Paper Citation Record · LEDGER

AIM: Adaptive Inference of Multi-Modal LLMs via Token Merging and Pruning

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2412.03248.

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

pith.paper-citation-record.v1
2412.03248 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 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 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:15:12.434364Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T10:41:03.999598Z

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 f61d0b3a-33cc-4d09-9490-858863c934ec · inbound

Streamline Without Sacrifice -- Squeeze out Computation Redundancy in LMM cites this paper.

Streamline Without Sacrifice -- Squeeze out Computation Redundancy in LMM AIM: Adaptive Inference of Multi-Modal LLMs via Token Merging and Pruning

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-07T15:15:12.434364Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4ed619fe-2182-414b-afff-bd1a1ca8dd69 · inbound

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

AdaTP: Attention-Debiased Token Pruning for Video Large Language Models AIM: Adaptive Inference of Multi-Modal LLMs via Token Merging and Pruning

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-07T14:08:10.915558Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b344fd13-b7d1-46a2-af72-80b526c10748 · inbound

Fast3D: Accelerating 3D Multi-modal Large Language Models for Efficient 3D Scene Understanding cites this paper.

Fast3D: Accelerating 3D Multi-modal Large Language Models for Efficient 3D Scene Understanding AIM: Adaptive Inference of Multi-Modal LLMs via Token Merging and Pruning

Reference 84

Resolution: unresolved; no resolver link, observed 2026-08-06T18:03:03.555597Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7d65a803-0200-4e6b-aa91-044e0e65175b · inbound

METEOR: Multi-Encoder Collaborative Token Pruning for Efficient Vision Language Models cites this paper.

METEOR: Multi-Encoder Collaborative Token Pruning for Efficient Vision Language Models AIM: Adaptive Inference of Multi-Modal LLMs via Token Merging and Pruning

Reference 81

Resolution: unresolved; no resolver link, observed 2026-08-06T13:18:06.370053Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6074cee1-1481-471e-9de5-4e6c03422122 · inbound

Efficient Inference for Large Vision-Language Models: Bottlenecks, Techniques, and Prospects cites this paper.

Efficient Inference for Large Vision-Language Models: Bottlenecks, Techniques, and Prospects AIM: Adaptive Inference of Multi-Modal LLMs via Token Merging and Pruning

Reference 13

Resolution: metadata mismatch; arxiv_id, observed 2026-05-10T23:45:50.915833Z

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 1228267b-abf2-44b3-99d4-d9c23b22df29 · inbound

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

POINTS-Long: Adaptive Dual-Mode Visual Reasoning in MLLMs AIM: Adaptive Inference of Multi-Modal LLMs via Token Merging and Pruning

Reference 122

Resolution: verified exact; arxiv_id, observed 2026-05-11T10:41:04.005982Z

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.