Paper Citation Record · LEDGER

Pushing the Limits of Large Language Model Quantization via the Linearity Theorem

As of 14 August 2026, this Paper Citation Record lists 50 of 50 outbound references and 7 inbound Pith citation observations for arXiv:2411.17525.

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

pith.paper-citation-record.v1
2411.17525 v1

Coverage vector

measured 50 of 50 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T12:07:30.282490Z

measured 57 of 57 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T20:34:01.289119Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T10:29:45.503006Z

Reference resolution

50 of 50 outbound references displayed

verified exact2
verified fuzzy0
unresolved47
parse uncertain0
malformed identifier0
metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 8e931ca6-7b20-4c6a-8757-1ed6a701140d · outbound

This paper cites an unresolved cited work.

Pushing the Limits of Large Language Model Quantization via the Linearity Theorem Unresolved cited work

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-12T12:07:30.084631Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cd9ef3cf-4c20-4eec-bbe1-ccf891b2d264 · outbound

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

Pushing the Limits of Large Language Model Quantization via the Linearity Theorem QuaRot: Outlier-Free 4-Bit Inference in Rotated LLMs

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-12T12:07:30.089789Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9b1e3c6a-8c52-4a8c-8d63-19d25f3a233b · outbound

This paper cites an unresolved cited work.

Pushing the Limits of Large Language Model Quantization via the Linearity Theorem Unresolved cited work

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-12T12:07:30.094572Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b39b94d3-7e74-404b-b65e-122b9f7c3a9b · outbound

This paper cites Qwen Technical Report.

Pushing the Limits of Large Language Model Quantization via the Linearity Theorem Qwen Technical Report

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-12T12:07:30.098277Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation eb61a05d-453e-4ee5-8f08-02196e7215cd · outbound

This paper cites QuIP: 2-Bit Quantization of Large Language Models With Guarantees.

Pushing the Limits of Large Language Model Quantization via the Linearity Theorem QuIP: 2-Bit Quantization of Large Language Models With Guarantees

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-12T12:07:30.102279Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3539d07e-54da-42dd-89c9-cf4862405e5f · outbound

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

Pushing the Limits of Large Language Model Quantization via the Linearity Theorem Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-12T12:07:30.106544Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b10bcbcf-b2ac-4285-b821-b1c81616c9b6 · outbound

This paper cites New Bounds For Distributed Mean Estimation and Variance Reduction.

Pushing the Limits of Large Language Model Quantization via the Linearity Theorem New Bounds For Distributed Mean Estimation and Variance Reduction

Reference 7

Resolution: verified exact; local_arxiv, observed 2026-08-12T12:07:30.689890Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 25d5f7d4-c903-4678-a3e6-d34c4ec54ae3 · outbound

This paper cites an unresolved cited work.

Pushing the Limits of Large Language Model Quantization via the Linearity Theorem Unresolved cited work

Reference 8

Resolution: unresolved; raw_fallback, observed 2026-08-12T12:07:30.859827Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 5077b3cc-9a4a-41df-9db4-ca61e7efb6e8 · outbound

This paper cites QLoRA: Efficient Finetuning of Quantized LLMs.

Pushing the Limits of Large Language Model Quantization via the Linearity Theorem QLoRA: Efficient Finetuning of Quantized LLMs

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-12T12:07:30.119506Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 30de5264-e0ff-415c-a055-75eb5ceffd8f · outbound

This paper cites SpQR: A Sparse-Quantized Representation for Near-Lossless LLM Weight Compression.

Pushing the Limits of Large Language Model Quantization via the Linearity Theorem SpQR: A Sparse-Quantized Representation for Near-Lossless LLM Weight Compression

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-12T12:07:30.124299Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9f5544af-0a08-4f33-a644-cc588d639a2c · outbound

This paper cites an unresolved cited work.

Pushing the Limits of Large Language Model Quantization via the Linearity Theorem Unresolved cited work

Reference 11

Resolution: unresolved; raw_fallback, observed 2026-08-12T12:07:30.846789Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation c7fc47a2-7626-4146-8fcf-88264558226c · outbound

This paper cites The case for 4-bit precision: k-bit Inference Scaling Laws.

Pushing the Limits of Large Language Model Quantization via the Linearity Theorem The case for 4-bit precision: k-bit Inference Scaling Laws

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-12T12:07:30.132120Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0006d9b4-06c8-4e03-b297-605716482785 · outbound

This paper cites The Llama 3 Herd of Models.

Pushing the Limits of Large Language Model Quantization via the Linearity Theorem The Llama 3 Herd of Models

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-12T12:07:30.135705Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ff19f2ad-17a8-454f-81c1-bed1deb2ca6f · outbound

This paper cites Extreme Compression of Large Language Models via Additive Quantization.

Pushing the Limits of Large Language Model Quantization via the Linearity Theorem Extreme Compression of Large Language Models via Additive Quantization

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-12T12:07:30.139505Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8e39312b-8a66-43f7-adae-30a2ee1fee76 · outbound

This paper cites SPDY: Accurate Pruning with Speedup Guarantees.

Pushing the Limits of Large Language Model Quantization via the Linearity Theorem SPDY: Accurate Pruning with Speedup Guarantees

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-12T12:07:30.143185Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b479fa4d-c00a-432f-ad42-855d461521a3 · outbound

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

Pushing the Limits of Large Language Model Quantization via the Linearity Theorem GPTQ: Accurate Post-Training Quantization for Generative Pre-trained Transformers

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-12T12:07:30.147064Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bae30d21-2384-42e1-abe4-7ed254df34aa · outbound

This paper cites MARLIN: Mixed-Precision Auto-Regressive Parallel Inference on Large Language Models.

Pushing the Limits of Large Language Model Quantization via the Linearity Theorem MARLIN: Mixed-Precision Auto-Regressive Parallel Inference on Large Language Models

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-12T12:07:30.150804Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c94f01cd-473e-477b-9b60-602e2acb6f47 · outbound

This paper cites an unresolved cited work.

Pushing the Limits of Large Language Model Quantization via the Linearity Theorem Unresolved cited work

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-12T12:07:30.155084Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 874cb9a2-565f-427a-82af-fd0c6a853de7 · outbound

This paper cites A Survey of Quantization Methods for Efficient Neural Network Inference.

Pushing the Limits of Large Language Model Quantization via the Linearity Theorem A Survey of Quantization Methods for Efficient Neural Network Inference

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-12T12:07:30.158934Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0a5f54e7-d482-4d2c-bca2-bcd15536d4c9 · outbound

This paper cites Fast Matrix Multiplications for Lookup Table-Quantized LLMs.

Pushing the Limits of Large Language Model Quantization via the Linearity Theorem Fast Matrix Multiplications for Lookup Table-Quantized LLMs

Reference 20

Resolution: verified exact; local_arxiv, observed 2026-08-12T12:07:30.572708Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 9c02e29a-74bc-41e1-b3f4-ead42b8a1f00 · outbound

This paper cites Measuring Massive Multitask Language Understanding.

Pushing the Limits of Large Language Model Quantization via the Linearity Theorem Measuring Massive Multitask Language Understanding

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-12T12:07:30.166853Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2944c500-c29d-442f-b280-76f842316fb5 · outbound

This paper cites SqueezeLLM: Dense-and-Sparse Quantization.

Pushing the Limits of Large Language Model Quantization via the Linearity Theorem SqueezeLLM: Dense-and-Sparse Quantization

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-12T12:07:30.170714Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 81ab99ba-97cb-4ae9-b6c5-eb9ecfe98788 · outbound

This paper cites Gonzalez, Hao Zhang, and Ion Stoica.

Pushing the Limits of Large Language Model Quantization via the Linearity Theorem Gonzalez, Hao Zhang, and Ion Stoica

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-12T12:07:30.174567Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation de9f2010-1148-4651-b1f2-d76f010f89b6 · outbound

This paper cites OWQ: Outlier-Aware Weight Quantization for Efficient Fine-Tuning and Inference of Large Language Models.

Pushing the Limits of Large Language Model Quantization via the Linearity Theorem OWQ: Outlier-Aware Weight Quantization for Efficient Fine-Tuning and Inference of Large Language Models

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-12T12:07:30.178086Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f0d16a36-4a7b-417a-ab6e-6c5a67b6e53c · outbound

This paper cites AWQ: Activation-aware Weight Quantization for LLM Compression and Acceleration.

Pushing the Limits of Large Language Model Quantization via the Linearity Theorem AWQ: Activation-aware Weight Quantization for LLM Compression and Acceleration

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-12T12:07:30.181926Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1b52193c-b804-4f98-afe0-6f7ffac0498d · outbound

This paper cites SpinQuant: LLM quantization with learned rotations.

Pushing the Limits of Large Language Model Quantization via the Linearity Theorem SpinQuant: LLM quantization with learned rotations

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-12T12:07:30.186121Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e7b03015-bed8-46fe-aa28-4d2cd2b48f6b · outbound

This paper cites Pointer Sentinel Mixture Models.

Pushing the Limits of Large Language Model Quantization via the Linearity Theorem Pointer Sentinel Mixture Models

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-12T12:07:30.193833Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6e6b4b6a-87e1-48e0-828c-8873a1046dc7 · outbound

This paper cites an unresolved cited work.

Pushing the Limits of Large Language Model Quantization via the Linearity Theorem Unresolved cited work

Reference 29

Resolution: unresolved; raw_fallback, observed 2026-08-12T12:07:30.828305Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation a27bc9cb-8365-45a3-a9e0-79a85bc36245 · outbound

This paper cites an unresolved cited work.

Pushing the Limits of Large Language Model Quantization via the Linearity Theorem Unresolved cited work

Reference 30

Resolution: unresolved; raw_fallback, observed 2026-08-12T12:07:30.816308Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation dc93881d-8e8d-4a22-9d54-0eaca56cdc63 · outbound

This paper cites LUT-GEMM: Quantized Matrix Multiplication based on LUTs for Efficient Inference in Large-Scale Generative Language Models.

Pushing the Limits of Large Language Model Quantization via the Linearity Theorem LUT-GEMM: Quantized Matrix Multiplication based on LUTs for Efficient Inference in Large-Scale Generative Language Models

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-12T12:07:30.204508Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 45c72733-76ad-4009-9971-acdd63cb1129 · outbound

This paper cites an unresolved cited work.

Pushing the Limits of Large Language Model Quantization via the Linearity Theorem Unresolved cited work

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-12T12:07:30.208108Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6d528b8a-5230-4e4d-970f-026ec6b1af1d · outbound

This paper cites an unresolved cited work.

Pushing the Limits of Large Language Model Quantization via the Linearity Theorem Unresolved cited work

Reference 33

Resolution: unresolved; raw_fallback, observed 2026-08-12T12:07:30.797729Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 333c96cf-9aea-4074-8694-983832cf2a42 · outbound

This paper cites an unresolved cited work.

Pushing the Limits of Large Language Model Quantization via the Linearity Theorem Unresolved cited work

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-12T12:07:30.216197Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4fc34261-3b22-415d-8261-5c19164091e0 · outbound

This paper cites Distributed Mean Estimation with Limited Communication.

Pushing the Limits of Large Language Model Quantization via the Linearity Theorem Distributed Mean Estimation with Limited Communication

Reference 35

Resolution: metadata mismatch; local_arxiv, observed 2026-08-12T12:07:30.470908Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation b3061b82-c5c0-4cdb-8cb3-c682b9622fa0 · outbound

This paper cites an unresolved cited work.

Pushing the Limits of Large Language Model Quantization via the Linearity Theorem Unresolved cited work

Reference 36

Resolution: unresolved; raw_fallback, observed 2026-08-12T12:07:30.785313Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation bf461b08-9a23-4f36-ae2f-beaabd37830b · outbound

This paper cites an unresolved cited work.

Pushing the Limits of Large Language Model Quantization via the Linearity Theorem Unresolved cited work

Reference 37

Resolution: unresolved; raw_fallback, observed 2026-08-12T12:07:30.773067Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 17d524fe-736b-4d72-921d-460b2db5530e · outbound

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

Pushing the Limits of Large Language Model Quantization via the Linearity Theorem QuIP#: Even Better LLM Quantization with Hadamard Incoherence and Lattice Codebooks

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-12T12:07:30.231141Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2a8598c7-5839-49c6-becd-12b696923a07 · outbound

This paper cites QTIP: Quantization with Trellises and Incoherence Processing.

Pushing the Limits of Large Language Model Quantization via the Linearity Theorem QTIP: Quantization with Trellises and Incoherence Processing

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-12T12:07:30.234824Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f44b096f-0126-4412-8715-8e70487c6e83 · outbound

This paper cites GPTVQ: The Blessing of Dimensionality for LLM Quantization.

Pushing the Limits of Large Language Model Quantization via the Linearity Theorem GPTVQ: The Blessing of Dimensionality for LLM Quantization

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-12T12:07:30.238902Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 37994103-658c-4d4d-b324-61ea3983cde8 · outbound

This paper cites DRIVE: One-bit Distributed Mean Estimation.

Pushing the Limits of Large Language Model Quantization via the Linearity Theorem DRIVE: One-bit Distributed Mean Estimation

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-12T12:07:30.242741Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f0226074-94dc-4eba-8178-2a37740906e0 · outbound

This paper cites EDEN: Communication-Efficient and Robust Distributed Mean Estimation for Federated Learning.

Pushing the Limits of Large Language Model Quantization via the Linearity Theorem EDEN: Communication-Efficient and Robust Distributed Mean Estimation for Federated Learning

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-12T12:07:30.246967Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aae0845c-0b73-4211-8c8d-d97f2e12bd39 · outbound

This paper cites an unresolved cited work.

Pushing the Limits of Large Language Model Quantization via the Linearity Theorem Unresolved cited work

Reference 43

Resolution: unresolved; raw_fallback, observed 2026-08-12T12:07:30.761743Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation f1f6c9aa-6529-458e-96d3-e75f2c1c536c · outbound

This paper cites FP6-LLM: Efficiently Serving Large Language Models Through FP6-Centric Algorithm-System Co-Design.

Pushing the Limits of Large Language Model Quantization via the Linearity Theorem FP6-LLM: Efficiently Serving Large Language Models Through FP6-Centric Algorithm-System Co-Design

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-12T12:07:30.254327Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9015d2e5-5189-4571-abb4-2871b0e365e5 · outbound

This paper cites ZeroQuant: Efficient and Affordable Post-Training Quantization for Large-Scale Transformers.

Pushing the Limits of Large Language Model Quantization via the Linearity Theorem ZeroQuant: Efficient and Affordable Post-Training Quantization for Large-Scale Transformers

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-12T12:07:30.258416Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f5c7acba-c9af-4b5d-a774-2f36e9dc24ba · outbound

This paper cites Outlier Weighed Layerwise Sparsity (OWL): A Missing Secret Sauce for Pruning LLMs to High Sparsity.

Pushing the Limits of Large Language Model Quantization via the Linearity Theorem Outlier Weighed Layerwise Sparsity (OWL): A Missing Secret Sauce for Pruning LLMs to High Sparsity

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-12T12:07:30.262218Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 12283b9e-4a4e-4c96-8559-9caae4e85edd · outbound

This paper cites NF4 Isn't Information Theoretically Optimal (and that's Good).

Pushing the Limits of Large Language Model Quantization via the Linearity Theorem NF4 Isn't Information Theoretically Optimal (and that's Good)

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-12T12:07:30.266478Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 81f70250-5938-4f27-b9cd-df7b122b723f · outbound

This paper cites an unresolved cited work.

Pushing the Limits of Large Language Model Quantization via the Linearity Theorem Unresolved cited work

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-12T12:07:30.270394Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7bed2eb8-17e9-4f9a-9a1b-1a4dc8253917 · outbound

This paper cites OPT: Open Pre-trained Transformer Language Models.

Pushing the Limits of Large Language Model Quantization via the Linearity Theorem OPT: Open Pre-trained Transformer Language Models

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-12T12:07:30.274074Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 665598d1-cad2-4c77-b593-78ad8b2f88f9 · outbound

This paper cites online" 'onlinestring :=.

Pushing the Limits of Large Language Model Quantization via the Linearity Theorem online" 'onlinestring :=

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-12T12:07:30.277992Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ca5e6263-3184-4fe6-a383-540e4005972c · outbound

This paper cites write newline.

Pushing the Limits of Large Language Model Quantization via the Linearity Theorem write newline

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-12T12:07:30.282490Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation f0f3d9b0-5619-4ccf-a814-6d412e9edcfc · inbound

Cache Me If You Must: Adaptive Key-Value Quantization for Large Language Models cites this paper.

Cache Me If You Must: Adaptive Key-Value Quantization for Large Language Models Pushing the Limits of Large Language Model Quantization via the Linearity Theorem

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-09T20:34:01.289119Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 26d22641-5be1-453b-bcca-af9996668f5f · inbound

CE-LoRA: Computation-Efficient LoRA Fine-Tuning for Language Models cites this paper.

CE-LoRA: Computation-Efficient LoRA Fine-Tuning for Language Models Pushing the Limits of Large Language Model Quantization via the Linearity Theorem

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-09T15:36:04.444303Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7660a5e6-f3c7-4897-aecd-a5e13d5e036c · inbound

KV Cache Offloading for Context-Intensive Tasks cites this paper.

KV Cache Offloading for Context-Intensive Tasks Pushing the Limits of Large Language Model Quantization via the Linearity Theorem

Reference 35

Resolution: verified exact; arxiv_id, observed 2026-05-11T08:06:01.042670Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 69b2aa2a-6198-48c1-b62a-6ea3ecd0af6c · inbound

KV Cache Offloading for Context-Intensive Tasks cites this paper.

KV Cache Offloading for Context-Intensive Tasks Pushing the Limits of Large Language Model Quantization via the Linearity Theorem

Reference 35

Resolution: verified exact; arxiv_id, observed 2026-05-11T04:20:56.317662Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation efc361d6-9c2b-4631-9de5-5a2be0490d6e · inbound

KV Cache Offloading for Context-Intensive Tasks cites this paper.

KV Cache Offloading for Context-Intensive Tasks Pushing the Limits of Large Language Model Quantization via the Linearity Theorem

Reference 35

Resolution: verified exact; arxiv_id, observed 2026-05-13T07:37:29.365075Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation a729e4b6-e5e5-43fa-9169-c18a4b781040 · inbound

KV Cache Offloading for Context-Intensive Tasks cites this paper.

KV Cache Offloading for Context-Intensive Tasks Pushing the Limits of Large Language Model Quantization via the Linearity Theorem

Reference 35

Resolution: verified exact; arxiv_id, observed 2026-05-19T16:42:39.689196Z

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Observation f8aab825-e78f-41ce-a5fd-3a528d9b95e3 · inbound

HyperQuant: A Rate-Distortion-Optimal Quantization Pipeline for Large Language and Diffusion Models cites this paper.

HyperQuant: A Rate-Distortion-Optimal Quantization Pipeline for Large Language and Diffusion Models Pushing the Limits of Large Language Model Quantization via the Linearity Theorem

Reference 21

Resolution: verified exact; arxiv_id, observed 2026-07-04T10:29:45.504441Z

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