Paper Citation Record · LEDGER

Q-VLM: Post-training Quantization for Large Vision-Language Models

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2410.08119.

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

pith.paper-citation-record.v1
2410.08119 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 8 of 8 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:42:55.672801Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T22:57:26.724266Z

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 f5c3e04f-90a1-43b1-a083-a396502bbb87 · inbound

Speculative Decoding Reimagined for Multimodal Large Language Models cites this paper.

Speculative Decoding Reimagined for Multimodal Large Language Models Q-VLM: Post-training Quantization for Large Vision-Language Models

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-07T15:42:55.672801Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 020eefa4-efc6-4314-98b0-eeba14e171a4 · inbound

LaViDa: A Large Diffusion Language Model for Multimodal Understanding cites this paper.

LaViDa: A Large Diffusion Language Model for Multimodal Understanding Q-VLM: Post-training Quantization for Large Vision-Language Models

Reference 72

Resolution: unresolved; no resolver link, observed 2026-08-07T14:59:39.130706Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 76d86c79-9ba3-471e-ae7f-c9e467fe44df · inbound

LatentLLM: Attention-Aware Joint Tensor Compression cites this paper.

LatentLLM: Attention-Aware Joint Tensor Compression Q-VLM: Post-training Quantization for Large Vision-Language Models

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-07T14:36:28.109772Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aee252e7-274c-4e48-941a-fc682c41b9f7 · inbound

$\mu$-MoE: Test-Time Pruning as Micro-Grained Mixture-of-Experts cites this paper.

$\mu$-MoE: Test-Time Pruning as Micro-Grained Mixture-of-Experts Q-VLM: Post-training Quantization for Large Vision-Language Models

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-07T14:34:13.953373Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b76430f5-4070-4091-84cc-98b50871b9f6 · inbound

WSVD: Weighted Low-Rank Approximation for Fast and Efficient Execution of Low-Precision Vision-Language Models cites this paper.

WSVD: Weighted Low-Rank Approximation for Fast and Efficient Execution of Low-Precision Vision-Language Models Q-VLM: Post-training Quantization for Large Vision-Language Models

Reference 15

Resolution: verified exact; arxiv_id, observed 2026-05-13T21:08:18.074897Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 6c988950-fe96-4d7d-ad80-4231688abec3 · inbound

DREAM-S: Speculative Decoding with Searchable Drafting and Target-Aware Refinement for Multimodal Generation cites this paper.

DREAM-S: Speculative Decoding with Searchable Drafting and Target-Aware Refinement for Multimodal Generation Q-VLM: Post-training Quantization for Large Vision-Language Models

Reference 50

Resolution: verified exact; arxiv_id, observed 2026-06-28T19:02:34.641241Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation ab7031a3-1305-4270-89be-63330b925136 · inbound

LASER: Loss-Aware Singular-value Decomposition and Rank Allocation for Efficient Low-Precision Vision-Language Models cites this paper.

LASER: Loss-Aware Singular-value Decomposition and Rank Allocation for Efficient Low-Precision Vision-Language Models Q-VLM: Post-training Quantization for Large Vision-Language Models

Reference 44

Resolution: verified exact; arxiv_id, observed 2026-06-28T19:12:34.656455Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation c570f93a-ff93-4205-b5e8-9e5136aecba5 · inbound

EinSort: Sorting is All We Need for Tensorizing LLM cites this paper.

EinSort: Sorting is All We Need for Tensorizing LLM Q-VLM: Post-training Quantization for Large Vision-Language Models

Reference 83

Resolution: verified exact; arxiv_id, observed 2026-07-02T22:57:26.725735Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.