Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-10T16:13:20.004756Z
Paper Citation Record · LEDGER
OstQuant: Refining Large Language Model Quantization with Orthogonal and Scaling Transformations for Better Distribution Fitting
As of 17 August 2026, this Paper Citation Record lists 37 of 37 outbound references and 22 inbound Pith citation observations for arXiv:2501.13987.
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 2026-08-14T12:54:26.511410Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-07-10T14:47:14.541739Z
Reference resolution
37 of 37 outbound references displayed
- verified exact0
- verified fuzzy4
- unresolved32
- parse uncertain0
- malformed identifier1
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation f9e28a0a-43f5-4102-b60c-d2bf42b495e4 · outbound
This paper cites GPT-4 Technical Report.
OstQuant: Refining Large Language Model Quantization with Orthogonal and Scaling Transformations for Better Distribution Fitting GPT-4 Technical Report
Reference 1
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T16:13:19.891667Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d96730dd-3b9b-4b4e-8f45-535fc4726c1a · outbound
This paper cites QuaRot: Outlier-Free 4-Bit Inference in Rotated LLMs.
OstQuant: Refining Large Language Model Quantization with Orthogonal and Scaling Transformations for Better Distribution Fitting QuaRot: Outlier-Free 4-Bit Inference in Rotated LLMs
Reference 2
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T16:13:19.895149Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5a7f3044-ddba-40da-a6d2-5f8d7a476db1 · outbound
This paper cites Riemannian Adaptive Optimization Methods.
OstQuant: Refining Large Language Model Quantization with Orthogonal and Scaling Transformations for Better Distribution Fitting Riemannian Adaptive Optimization Methods
Reference 3
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T16:13:19.898135Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1a1eb707-f59b-4400-890e-dc51fa180a0a · outbound
This paper cites Piqa: Reasoning about physical commonsense in natural language.
OstQuant: Refining Large Language Model Quantization with Orthogonal and Scaling Transformations for Better Distribution Fitting Piqa: Reasoning about physical commonsense in natural language
Reference 4
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T16:13:19.901788Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 87526d87-580b-44a3-ac45-b82f1efe4d3b · outbound
This paper cites A Systematic Classification of Knowledge, Reasoning, and Context within the ARC Dataset.
OstQuant: Refining Large Language Model Quantization with Orthogonal and Scaling Transformations for Better Distribution Fitting A Systematic Classification of Knowledge, Reasoning, and Context within the ARC Dataset
Reference 5
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T16:13:19.905063Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 50759f5d-a546-42c4-888f-72e3fee4cbcc · outbound
This paper cites QuIP: 2-Bit Quantization of Large Language Models With Guarantees.
OstQuant: Refining Large Language Model Quantization with Orthogonal and Scaling Transformations for Better Distribution Fitting QuIP: 2-Bit Quantization of Large Language Models With Guarantees
Reference 6
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T16:13:19.908404Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b983fb3d-502e-4f32-a4e8-cbd9a9de49d8 · outbound
This paper cites Driving with llms: Fusing object-level vector modality for explainable autonomous driving.
OstQuant: Refining Large Language Model Quantization with Orthogonal and Scaling Transformations for Better Distribution Fitting Driving with llms: Fusing object-level vector modality for explainable autonomous driving
Reference 7
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T16:13:20.451293Z
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 8aa98808-749c-480d-a83e-082e4fe38242 · outbound
This paper cites Distributional quantization of large language models.
OstQuant: Refining Large Language Model Quantization with Orthogonal and Scaling Transformations for Better Distribution Fitting Distributional quantization of large language models
Reference 8
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T16:13:20.440804Z
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 2e74fef4-d385-43d9-8b0c-1f008c0f3e55 · outbound
This paper cites BoolQ: Exploring the Surprising Difficulty of Natural Yes/No Questions.
OstQuant: Refining Large Language Model Quantization with Orthogonal and Scaling Transformations for Better Distribution Fitting BoolQ: Exploring the Surprising Difficulty of Natural Yes/No Questions
Reference 9
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T16:13:19.917627Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4a5ba079-b1c3-4606-816b-65b18b35b9a4 · outbound
This paper cites an unresolved cited work.
OstQuant: Refining Large Language Model Quantization with Orthogonal and Scaling Transformations for Better Distribution Fitting Unresolved cited work
Reference 10
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T16:13:19.920908Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a0be1eaa-e935-424c-b151-c8778f59b39d · outbound
This paper cites GPTQ: Accurate Post-Training Quantization for Generative Pre-trained Transformers.
OstQuant: Refining Large Language Model Quantization with Orthogonal and Scaling Transformations for Better Distribution Fitting GPTQ: Accurate Post-Training Quantization for Generative Pre-trained Transformers
Reference 11
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T16:13:19.923928Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d158af50-efbe-404e-a5b5-dd08d3199988 · outbound
This paper cites A framework for few-shot language model evaluation, 07 2024.
OstQuant: Refining Large Language Model Quantization with Orthogonal and Scaling Transformations for Better Distribution Fitting A framework for few-shot language model evaluation, 07 2024
Reference 12
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T16:13:19.927047Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation aaaa6f37-4691-448f-b13b-563a8c370dec · outbound
This paper cites I-LLM: Efficient Integer-Only Inference for Fully-Quantized Low-Bit Large Language Models.
OstQuant: Refining Large Language Model Quantization with Orthogonal and Scaling Transformations for Better Distribution Fitting I-LLM: Efficient Integer-Only Inference for Fully-Quantized Low-Bit Large Language Models
Reference 13
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T16:13:19.929890Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 173008cf-539b-4b48-bf75-2b117e72f090 · outbound
This paper cites The topology of Stiefel manifolds, volume 24.
OstQuant: Refining Large Language Model Quantization with Orthogonal and Scaling Transformations for Better Distribution Fitting The topology of Stiefel manifolds, volume 24
Reference 14
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T16:13:20.424841Z
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 ecc961d3-0e04-44d8-9d9b-79cb1e4398bc · outbound
This paper cites Adam: A Method for Stochastic Optimization.
OstQuant: Refining Large Language Model Quantization with Orthogonal and Scaling Transformations for Better Distribution Fitting Adam: A Method for Stochastic Optimization
Reference 15
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T16:13:19.936085Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 57493104-f9ce-4cd2-a527-6bba40b14ace · outbound
This paper cites Geoopt: Riemannian optimization in pytorch, 2020.
OstQuant: Refining Large Language Model Quantization with Orthogonal and Scaling Transformations for Better Distribution Fitting Geoopt: Riemannian optimization in pytorch, 2020
Reference 16
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T16:13:19.939014Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8099866e-fca7-4610-b48f-6d02622d2c7e · outbound
This paper cites OWQ: Outlier-Aware Weight Quantization for Efficient Fine-Tuning and Inference of Large Language Models.
OstQuant: Refining Large Language Model Quantization with Orthogonal and Scaling Transformations for Better Distribution Fitting OWQ: Outlier-Aware Weight Quantization for Efficient Fine-Tuning and Inference of Large Language Models
Reference 17
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T16:13:19.941751Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0f5b7e03-ee08-4fc2-afb7-9614d5a8acaa · outbound
This paper cites Efficient Riemannian Optimization on the Stiefel Manifold via the Cayley Transform.
OstQuant: Refining Large Language Model Quantization with Orthogonal and Scaling Transformations for Better Distribution Fitting Efficient Riemannian Optimization on the Stiefel Manifold via the Cayley Transform
Reference 18
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T16:13:19.944930Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 930d2d93-5223-4a70-aad2-3647360bb88c · outbound
This paper cites AWQ: Activation-aware Weight Quantization for LLM Compression and Acceleration.
OstQuant: Refining Large Language Model Quantization with Orthogonal and Scaling Transformations for Better Distribution Fitting AWQ: Activation-aware Weight Quantization for LLM Compression and Acceleration
Reference 19
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T16:13:19.948946Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9a126cef-7a74-45cb-aa0b-3c97758022b9 · outbound
This paper cites SpinQuant: LLM quantization with learned rotations.
OstQuant: Refining Large Language Model Quantization with Orthogonal and Scaling Transformations for Better Distribution Fitting SpinQuant: LLM quantization with learned rotations
Reference 20
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T16:13:19.951975Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 166a56b1-ef19-463e-839d-1cb62672ca48 · outbound
This paper cites AffineQuant: Affine Transformation Quantization for Large Language Models.
OstQuant: Refining Large Language Model Quantization with Orthogonal and Scaling Transformations for Better Distribution Fitting AffineQuant: Affine Transformation Quantization for Large Language Models
Reference 21
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T16:13:19.955208Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6a645625-2a43-4db3-818a-4bdb75671c5b · outbound
This paper cites Pointer Sentinel Mixture Models.
OstQuant: Refining Large Language Model Quantization with Orthogonal and Scaling Transformations for Better Distribution Fitting Pointer Sentinel Mixture Models
Reference 22
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T16:13:19.958622Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 01b1de57-5097-44b0-b57e-c2821d653482 · outbound
This paper cites Can a Suit of Armor Conduct Electricity? A New Dataset for Open Book Question Answering.
OstQuant: Refining Large Language Model Quantization with Orthogonal and Scaling Transformations for Better Distribution Fitting Can a Suit of Armor Conduct Electricity? A New Dataset for Open Book Question Answering
Reference 23
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T16:13:19.961767Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7c0038c3-37cd-4fd9-bc2c-522ec5ac7ffc · outbound
This paper cites Language models are unsupervised multitask learners.
OstQuant: Refining Large Language Model Quantization with Orthogonal and Scaling Transformations for Better Distribution Fitting Language models are unsupervised multitask learners
Reference 24
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T16:13:19.964432Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1fd6c393-d5d7-46df-b17d-270372abe28d · outbound
This paper cites Winogrande: An adversarial winograd schema challenge at scale.
OstQuant: Refining Large Language Model Quantization with Orthogonal and Scaling Transformations for Better Distribution Fitting Winogrande: An adversarial winograd schema challenge at scale
Reference 25
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T16:13:20.404531Z
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 67d41117-7f90-49cc-8211-4eeed2a23e34 · outbound
This paper cites SocialIQA: Commonsense Reasoning about Social Interactions.
OstQuant: Refining Large Language Model Quantization with Orthogonal and Scaling Transformations for Better Distribution Fitting SocialIQA: Commonsense Reasoning about Social Interactions
Reference 26
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T16:13:19.969429Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation df928ba2-f7dc-455a-b9b7-4c19c81a4607 · outbound
This paper cites OmniQuant: Omnidirectionally Calibrated Quantization for Large Language Models.
OstQuant: Refining Large Language Model Quantization with Orthogonal and Scaling Transformations for Better Distribution Fitting OmniQuant: Omnidirectionally Calibrated Quantization for Large Language Models
Reference 27
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T16:13:19.972488Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 90b7234d-c566-4752-880b-594c5e760a1d · outbound
This paper cites LLaMA: Open and Efficient Foundation Language Models.
OstQuant: Refining Large Language Model Quantization with Orthogonal and Scaling Transformations for Better Distribution Fitting LLaMA: Open and Efficient Foundation Language Models
Reference 28
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T16:13:19.975474Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 71a20098-ff60-41a4-bd5f-56be22d2b7a0 · outbound
This paper cites Llama 2: Open Foundation and Fine-Tuned Chat Models.
OstQuant: Refining Large Language Model Quantization with Orthogonal and Scaling Transformations for Better Distribution Fitting Llama 2: Open Foundation and Fine-Tuned Chat Models
Reference 29
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T16:13:19.978710Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6537f63c-1669-4b9b-a292-4bb7a9402611 · outbound
This paper cites QuIP#: Even Better LLM Quantization with Hadamard Incoherence and Lattice Codebooks.
OstQuant: Refining Large Language Model Quantization with Orthogonal and Scaling Transformations for Better Distribution Fitting QuIP#: Even Better LLM Quantization with Hadamard Incoherence and Lattice Codebooks
Reference 30
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T16:13:19.981883Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a8e874f3-822b-48d7-af15-c9534422461c · outbound
This paper cites SmoothQuant: Accurate and Efficient Post-Training Quantization for Large Language Models.
OstQuant: Refining Large Language Model Quantization with Orthogonal and Scaling Transformations for Better Distribution Fitting SmoothQuant: Accurate and Efficient Post-Training Quantization for Large Language Models
Reference 31
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T16:13:19.985136Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d1c187c5-2f9a-4c8e-b164-77642734c8de · outbound
This paper cites ZeroQuant: Efficient and Affordable Post-Training Quantization for Large-Scale Transformers.
OstQuant: Refining Large Language Model Quantization with Orthogonal and Scaling Transformations for Better Distribution Fitting ZeroQuant: Efficient and Affordable Post-Training Quantization for Large-Scale Transformers
Reference 32
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T16:13:19.988135Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1e4030b3-c143-4615-9710-868a7e384154 · outbound
This paper cites HellaSwag: Can a Machine Really Finish Your Sentence?.
OstQuant: Refining Large Language Model Quantization with Orthogonal and Scaling Transformations for Better Distribution Fitting HellaSwag: Can a Machine Really Finish Your Sentence?
Reference 33
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T16:13:19.991146Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ff7a0792-c45d-43dd-beb7-3ba3753d3629 · outbound
This paper cites write newline.
Reference 34
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T16:13:19.994255Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 68bf4dff-eb60-4194-876c-414bde825a80 · outbound
This paper cites @esa (Ref.
Reference 35
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T16:13:19.998256Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 853873af-147e-4eea-bcc5-073c0c79443f · outbound
This paper cites an unresolved cited work.
OstQuant: Refining Large Language Model Quantization with Orthogonal and Scaling Transformations for Better Distribution Fitting Unresolved cited work
Reference 36
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T16:13:20.001515Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 72d7de02-d8d0-49d8-94a9-0dbc2585bd05 · outbound
This paper cites an unresolved cited work.
OstQuant: Refining Large Language Model Quantization with Orthogonal and Scaling Transformations for Better Distribution Fitting Unresolved cited work
Reference 37
- Resolution
- malformed identifier
- no resolver link, observed 2026-08-10T16:13:20.004756Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Pith citing papers
Observation 5fe2956b-78de-4d3e-ba8c-ce8102e30ea0 · inbound
DFRot: Achieving Outlier-Free and Massive Activation-Free for Rotated LLMs with Refined Rotation cites this paper.
DFRot: Achieving Outlier-Free and Massive Activation-Free for Rotated LLMs with Refined Rotation OstQuant: Refining Large Language Model Quantization with Orthogonal and Scaling Transformations for Better Distribution Fitting
Reference 2020
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T05:20:23.849109Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a559fc8b-f7ee-40ab-b741-7b5fc3d2db5f · inbound
MQuant: Unleashing the Inference Potential of Multimodal Large Language Models via Full Static Quantization cites this paper.
MQuant: Unleashing the Inference Potential of Multimodal Large Language Models via Full Static Quantization OstQuant: Refining Large Language Model Quantization with Orthogonal and Scaling Transformations for Better Distribution Fitting
Reference 27
- Resolution
- unresolved
- no resolver link, observed 2026-08-09T19:12:56.082348Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 76dddf82-afb5-4854-bccc-a09f17123e90 · 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 OstQuant: Refining Large Language Model Quantization with Orthogonal and Scaling Transformations for Better Distribution Fitting
Reference 7
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:50:06.797957Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 67e9cea5-60b0-4f83-a1c7-19a6a6315861 · inbound
NSNQuant: A Double Normalization Approach for Calibration-Free Low-Bit Vector Quantization of KV Cache cites this paper.
NSNQuant: A Double Normalization Approach for Calibration-Free Low-Bit Vector Quantization of KV Cache OstQuant: Refining Large Language Model Quantization with Orthogonal and Scaling Transformations for Better Distribution Fitting
Reference 20
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:42:20.965959Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d79a8ae5-d216-42f4-a1ae-10e1599b4b39 · inbound
TAH-QUANT: Effective Activation Quantization in Pipeline Parallelism over Slow Network cites this paper.
TAH-QUANT: Effective Activation Quantization in Pipeline Parallelism over Slow Network OstQuant: Refining Large Language Model Quantization with Orthogonal and Scaling Transformations for Better Distribution Fitting
Reference 43
- Resolution
- verified exact
- arxiv_id, observed 2026-05-19T11:27:15.970801Z
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 4f427d71-a399-4caf-ab73-9d9024678da8 · inbound
PCDVQ: Enhancing Vector Quantization for Large Language Models via Polar Coordinate Decoupling cites this paper.
PCDVQ: Enhancing Vector Quantization for Large Language Models via Polar Coordinate Decoupling OstQuant: Refining Large Language Model Quantization with Orthogonal and Scaling Transformations for Better Distribution Fitting
Reference 15
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T10:42:40.948535Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9c216eaf-d8bd-49af-87fe-7753206914e9 · inbound
BTC-LLM: Efficient Sub-1-Bit LLM Quantization via Learnable Transformation and Binary Codebook cites this paper.
BTC-LLM: Efficient Sub-1-Bit LLM Quantization via Learnable Transformation and Binary Codebook OstQuant: Refining Large Language Model Quantization with Orthogonal and Scaling Transformations for Better Distribution Fitting
Reference 10
- Resolution
- verified exact
- arxiv_id, observed 2026-05-19T14:07:20.549231Z
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 6d56403d-f536-4b30-b255-95fc7fe68239 · inbound
BASE-Q: Bias and Asymmetric Scaling Enhanced Rotational Quantization for Large Language Models cites this paper.
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 332b1750-a916-408a-9724-90631d4a2c20 · inbound
QuantVLA: Scale-Calibrated Post-Training Quantization for Vision-Language-Action Models cites this paper.
QuantVLA: Scale-Calibrated Post-Training Quantization for Vision-Language-Action Models OstQuant: Refining Large Language Model Quantization with Orthogonal and Scaling Transformations for Better Distribution Fitting
Reference 11
- Resolution
- verified exact
- arxiv_id, observed 2026-05-15T20:20:17.353194Z
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 7a238a67-7853-49d2-9596-37552a95dd6b · inbound
CoQuant: Joint Weight-Activation Subspace Projection for Mixed-Precision LLMs cites this paper.
CoQuant: Joint Weight-Activation Subspace Projection for Mixed-Precision LLMs OstQuant: Refining Large Language Model Quantization with Orthogonal and Scaling Transformations for Better Distribution Fitting
Reference 6
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-12T08:51:24.365884Z
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 9d909944-23ac-45db-bc4c-45acc74a9ede · inbound
LoopQ: Quantization for Recursive Transformers cites this paper.
LoopQ: Quantization for Recursive Transformers OstQuant: Refining Large Language Model Quantization with Orthogonal and Scaling Transformations for Better Distribution Fitting
Reference 14
- Resolution
- verified exact
- arxiv_id, observed 2026-05-20T22:43:50.823348Z
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 1f2f61f0-e9d5-4cf8-9ad8-f9a6ec79edf2 · inbound
GAMMA: Global Bit Allocation for Mixed-Precision Models under Arbitrary Budgets cites this paper.
GAMMA: Global Bit Allocation for Mixed-Precision Models under Arbitrary Budgets OstQuant: Refining Large Language Model Quantization with Orthogonal and Scaling Transformations for Better Distribution Fitting
Reference 49
- Resolution
- verified exact
- arxiv_id, observed 2026-05-20T12:28:16.794228Z
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 f79f4af6-d087-43fc-9b2f-f646131dfb32 · inbound
Theory-optimal Quantization Based on Flatness cites this paper.
Theory-optimal Quantization Based on Flatness OstQuant: Refining Large Language Model Quantization with Orthogonal and Scaling Transformations for Better Distribution Fitting
Reference 6
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-20T22:39:09.902771Z
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 b600cc3a-2a90-4409-8fc9-e66fa77b68e6 · inbound
Breaking Modality Heterogeneity in Low-Bit Quantization for Large Vision-Language Models cites this paper.
Breaking Modality Heterogeneity in Low-Bit Quantization for Large Vision-Language Models OstQuant: Refining Large Language Model Quantization with Orthogonal and Scaling Transformations for Better Distribution Fitting
Reference 19
- Resolution
- verified exact
- arxiv_id, observed 2026-05-20T05:23:03.619341Z
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 af2a470a-7516-4cd6-93cf-417adf65cc40 · inbound
MGVQ: Synergizing Multi-dimensional Sensitivity-Aware and Gradient-Hessian Fusion for Vector Quantization cites this paper.
MGVQ: Synergizing Multi-dimensional Sensitivity-Aware and Gradient-Hessian Fusion for Vector Quantization OstQuant: Refining Large Language Model Quantization with Orthogonal and Scaling Transformations for Better Distribution Fitting
Reference 5
- Resolution
- verified exact
- arxiv_id, observed 2026-07-01T15:05:48.333381Z
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 6a58618d-e155-46f8-80b3-7768f06d4160 · inbound
HoloQ-VLA: Uniform W4A4 Quantization of Vision-Language-Action Models cites this paper.
HoloQ-VLA: Uniform W4A4 Quantization of Vision-Language-Action Models OstQuant: Refining Large Language Model Quantization with Orthogonal and Scaling Transformations for Better Distribution Fitting
Reference 4
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-06-29T12:53:26.946776Z
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 83fea8c0-1853-41f1-94ad-521d2a547e1a · inbound
MixFP4: Enhancing NVFP4 with Adaptive FP4/INT4 Block Representations cites this paper.
MixFP4: Enhancing NVFP4 with Adaptive FP4/INT4 Block Representations OstQuant: Refining Large Language Model Quantization with Orthogonal and Scaling Transformations for Better Distribution Fitting
Reference 11
- Resolution
- verified exact
- arxiv_id, observed 2026-06-28T20:22:37.216780Z
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 7542aa95-3ac1-4b1c-8cea-3e8ba3d8b8e6 · inbound
OrbitQuant: Data-Agnostic Quantization for Image and Video Diffusion Transformers cites this paper.
OrbitQuant: Data-Agnostic Quantization for Image and Video Diffusion Transformers OstQuant: Refining Large Language Model Quantization with Orthogonal and Scaling Transformations for Better Distribution Fitting
Reference 18
- Resolution
- verified exact
- arxiv_id, observed 2026-07-03T14:58:32.376068Z
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 eb0e06c6-54a2-4af6-843d-8aee223ec01b · inbound
KronQ: LLM Quantization via Kronecker-Factored Hessian cites this paper.
KronQ: LLM Quantization via Kronecker-Factored Hessian OstQuant: Refining Large Language Model Quantization with Orthogonal and Scaling Transformations for Better Distribution Fitting
Reference 13
- Resolution
- verified exact
- local_arxiv, observed 2026-07-10T14:47:14.543000Z
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 ba66d4ad-6293-4e9e-ad0b-b288e8cebc40 · inbound
Break Through the Compression Bottleneck: From Theory to Practice cites this paper.
Break Through the Compression Bottleneck: From Theory to Practice OstQuant: Refining Large Language Model Quantization with Orthogonal and Scaling Transformations for Better Distribution Fitting
Reference 81
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T14:29:36.125062Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a0da8510-6be4-4114-a83f-c86f6c1a7264 · inbound
GyRot: Leveraging Hidden Synergy between Rotation and Fine-grained Group Quantization for Low-bit LLM Inference cites this paper.
GyRot: Leveraging Hidden Synergy between Rotation and Fine-grained Group Quantization for Low-bit LLM Inference OstQuant: Refining Large Language Model Quantization with Orthogonal and Scaling Transformations for Better Distribution Fitting
Reference 17
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T03:16:46.815346Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ab679e37-2974-4fad-ac33-4266e21ecace · inbound
When Local Variance Optimality Is Not Enough: RoPE-Aligned Q/K Rotations for Dynamic 4-Bit Quantisation cites this paper.
When Local Variance Optimality Is Not Enough: RoPE-Aligned Q/K Rotations for Dynamic 4-Bit Quantisation OstQuant: Refining Large Language Model Quantization with Orthogonal and Scaling Transformations for Better Distribution Fitting
Reference 17
- Resolution
- unresolved
- no resolver link, observed 2026-08-14T12:54:26.511410Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.