Paper Citation Record · LEDGER

BASE-Q: Bias and Asymmetric Scaling Enhanced Rotational Quantization for Large Language Models

As of 8 August 2026, this Paper Citation Record lists 35 of 35 outbound references and 0 inbound Pith citation observations for arXiv:2506.15689.

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

pith.paper-citation-record.v1
2506.15689 v2

Coverage vector

measured 35 of 35 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:06:26.892775Z

measured 35 of 35 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

35 of 35 outbound references displayed

verified exact1
verified fuzzy2
unresolved31
parse uncertain0
malformed identifier1
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation c26b6598-1de8-4ada-8468-c7e4cb088ac7 · outbound

This paper cites LLaMA: Open and Efficient Foundation Language Models.

BASE-Q: Bias and Asymmetric Scaling Enhanced Rotational Quantization for Large Language Models LLaMA: Open and Efficient Foundation Language Models

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-07T14:06:23.265922Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 05a417ef-fd3b-4b5f-87a9-a6aea89baf01 · outbound

This paper cites Qwen Technical Report.

BASE-Q: Bias and Asymmetric Scaling Enhanced Rotational Quantization for Large Language Models Qwen Technical Report

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-07T14:06:23.340470Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 14e4d958-dd5c-4e81-9604-b5df1725345f · outbound

This paper cites The Llama 3 Herd of Models.

BASE-Q: Bias and Asymmetric Scaling Enhanced Rotational Quantization for Large Language Models The Llama 3 Herd of Models

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-07T14:06:23.455560Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 255e687c-dcf6-44f7-8eee-ae557b2dd2f9 · outbound

This paper cites Llama 2: Open Foundation and Fine-Tuned Chat Models.

BASE-Q: Bias and Asymmetric Scaling Enhanced Rotational Quantization for Large Language Models Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-07T14:06:23.594746Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c77f5654-34e3-4405-b46a-3c48140c66c3 · outbound

This paper cites DeepSeek-V3 Technical Report.

BASE-Q: Bias and Asymmetric Scaling Enhanced Rotational Quantization for Large Language Models DeepSeek-V3 Technical Report

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-07T14:06:23.658205Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ee549646-d103-4bea-8b68-47d41e8179a3 · outbound

This paper cites Up or Down? Adaptive Rounding for Post-Training Quantization.

BASE-Q: Bias and Asymmetric Scaling Enhanced Rotational Quantization for Large Language Models Up or Down? Adaptive Rounding for Post-Training Quantization

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-07T14:06:23.724826Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 877e906a-cbc8-48e9-bb07-2fa16961d5d4 · outbound

This paper cites BRECQ: Pushing the Limit of Post-Training Quantization by Block Reconstruction.

BASE-Q: Bias and Asymmetric Scaling Enhanced Rotational Quantization for Large Language Models BRECQ: Pushing the Limit of Post-Training Quantization by Block Reconstruction

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-07T14:06:23.802464Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6d94a65f-318a-44c2-bcc7-43a679a065f5 · outbound

This paper cites Noisyquant: Noisy bias-enhanced post-training activation quantization for vision transformers.

BASE-Q: Bias and Asymmetric Scaling Enhanced Rotational Quantization for Large Language Models Noisyquant: Noisy bias-enhanced post-training activation quantization for vision transformers

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:06:27.887445Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation c5994444-902e-43be-8f25-944b878c1048 · outbound

This paper cites FBQuant: FeedBack Quantization for Large Language Models.

BASE-Q: Bias and Asymmetric Scaling Enhanced Rotational Quantization for Large Language Models FBQuant: FeedBack Quantization for Large Language Models

Reference 9

Resolution: verified exact; local_arxiv, observed 2026-08-07T14:06:27.286396Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation a05345fa-7475-41b2-a502-2699e1cf9580 · outbound

This paper cites Outlier Suppression+: Accurate quantization of large language models by equivalent and optimal shifting and scaling.

BASE-Q: Bias and Asymmetric Scaling Enhanced Rotational Quantization for Large Language Models Outlier Suppression+: Accurate quantization of large language models by equivalent and optimal shifting and scaling

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-07T14:06:24.060629Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 322b8f75-4cb1-4daa-aa9a-b2684b503bac · outbound

This paper cites LLM.int8(): 8-bit Matrix Multiplication for Transformers at Scale.

BASE-Q: Bias and Asymmetric Scaling Enhanced Rotational Quantization for Large Language Models LLM.int8(): 8-bit Matrix Multiplication for Transformers at Scale

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-07T14:06:24.154265Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bd38d449-b875-4550-8691-70ccca586eb4 · outbound

This paper cites SmoothQuant: Accurate and Efficient Post-Training Quantization for Large Language Models.

BASE-Q: Bias and Asymmetric Scaling Enhanced Rotational Quantization for Large Language Models SmoothQuant: Accurate and Efficient Post-Training Quantization for Large Language Models

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-07T14:06:24.279700Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 47f24cf5-f99d-477e-bda5-0f8bcad15e1c · outbound

This paper cites QuaRot: Outlier-Free 4-Bit Inference in Rotated LLMs.

BASE-Q: Bias and Asymmetric Scaling Enhanced Rotational Quantization for Large Language Models QuaRot: Outlier-Free 4-Bit Inference in Rotated LLMs

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-07T14:06:24.394539Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 63ce508e-bbf5-45fe-867e-4b47695ddeca · outbound

This paper cites SpinQuant: LLM quantization with learned rotations.

BASE-Q: Bias and Asymmetric Scaling Enhanced Rotational Quantization for Large Language Models SpinQuant: LLM quantization with learned rotations

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-07T14:06:24.448912Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6d56403d-f536-4b30-b255-95fc7fe68239 · outbound

This paper cites OstQuant: Refining Large Language Model Quantization with Orthogonal and Scaling Transformations for Better Distribution Fitting.

BASE-Q: Bias and Asymmetric Scaling Enhanced Rotational Quantization for Large Language Models OstQuant: Refining Large Language Model Quantization with Orthogonal and Scaling Transformations for Better Distribution Fitting

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-07T14:06:24.512952Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation db2a2f74-26e0-42fe-9bd5-1a29b77d24f2 · outbound

This paper cites Awq: Activation-aware weight quantization for on-device llm compression and acceleration.

BASE-Q: Bias and Asymmetric Scaling Enhanced Rotational Quantization for Large Language Models Awq: Activation-aware weight quantization for on-device llm compression and acceleration

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-07T14:06:24.569811Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 13303272-2f8c-4228-ab0f-54d8b80b88b8 · outbound

This paper cites OmniQuant: Omnidirectionally Calibrated Quantization for Large Language Models.

BASE-Q: Bias and Asymmetric Scaling Enhanced Rotational Quantization for Large Language Models OmniQuant: Omnidirectionally Calibrated Quantization for Large Language Models

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-07T14:06:24.651918Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fa214855-69a4-4aa3-82e5-215be9e068c3 · outbound

This paper cites AffineQuant: Affine Transformation Quantization for Large Language Models.

BASE-Q: Bias and Asymmetric Scaling Enhanced Rotational Quantization for Large Language Models AffineQuant: Affine Transformation Quantization for Large Language Models

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-07T14:06:24.737750Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f87cbbb8-73fe-4fe3-a03e-d36621456d68 · outbound

This paper cites Quip: 2-bit quantiza- tion of large language models with guarantees.

BASE-Q: Bias and Asymmetric Scaling Enhanced Rotational Quantization for Large Language Models Quip: 2-bit quantiza- tion of large language models with guarantees

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:06:27.720106Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 76718352-586f-4a20-830d-36091d474f31 · outbound

This paper cites QuIP#: Even Better LLM Quantization with Hadamard Incoherence and Lattice Codebooks.

BASE-Q: Bias and Asymmetric Scaling Enhanced Rotational Quantization for Large Language Models QuIP#: Even Better LLM Quantization with Hadamard Incoherence and Lattice Codebooks

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-07T14:06:24.880486Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9cc3d3d4-1efb-4d42-98ee-49973a2542a7 · outbound

This paper cites Duquant: Distributing outliers via dual transformation makes stronger quantized llms.

BASE-Q: Bias and Asymmetric Scaling Enhanced Rotational Quantization for Large Language Models Duquant: Distributing outliers via dual transformation makes stronger quantized llms

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-07T14:06:25.040563Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f7019349-af58-4c26-82d7-f4579f20ef7b · outbound

This paper cites FlatQuant: Flatness Matters for LLM Quantization.

BASE-Q: Bias and Asymmetric Scaling Enhanced Rotational Quantization for Large Language Models FlatQuant: Flatness Matters for LLM Quantization

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-07T14:06:25.044991Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6b97d8ae-1689-4b07-a2e4-70ab795811b6 · outbound

This paper cites Qwen2.5 Technical Report.

BASE-Q: Bias and Asymmetric Scaling Enhanced Rotational Quantization for Large Language Models Qwen2.5 Technical Report

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-07T14:06:25.171531Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8a89b250-4652-47dd-96e8-1cea268d5ce7 · outbound

This paper cites Pointer Sentinel Mixture Models.

BASE-Q: Bias and Asymmetric Scaling Enhanced Rotational Quantization for Large Language Models Pointer Sentinel Mixture Models

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-07T14:06:25.309380Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a5e21f50-4d94-4b74-918a-920a38331dd1 · outbound

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

BASE-Q: Bias and Asymmetric Scaling Enhanced Rotational Quantization for Large Language Models Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-07T14:06:25.480561Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 001e0c7b-6999-4c98-bdfb-5ef3be6e97f2 · outbound

This paper cites BoolQ: Exploring the Surprising Difficulty of Natural Yes/No Questions.

BASE-Q: Bias and Asymmetric Scaling Enhanced Rotational Quantization for Large Language Models BoolQ: Exploring the Surprising Difficulty of Natural Yes/No Questions

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-07T14:06:25.696290Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7cd97b0b-3595-4b10-8ba1-b470dfd6eb62 · outbound

This paper cites HellaSwag: Can a Machine Really Finish Your Sentence?.

BASE-Q: Bias and Asymmetric Scaling Enhanced Rotational Quantization for Large Language Models HellaSwag: Can a Machine Really Finish Your Sentence?

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-07T14:06:25.812447Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d0c8a70a-e737-49a4-8cc8-b9e5dfcbdc42 · outbound

This paper cites Language models are unsupervised multitask learners.

BASE-Q: Bias and Asymmetric Scaling Enhanced Rotational Quantization for Large Language Models Language models are unsupervised multitask learners

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-07T14:06:25.954271Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 49a511ed-2fbd-45cd-aad5-98edf09d33cc · outbound

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

BASE-Q: Bias and Asymmetric Scaling Enhanced Rotational Quantization for Large Language Models Can a Suit of Armor Conduct Electricity? A New Dataset for Open Book Question Answering

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-07T14:06:26.090941Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b28cd0b4-4ea0-41df-a379-6ed83b610544 · outbound

This paper cites Piqa: Reasoning about phys- ical commonsense in natural language.

BASE-Q: Bias and Asymmetric Scaling Enhanced Rotational Quantization for Large Language Models Piqa: Reasoning about phys- ical commonsense in natural language

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-07T14:06:26.218349Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 25259a9f-ab99-41c5-b64c-56f87f578427 · outbound

This paper cites SocialIQA: Commonsense Reasoning about Social Interactions.

BASE-Q: Bias and Asymmetric Scaling Enhanced Rotational Quantization for Large Language Models SocialIQA: Commonsense Reasoning about Social Interactions

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-07T14:06:26.330099Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6619db19-55fd-4d76-a959-9b6d2575756c · outbound

This paper cites Winogrande: An adversarial winograd schema challenge at scale.

BASE-Q: Bias and Asymmetric Scaling Enhanced Rotational Quantization for Large Language Models Winogrande: An adversarial winograd schema challenge at scale

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-07T14:06:26.454824Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 16bbe977-c947-4ea2-88f1-a446af282dcd · outbound

This paper cites The language model evaluation harness, 07 2024.

BASE-Q: Bias and Asymmetric Scaling Enhanced Rotational Quantization for Large Language Models The language model evaluation harness, 07 2024

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-07T14:06:26.592387Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5efa2cdb-d0dc-438b-9bd0-b1468289d2fb · outbound

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

BASE-Q: Bias and Asymmetric Scaling Enhanced Rotational Quantization for Large Language Models GPTQ: Accurate Post-Training Quantization for Generative Pre-trained Transformers

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-07T14:06:26.709166Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2dc92a52-3d22-4aba-ab42-925513558bac · outbound

This paper cites fast-hadamard-transform, 2023.

BASE-Q: Bias and Asymmetric Scaling Enhanced Rotational Quantization for Large Language Models fast-hadamard-transform, 2023

Reference 35

Resolution: malformed identifier; raw_fallback, observed 2026-08-07T14:06:27.498397Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Pith citing papers

No inbound Pith citation observations are available.