Paper Citation Record · LEDGER

SiLQ: Simple Large Language Model Quantization-Aware Training

As of 7 August 2026, this Paper Citation Record lists 29 of 29 outbound references and 1 inbound Pith citation observation for arXiv:2507.16933.

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

pith.paper-citation-record.v1
2507.16933 v1

Coverage vector

measured 29 of 29 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T15:08:29.799420Z

measured 30 of 30 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 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-12T02:38:11.071221Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-12T07:31:26.282151Z

Reference resolution

29 of 29 outbound references displayed

verified exact0
verified fuzzy3
unresolved26
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 5baac5d1-5fd9-4271-8ee8-bb50732ab57b · outbound

This paper cites an unresolved cited work.

SiLQ: Simple Large Language Model Quantization-Aware Training Unresolved cited work

Reference 1

Resolution: unresolved; raw_fallback, observed 2026-08-06T15:08:33.301777Z

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 b7837cf5-cf70-47a6-9c0e-ca5cb06516b2 · outbound

This paper cites an unresolved cited work.

SiLQ: Simple Large Language Model Quantization-Aware Training Unresolved cited work

Reference 2

Resolution: unresolved; raw_fallback, observed 2026-08-06T15:08:32.987585Z

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 a790008b-46fd-4a59-ac4a-69a8f4706e9e · outbound

This paper cites Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation.

SiLQ: Simple Large Language Model Quantization-Aware Training Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-06T15:08:26.301138Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9bf823a9-ad89-4c39-99d7-368d25843d7f · outbound

This paper cites PrefixQuant: Eliminating Outliers by Prefixed Tokens for Large Language Models Quantization.

SiLQ: Simple Large Language Model Quantization-Aware Training PrefixQuant: Eliminating Outliers by Prefixed Tokens for Large Language Models Quantization

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-06T15:08:26.413524Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fd84d796-2cf5-4b7f-8e53-5a75ae456c08 · outbound

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

SiLQ: Simple Large Language Model Quantization-Aware Training EfficientQAT: Efficient Quantization-Aware Training for Large Language Models

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-06T15:08:26.568508Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c296ec80-830a-4812-b5ae-1a6d519a41d8 · outbound

This paper cites Fu, Stefano Ermon, Atri Rudra, and Christopher R \'e.

SiLQ: Simple Large Language Model Quantization-Aware Training Fu, Stefano Ermon, Atri Rudra, and Christopher R \'e

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:08:32.690384Z

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 8f314e75-ca3b-447b-9648-af25be343cd5 · outbound

This paper cites BitDistiller: Unleashing the Potential of Sub-4-Bit LLMs via Self-Distillation.

SiLQ: Simple Large Language Model Quantization-Aware Training BitDistiller: Unleashing the Potential of Sub-4-Bit LLMs via Self-Distillation

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-06T15:08:26.859827Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c9a89695-b5ca-400c-b104-94990150d472 · outbound

This paper cites an unresolved cited work.

SiLQ: Simple Large Language Model Quantization-Aware Training Unresolved cited work

Reference 8

Resolution: unresolved; raw_fallback, observed 2026-08-06T15:08:32.496434Z

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 fdb6a6e9-43eb-4baa-b7f4-a187957cefe4 · outbound

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

SiLQ: Simple Large Language Model Quantization-Aware Training GPTQ: Accurate Post-Training Quantization for Generative Pre-trained Transformers

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-06T15:08:27.101492Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2b4fe852-b01c-4541-8072-0ee8f6b4f777 · outbound

This paper cites an unresolved cited work.

SiLQ: Simple Large Language Model Quantization-Aware Training Unresolved cited work

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-06T15:08:27.217357Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3d87b40c-8c32-4e05-94ea-bea2f0f8b03d · outbound

This paper cites Distilling the Knowledge in a Neural Network.

SiLQ: Simple Large Language Model Quantization-Aware Training Distilling the Knowledge in a Neural Network

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-06T15:08:27.368246Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 79f4bc61-c53a-47b4-9e38-511059cd917d · outbound

This paper cites an unresolved cited work.

SiLQ: Simple Large Language Model Quantization-Aware Training Unresolved cited work

Reference 12

Resolution: unresolved; raw_fallback, observed 2026-08-06T15:08:32.227892Z

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 f209ca72-dfb3-4a03-a87c-73965a29ea66 · outbound

This paper cites Sft trainer — trl documentation.

SiLQ: Simple Large Language Model Quantization-Aware Training Sft trainer — trl documentation

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:08:31.886610Z

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 1fcfa5a1-2395-4d70-85a3-0cc4378b5a08 · outbound

This paper cites Tulu 3: Pushing Frontiers in Open Language Model Post-Training.

SiLQ: Simple Large Language Model Quantization-Aware Training Tulu 3: Pushing Frontiers in Open Language Model Post-Training

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-06T15:08:27.751884Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3ed256d7-a068-4937-89fa-bdd3fa7edddd · outbound

This paper cites Exploring the Trade-Offs: Quantization Methods, Task Difficulty, and Model Size in Large Language Models From Edge to Giant.

SiLQ: Simple Large Language Model Quantization-Aware Training Exploring the Trade-Offs: Quantization Methods, Task Difficulty, and Model Size in Large Language Models From Edge to Giant

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-06T15:08:27.899104Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8badd7f2-ff3d-435e-a3a0-49886357854a · outbound

This paper cites an unresolved cited work.

SiLQ: Simple Large Language Model Quantization-Aware Training Unresolved cited work

Reference 16

Resolution: unresolved; raw_fallback, observed 2026-08-06T15:08:31.537278Z

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 b814e3ab-99ec-4300-aa5e-a2060109a7fe · outbound

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

SiLQ: Simple Large Language Model Quantization-Aware Training LLM-QAT: Data-Free Quantization Aware Training for Large Language Models

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-06T15:08:28.125268Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation eaeed9bd-da10-446b-bd69-1300b891e7d1 · outbound

This paper cites SpinQuant: LLM quantization with learned rotations.

SiLQ: Simple Large Language Model Quantization-Aware Training SpinQuant: LLM quantization with learned rotations

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-06T15:08:28.214739Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e6295020-d45f-4060-8428-b6db17d85d41 · outbound

This paper cites an unresolved cited work.

SiLQ: Simple Large Language Model Quantization-Aware Training Unresolved cited work

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-06T15:08:28.368262Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 33c9b6d1-415c-4699-826d-8458d6bb6ac7 · outbound

This paper cites Decoupled Weight Decay Regularization.

SiLQ: Simple Large Language Model Quantization-Aware Training Decoupled Weight Decay Regularization

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-06T15:08:28.517646Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 466df803-ac7c-425d-8cf3-20e2321972d8 · outbound

This paper cites an unresolved cited work.

SiLQ: Simple Large Language Model Quantization-Aware Training Unresolved cited work

Reference 21

Resolution: unresolved; raw_fallback, observed 2026-08-06T15:08:31.259306Z

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 8f1fc671-7f1f-4f48-89f3-2ea61bae8bbe · outbound

This paper cites an unresolved cited work.

SiLQ: Simple Large Language Model Quantization-Aware Training Unresolved cited work

Reference 22

Resolution: unresolved; raw_fallback, observed 2026-08-06T15:08:31.037446Z

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 3bfa4de5-803d-429d-827b-ac5a995d7023 · outbound

This paper cites Power Scheduler: A Batch Size and Token Number Agnostic Learning Rate Scheduler.

SiLQ: Simple Large Language Model Quantization-Aware Training Power Scheduler: A Batch Size and Token Number Agnostic Learning Rate Scheduler

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-06T15:08:28.936813Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 04573746-73c2-4467-921f-fc0156a45b36 · outbound

This paper cites https://github.com/facebookresearch/LLM-QAT, Accessed: 2025-06-19.

SiLQ: Simple Large Language Model Quantization-Aware Training https://github.com/facebookresearch/LLM-QAT, Accessed: 2025-06-19

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:08:30.762839Z

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 c968c840-9b15-4a3b-ab6d-fa46d242edff · outbound

This paper cites BitNet a4.8: 4-bit Activations for 1-bit LLMs.

SiLQ: Simple Large Language Model Quantization-Aware Training BitNet a4.8: 4-bit Activations for 1-bit LLMs

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-06T15:08:29.258048Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e16ef3ae-d6ec-40c1-a0b7-235198e21f99 · outbound

This paper cites an unresolved cited work.

SiLQ: Simple Large Language Model Quantization-Aware Training Unresolved cited work

Reference 26

Resolution: unresolved; raw_fallback, observed 2026-08-06T15:08:30.388348Z

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 24e555cf-f4aa-4ff6-a58a-63884a6dbeeb · outbound

This paper cites an unresolved cited work.

SiLQ: Simple Large Language Model Quantization-Aware Training Unresolved cited work

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-06T15:08:29.530102Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3a3a095f-eda8-41a2-a546-7817e53568a1 · outbound

This paper cites QA-LoRA: Quantization-Aware Low-Rank Adaptation of Large Language Models.

SiLQ: Simple Large Language Model Quantization-Aware Training QA-LoRA: Quantization-Aware Low-Rank Adaptation of Large Language Models

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-06T15:08:29.673002Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d1122fd9-4d29-43fe-96f4-d99741b8e8b8 · outbound

This paper cites an unresolved cited work.

SiLQ: Simple Large Language Model Quantization-Aware Training Unresolved cited work

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-06T15:08:29.799420Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation b227dcf7-2a16-480c-8cdd-fd94f39f1e9f · inbound

AtteConDA: Attention-Based Conflict Suppression in Multi-Condition Diffusion Models and Synthetic Data Augmentation cites this paper.

AtteConDA: Attention-Based Conflict Suppression in Multi-Condition Diffusion Models and Synthetic Data Augmentation SiLQ: Simple Large Language Model Quantization-Aware Training

Reference 19

Resolution: verified exact; arxiv_id, observed 2026-05-12T07:31:26.284793Z

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.