Paper Citation Record · LEDGER

LC-QAT: Data-Efficient 2-Bit QAT for LLMs via Linear-Constrained Vector Quantization

As of 14 August 2026, this Paper Citation Record lists 23 of 23 outbound references and 1 inbound Pith citation observation for arXiv:2606.10531.

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

pith.paper-citation-record.v1
2606.10531 v2

Coverage vector

measured 23 of 23 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-02T22:47:05.759610Z

measured 24 of 24 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-10T04:03:37.649301Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-10T04:06:44.605939Z

Reference resolution

23 of 23 outbound references displayed

verified exact20
verified fuzzy1
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch2

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation a51ae9af-5aba-4ac4-aded-bd05a42645d7 · outbound

This paper cites Understanding pre-training and fine-tuning from loss landscape perspectives.

LC-QAT: Data-Efficient 2-Bit QAT for LLMs via Linear-Constrained Vector Quantization Understanding pre-training and fine-tuning from loss landscape perspectives

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-07-02T22:47:25.253535Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 53375a1a-0c49-4d6d-988a-c7547cece42e · outbound

This paper cites Evaluating Large Language Models Trained on Code.

LC-QAT: Data-Efficient 2-Bit QAT for LLMs via Linear-Constrained Vector Quantization Evaluating Large Language Models Trained on Code

Reference 2

Resolution: verified exact; local_arxiv, observed 2026-07-02T22:47:25.271967Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation bafb2105-581c-4742-a818-6f6bdf055903 · outbound

This paper cites EfficientQAT: Efficient Quantization-Aware Training for Large Language Models.

LC-QAT: Data-Efficient 2-Bit QAT for LLMs via Linear-Constrained Vector Quantization EfficientQAT: Efficient Quantization-Aware Training for Large Language Models

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-07-02T22:47:25.239020Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation d331fbbc-3ee9-4358-b86c-7acdaa81742e · outbound

This paper cites Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge.

LC-QAT: Data-Efficient 2-Bit QAT for LLMs via Linear-Constrained Vector Quantization Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge

Reference 4

Resolution: verified exact; local_arxiv, observed 2026-07-02T22:47:25.223718Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation f0fd8366-b7f0-4db7-8d88-dbe624b501ae · outbound

This paper cites Training Verifiers to Solve Math Word Problems.

LC-QAT: Data-Efficient 2-Bit QAT for LLMs via Linear-Constrained Vector Quantization Training Verifiers to Solve Math Word Problems

Reference 5

Resolution: verified exact; local_arxiv, observed 2026-07-02T22:47:25.272635Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation c40e9d83-52ab-4a7c-aec8-ff44745c40a0 · outbound

This paper cites GPTQ: Accurate Post-Training Quantization for Generative Pre-trained Transformers.

LC-QAT: Data-Efficient 2-Bit QAT for LLMs via Linear-Constrained Vector Quantization GPTQ: Accurate Post-Training Quantization for Generative Pre-trained Transformers

Reference 6

Resolution: verified exact; local_arxiv, observed 2026-07-02T22:47:25.238995Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation e8f262cc-5885-442e-bd3d-e59dd40bb7d3 · outbound

This paper cites Low-Precision Training of Large Language Models: Methods, Challenges, and Opportunities.

LC-QAT: Data-Efficient 2-Bit QAT for LLMs via Linear-Constrained Vector Quantization Low-Precision Training of Large Language Models: Methods, Challenges, and Opportunities

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-07-30T01:18:51.459998Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 85b81d36-0bcd-4c32-8c96-bb3d12747fb1 · outbound

This paper cites Measuring Massive Multitask Language Understanding.

LC-QAT: Data-Efficient 2-Bit QAT for LLMs via Linear-Constrained Vector Quantization Measuring Massive Multitask Language Understanding

Reference 8

Resolution: verified exact; local_arxiv, observed 2026-07-02T22:47:25.274836Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation ffcc7459-17e8-46ff-84d9-fcad965d5780 · outbound

This paper cites MiniCPM: Unveiling the Potential of Small Language Models with Scalable Training Strategies.

LC-QAT: Data-Efficient 2-Bit QAT for LLMs via Linear-Constrained Vector Quantization MiniCPM: Unveiling the Potential of Small Language Models with Scalable Training Strategies

Reference 9

Resolution: metadata mismatch; local_arxiv, observed 2026-07-02T22:47:25.253434Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 532c621b-663a-4d2b-831a-529cf7e5b993 · outbound

This paper cites Let's Verify Step by Step.

LC-QAT: Data-Efficient 2-Bit QAT for LLMs via Linear-Constrained Vector Quantization Let's Verify Step by Step

Reference 10

Resolution: verified exact; local_arxiv, observed 2026-07-02T22:47:25.266683Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation a5a612fb-9ba0-40d2-b5d0-995de1e16987 · outbound

This paper cites LLM-QAT: Data-Free Quantization Aware Training for Large Language Models.

LC-QAT: Data-Efficient 2-Bit QAT for LLMs via Linear-Constrained Vector Quantization LLM-QAT: Data-Free Quantization Aware Training for Large Language Models

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-07-02T22:47:25.227142Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation cc5e1356-2771-4ec5-bdeb-6753fbb55409 · outbound

This paper cites The Llama 3 Herd of Models.

LC-QAT: Data-Efficient 2-Bit QAT for LLMs via Linear-Constrained Vector Quantization The Llama 3 Herd of Models

Reference 12

Resolution: verified exact; local_arxiv, observed 2026-07-02T22:47:25.250996Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 8a249931-a43c-494b-965c-b38b6b71fac3 · outbound

This paper cites BitNet b1.58 2B4T Technical Report.

LC-QAT: Data-Efficient 2-Bit QAT for LLMs via Linear-Constrained Vector Quantization BitNet b1.58 2B4T Technical Report

Reference 13

Resolution: verified exact; arxiv_id, observed 2026-07-02T22:47:25.270163Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation ea39d109-18e3-400e-83fd-486326f90ca4 · outbound

This paper cites Pointer Sentinel Mixture Models.

LC-QAT: Data-Efficient 2-Bit QAT for LLMs via Linear-Constrained Vector Quantization Pointer Sentinel Mixture Models

Reference 14

Resolution: verified exact; local_arxiv, observed 2026-07-02T22:47:25.244629Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 6006294d-9c60-4bf4-b99f-7bed29ef6141 · outbound

This paper cites Can a Suit of Armor Conduct Electricity? A New Dataset for Open Book Question Answering.

LC-QAT: Data-Efficient 2-Bit QAT for LLMs via Linear-Constrained Vector Quantization Can a Suit of Armor Conduct Electricity? A New Dataset for Open Book Question Answering

Reference 15

Resolution: verified exact; local_arxiv, observed 2026-07-02T22:47:25.263995Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation e7d9c0a0-b8bf-46f7-9ce3-42aaad1fe245 · outbound

This paper cites The FineWeb Datasets: Decanting the Web for the Finest Text Data at Scale.

LC-QAT: Data-Efficient 2-Bit QAT for LLMs via Linear-Constrained Vector Quantization The FineWeb Datasets: Decanting the Web for the Finest Text Data at Scale

Reference 16

Resolution: metadata mismatch; local_arxiv, observed 2026-07-02T22:47:25.255983Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 5d6c43d1-7e80-4924-935f-77413081bcb4 · outbound

This paper cites Model-Preserving Adaptive Rounding.

LC-QAT: Data-Efficient 2-Bit QAT for LLMs via Linear-Constrained Vector Quantization Model-Preserving Adaptive Rounding

Reference 17

Resolution: verified exact; local_arxiv, observed 2026-07-02T22:47:25.215524Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation a6e1e0fc-dee2-4ecf-ac80-73c2c42e9c06 · outbound

This paper cites Optimizing Large Language Model Training Using FP4 Quantization.

LC-QAT: Data-Efficient 2-Bit QAT for LLMs via Linear-Constrained Vector Quantization Optimizing Large Language Model Training Using FP4 Quantization

Reference 18

Resolution: verified exact; local_arxiv, observed 2026-07-02T22:47:25.269295Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 192cbd20-acdb-41f4-88ba-745b19a23c7e · outbound

This paper cites Qwen3 Technical Report.

LC-QAT: Data-Efficient 2-Bit QAT for LLMs via Linear-Constrained Vector Quantization Qwen3 Technical Report

Reference 19

Resolution: verified exact; local_arxiv, observed 2026-07-02T22:47:25.258730Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 91240b77-ba6c-4466-8c78-2814b97af4dc · outbound

This paper cites Understanding Straight-Through Estimator in Training Activation Quantized Neural Nets.

LC-QAT: Data-Efficient 2-Bit QAT for LLMs via Linear-Constrained Vector Quantization Understanding Straight-Through Estimator in Training Activation Quantized Neural Nets

Reference 20

Resolution: verified exact; arxiv_id, observed 2026-07-02T22:47:25.256083Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation ddd0a765-c47f-4ee2-8964-e8c23d26b99b · outbound

This paper cites Instruction-Following Evaluation for Large Language Models.

LC-QAT: Data-Efficient 2-Bit QAT for LLMs via Linear-Constrained Vector Quantization Instruction-Following Evaluation for Large Language Models

Reference 21

Resolution: verified exact; local_arxiv, observed 2026-07-02T22:47:25.264138Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 291b7156-4a4c-43fc-ab4e-2557744742a2 · outbound

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

LC-QAT: Data-Efficient 2-Bit QAT for LLMs via Linear-Constrained Vector Quantization CCQ: Convolutional Code for Extreme Low-bit Quantization in LLMs

Reference 22

Resolution: verified exact; arxiv_id, observed 2026-07-02T22:47:25.261681Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 942c4db7-960f-4274-8c25-6661349b7d24 · outbound

This paper cites METHOD PTQ TIME (H) QAT TIME (H) T OTAL TIME (H) LC-QAT 6 55 61 PARETO Q N/A 417 417 A.3.

LC-QAT: Data-Efficient 2-Bit QAT for LLMs via Linear-Constrained Vector Quantization METHOD PTQ TIME (H) QAT TIME (H) T OTAL TIME (H) LC-QAT 6 55 61 PARETO Q N/A 417 417 A.3

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T18:31:23.163976Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Pith citing papers

Observation 8b7d278f-f55c-44e3-a5b4-49faa595d462 · inbound

BiSCo-LLM: Lookup-Free Binary Spherical Coding for Extreme Low-Bit Large Language Model Compression cites this paper.

BiSCo-LLM: Lookup-Free Binary Spherical Coding for Extreme Low-Bit Large Language Model Compression LC-QAT: Data-Efficient 2-Bit QAT for LLMs via Linear-Constrained Vector Quantization

Reference 34

Resolution: verified exact; local_arxiv, observed 2026-07-10T04:06:44.608002Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.