Paper Citation Record · LEDGER

GPTAQ: Efficient Finetuning-Free Quantization for Asymmetric Calibration

As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 11 inbound Pith citation observations for arXiv:2504.02692.

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

pith.paper-citation-record.v1
2504.02692 v3

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 2026-08-19T06:32:44.657259+00:00

measured 11 of 11 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T00:26:51.642528Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-10T14:47:14.597664Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
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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 b916734e-53dd-4b04-9cc4-c8e8cc7594cc · inbound

NeUQI: Near-Optimal Uniform Quantization Parameter Initialization for Low-Bit LLMs cites this paper.

NeUQI: Near-Optimal Uniform Quantization Parameter Initialization for Low-Bit LLMs GPTAQ: Efficient Finetuning-Free Quantization for Asymmetric Calibration

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-07T14:50:07.468226Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 28ec7371-2137-4ba6-ab17-ce307adb0be9 · inbound

CCQ: Convolutional Code for Extreme Low-bit Quantization in LLMs cites this paper.

CCQ: Convolutional Code for Extreme Low-bit Quantization in LLMs GPTAQ: Efficient Finetuning-Free Quantization for Asymmetric Calibration

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-06T19:09:14.944813Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8805c87f-0921-40a8-b97e-06253c9e9cc2 · inbound

Sensitivity-LoRA: Low-Load Sensitivity-Based Fine-Tuning for Large Language Models cites this paper.

Sensitivity-LoRA: Low-Load Sensitivity-Based Fine-Tuning for Large Language Models GPTAQ: Efficient Finetuning-Free Quantization for Asymmetric Calibration

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-04T19:43:37.229657Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5adc01a8-cfc0-4c64-b3c7-7b3cc535dbaa · inbound

Rethinking Residual Errors in Compensation-based LLM Quantization cites this paper.

Rethinking Residual Errors in Compensation-based LLM Quantization GPTAQ: Efficient Finetuning-Free Quantization for Asymmetric Calibration

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-05-11T05:21:01.344171Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation bb41a05f-8111-47f0-9387-85fa633333d0 · inbound

CAR-SAM: Cross-Attention Reconstruction for Post-Training Quantization of the Segment Anything Model cites this paper.

CAR-SAM: Cross-Attention Reconstruction for Post-Training Quantization of the Segment Anything Model GPTAQ: Efficient Finetuning-Free Quantization for Asymmetric Calibration

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-05-19T21:32:47.921829Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 2b0a8e15-181d-486d-9aff-68e278f833b0 · inbound

MARR: Module-Adaptive Residual Reconstruction for Low-Bit Post-Training Quantization cites this paper.

MARR: Module-Adaptive Residual Reconstruction for Low-Bit Post-Training Quantization GPTAQ: Efficient Finetuning-Free Quantization for Asymmetric Calibration

Reference 19

Resolution: verified exact; arxiv_id, observed 2026-05-20T12:58:17.782611Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 89722c4a-e2b0-4ee3-bd7c-026193208c7f · inbound

Qift: Shift-Friendly No-Zero W2 Post-Training Quantization for Rotated W2A4/KV4 LLM Inference cites this paper.

Qift: Shift-Friendly No-Zero W2 Post-Training Quantization for Rotated W2A4/KV4 LLM Inference GPTAQ: Efficient Finetuning-Free Quantization for Asymmetric Calibration

Reference 2

Resolution: verified exact; arxiv_id, observed 2026-07-01T22:06:15.961244Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 3964656c-7633-4dd1-98d0-d2a18022d026 · inbound

Quantizing Time-Series Models As Dynamical Systems: Trajectory-Based Quantization Sensitivity Score cites this paper.

Quantizing Time-Series Models As Dynamical Systems: Trajectory-Based Quantization Sensitivity Score GPTAQ: Efficient Finetuning-Free Quantization for Asymmetric Calibration

Reference 28

Resolution: metadata mismatch; arxiv_id, observed 2026-07-03T13:58:21.998491Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation d5952310-d2ac-4fef-b622-a7b8c6079f36 · inbound

KronQ: LLM Quantization via Kronecker-Factored Hessian cites this paper.

KronQ: LLM Quantization via Kronecker-Factored Hessian GPTAQ: Efficient Finetuning-Free Quantization for Asymmetric Calibration

Reference 21

Resolution: verified exact; local_arxiv, observed 2026-07-10T14:47:14.598880Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation fbb4eb6b-d828-490c-b822-fa729bbc168f · inbound

ReQuant: Fixed-Grid Discrete Refinement for Post-Training Quantization cites this paper.

ReQuant: Fixed-Grid Discrete Refinement for Post-Training Quantization GPTAQ: Efficient Finetuning-Free Quantization for Asymmetric Calibration

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-10T16:36:24.484974Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ade6ce60-90a3-4f87-939f-0291b703176d · inbound

SoftWater: Class-Aware Rate Allocation for Softmax Quantization cites this paper.

SoftWater: Class-Aware Rate Allocation for Softmax Quantization GPTAQ: Efficient Finetuning-Free Quantization for Asymmetric Calibration

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-16T00:26:51.642528Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.