Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-07-02T22:47:05.759610Z
Paper Citation Record · LEDGER
LC-QAT: Data-Efficient 2-Bit QAT for LLMs via Linear-Constrained Vector Quantization
As of 16 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.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-07-10T04:03:37.649301Z
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 2026-08-16T06:30:59.297886+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 2026-08-16T06:30:59.297886+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 2026-08-16T06:30:59.297886+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 2026-08-16T06:30:59.297886+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 2026-08-16T06:30:59.297886+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 2026-08-16T06:30:59.297886+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 2026-08-16T06:30:59.297886+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 2026-08-16T06:30:59.297886+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 2026-08-16T06:30:59.297886+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 2026-08-16T06:30:59.297886+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 2026-08-16T06:30:59.297886+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 2026-08-16T06:30:59.297886+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 2026-08-16T06:30:59.297886+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 2026-08-16T06:30:59.297886+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 2026-08-16T06:30:59.297886+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 2026-08-16T06:30:59.297886+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 2026-08-16T06:30:59.297886+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 2026-08-16T06:30:59.297886+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 2026-08-16T06:30:59.297886+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 2026-08-16T06:30:59.297886+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 2026-08-16T06:30:59.297886+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 2026-08-16T06:30:59.297886+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 2026-08-16T06:30:59.297886+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 2026-08-16T06:30:59.297886+00:00.