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 PruneVid: Visual Token Pruning for Efficient Video Large Language Models

Reference 97

Resolution: unresolved; no resolver link, observed 2026-08-07T00:11:49.166898Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.