SqueezeLLM: Dense-and-Sparse Quantization | Paper Citation Record

Observation fe5067cf-dab7-4166-aa91-a11026099e93 · inbound

ASVD: Activation-aware Singular Value Decomposition for Compressing Large Language Models cites this paper.

ASVD: Activation-aware Singular Value Decomposition for Compressing Large Language Models SqueezeLLM: Dense-and-Sparse Quantization

Reference 13

Resolution: metadata mismatch; arxiv_id, observed 2026-05-20T13:49:33.850130Z

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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 652a7ae9-34ed-4e07-bc1c-d8e964f9b301 · inbound

Medusa: Simple LLM Inference Acceleration Framework with Multiple Decoding Heads cites this paper.

Medusa: Simple LLM Inference Acceleration Framework with Multiple Decoding Heads SqueezeLLM: Dense-and-Sparse Quantization

Reference 81

Resolution: metadata mismatch; arxiv_id, observed 2026-05-13T10:36:18.341205Z

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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 37c8d920-1703-41cf-9a2c-069a3b3898ab · inbound

KIVI: A Tuning-Free Asymmetric 2bit Quantization for KV Cache cites this paper.

KIVI: A Tuning-Free Asymmetric 2bit Quantization for KV Cache SqueezeLLM: Dense-and-Sparse Quantization

Reference 10

Resolution: metadata mismatch; arxiv_id, observed 2026-05-12T08:53:12.337562Z

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Observation 8c46ab81-0c82-4bf6-82d4-4f4f738c1f12 · inbound

RouterBench: A Benchmark for Multi-LLM Routing System cites this paper.

RouterBench: A Benchmark for Multi-LLM Routing System SqueezeLLM: Dense-and-Sparse Quantization

Reference 89

Resolution: verified exact; arxiv_id, observed 2026-05-16T10:47:31.094875Z

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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation dc0a389b-ad0f-4564-b0d7-fec01552fe30 · inbound

A Survey on Efficient Inference for Large Language Models cites this paper.

A Survey on Efficient Inference for Large Language Models SqueezeLLM: Dense-and-Sparse Quantization

Reference 197

Resolution: metadata mismatch; arxiv_id, observed 2026-05-15T02:39:33.214075Z

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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation c2b6fba9-5454-4565-b948-54fe9cad1fec · inbound

SpinQuant: LLM quantization with learned rotations cites this paper.

SpinQuant: LLM quantization with learned rotations SqueezeLLM: Dense-and-Sparse Quantization

Reference 8

Resolution: metadata mismatch; arxiv_id, observed 2026-05-15T15:52:34.700791Z

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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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

Pushing the Limits of Large Language Model Quantization via the Linearity Theorem cites this paper.

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

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Observation 7a58fbbb-e45d-483c-9b3b-619bad0672ae · inbound

CPTQuant - A Novel Mixed Precision Post-Training Quantization Techniques for Large Language Models cites this paper.

CPTQuant - A Novel Mixed Precision Post-Training Quantization Techniques for Large Language Models SqueezeLLM: Dense-and-Sparse Quantization

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-11T23:50:28.874894Z

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Observation 7621d1ce-c7a9-4454-835a-11f8a9a705e5 · inbound

SKIM: Any-bit Quantization Pushing The Limits of Post-Training Quantization cites this paper.

SKIM: Any-bit Quantization Pushing The Limits of Post-Training Quantization SqueezeLLM: Dense-and-Sparse Quantization

Reference 2002

Resolution: unresolved; no resolver link, observed 2026-08-11T21:45:16.624860Z

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Observation 04f5fb6c-f226-4659-bf54-4ba5affb2bb7 · inbound

Taming Sensitive Weights : Noise Perturbation Fine-tuning for Robust LLM Quantization cites this paper.

Taming Sensitive Weights : Noise Perturbation Fine-tuning for Robust LLM Quantization SqueezeLLM: Dense-and-Sparse Quantization

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-11T20:08:46.631080Z

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Observation 5194d093-8a59-44b6-8c34-a4f59fa04511 · inbound

ResQ: Mixed-Precision Quantization of Large Language Models with Low-Rank Residuals cites this paper.

ResQ: Mixed-Precision Quantization of Large Language Models with Low-Rank Residuals SqueezeLLM: Dense-and-Sparse Quantization

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-11T12:22:38.853192Z

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Observation 2006d8ae-b07d-40b6-9803-43fa6828a3b0 · inbound

1.58-bit FLUX cites this paper.

1.58-bit FLUX SqueezeLLM: Dense-and-Sparse Quantization

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-11T04:39:36.579296Z

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Observation 7d957495-3395-43b2-b49d-98a464d2b749 · inbound

BlockDialect: Block-wise Fine-grained Mixed Format Quantization for Energy-Efficient LLM Inference cites this paper.

BlockDialect: Block-wise Fine-grained Mixed Format Quantization for Energy-Efficient LLM Inference SqueezeLLM: Dense-and-Sparse Quantization

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-10T22:44:30.128860Z

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Observation 546c6e91-2378-4d7f-b935-d5c1767416df · inbound

FlexQuant: Elastic Quantization Framework for Locally Hosted LLM on Edge Devices cites this paper.

FlexQuant: Elastic Quantization Framework for Locally Hosted LLM on Edge Devices SqueezeLLM: Dense-and-Sparse Quantization

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-10T20:56:20.735632Z

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Observation b321e75c-9bc7-4ccf-b55a-f6121396b34b · inbound

PICE: A Semantic-Driven Progressive Inference System for LLM Serving in Cloud-Edge Networks cites this paper.

PICE: A Semantic-Driven Progressive Inference System for LLM Serving in Cloud-Edge Networks SqueezeLLM: Dense-and-Sparse Quantization

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-10T20:13:43.264913Z

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Observation e4589b22-bab1-4780-bff3-fd0e67da1f41 · inbound

Qrazor: Reliable and Effortless 4-bit LLM Quantization by Significant Data Razoring cites this paper.

Qrazor: Reliable and Effortless 4-bit LLM Quantization by Significant Data Razoring SqueezeLLM: Dense-and-Sparse Quantization

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-10T16:19:57.446387Z

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Observation 8a3ad5eb-fb11-437b-a842-f2b5f1e3381a · inbound

Elucidating Subspace Perturbation in Zeroth-Order Optimization: Theory and Practice at Scale cites this paper.

Elucidating Subspace Perturbation in Zeroth-Order Optimization: Theory and Practice at Scale SqueezeLLM: Dense-and-Sparse Quantization

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-09T21:23:48.574835Z

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Observation 8b308851-e505-4df8-ad27-7ad194f53a52 · inbound

Dobi-SVD: Differentiable SVD for LLM Compression and Some New Perspectives cites this paper.

Dobi-SVD: Differentiable SVD for LLM Compression and Some New Perspectives SqueezeLLM: Dense-and-Sparse Quantization

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-09T11:28:42.183775Z

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Observation 82638e70-4319-4cad-85ea-af7a65b3dd55 · inbound

Lossless Acceleration of Large Language Models with Hierarchical Drafting based on Temporal Locality in Speculative Decoding cites this paper.

Lossless Acceleration of Large Language Models with Hierarchical Drafting based on Temporal Locality in Speculative Decoding SqueezeLLM: Dense-and-Sparse Quantization

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-08T18:42:15.010420Z

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Observation 82fa24fe-d6f5-4e80-a3b1-bf4e25e3196a · inbound

SHARP: Accelerating Language Model Inference by SHaring Adjacent layers with Recovery Parameters cites this paper.

SHARP: Accelerating Language Model Inference by SHaring Adjacent layers with Recovery Parameters SqueezeLLM: Dense-and-Sparse Quantization

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-08T13:44:00.544467Z

Source-reported events for the cited work

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Observation 4eee505b-e77f-4694-be24-ab55ae4e2279 · inbound

On multi-token prediction for efficient LLM inference cites this paper.

On multi-token prediction for efficient LLM inference SqueezeLLM: Dense-and-Sparse Quantization

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-07T21:38:34.760608Z

Source-reported events for the cited work

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Observation 9949b154-5c0b-4936-8e4c-06b655bb5173 · inbound

QuantSpec: Self-Speculative Decoding with Hierarchical Quantized KV Cache cites this paper.

QuantSpec: Self-Speculative Decoding with Hierarchical Quantized KV Cache SqueezeLLM: Dense-and-Sparse Quantization

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-09T04:28:03.938479Z

Source-reported events for the cited work

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Observation a609dd30-4a14-47d9-b2e7-a04c77294da5 · inbound

Will LLMs Scaling Hit the Wall? Breaking Barriers via Distributed Resources on Massive Edge Devices cites this paper.

Will LLMs Scaling Hit the Wall? Breaking Barriers via Distributed Resources on Massive Edge Devices SqueezeLLM: Dense-and-Sparse Quantization

Reference 174

Resolution: metadata mismatch; arxiv_id, observed 2026-05-23T01:05:16.310998Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 52cc938e-9e87-487e-b765-9b181799675b · inbound

FGMP: Fine-Grained Mixed-Precision Weight and Activation Quantization for Hardware-Accelerated LLM Inference cites this paper.

FGMP: Fine-Grained Mixed-Precision Weight and Activation Quantization for Hardware-Accelerated LLM Inference SqueezeLLM: Dense-and-Sparse Quantization

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-16T12:00:43.084578Z

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Observation 96011ff3-6b96-4f6e-86b1-e5309a87cf7c · inbound

TeleSparse: Practical Privacy-Preserving Verification of Deep Neural Networks cites this paper.

TeleSparse: Practical Privacy-Preserving Verification of Deep Neural Networks SqueezeLLM: Dense-and-Sparse Quantization

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-16T06:06:57.425786Z

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Observation 49ef2c4b-10db-4fd8-b047-447b5e02ca89 · inbound

R-Sparse: Rank-Aware Activation Sparsity for Efficient LLM Inference cites this paper.

R-Sparse: Rank-Aware Activation Sparsity for Efficient LLM Inference SqueezeLLM: Dense-and-Sparse Quantization

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-16T05:58:46.632513Z

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Observation 8c4c853e-fc2a-4b1b-b7df-37648d77476c · inbound

FineQ: Software-Hardware Co-Design for Low-Bit Fine-Grained Mixed-Precision Quantization of LLMs cites this paper.

FineQ: Software-Hardware Co-Design for Low-Bit Fine-Grained Mixed-Precision Quantization of LLMs SqueezeLLM: Dense-and-Sparse Quantization

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-16T05:52:21.244939Z

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Observation e28853ba-9226-4caf-bf9b-35df3a4991a8 · inbound

TurboQuant: Online Vector Quantization with Near-optimal Distortion Rate cites this paper.

TurboQuant: Online Vector Quantization with Near-optimal Distortion Rate SqueezeLLM: Dense-and-Sparse Quantization

Reference 37

Resolution: verified exact; arxiv_id, observed 2026-05-20T08:09:22.277661Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation a965507b-7a49-44ba-a3a6-67f775b63726 · inbound

ICQuant: Index Coding enables Low-bit LLM Quantization cites this paper.

ICQuant: Index Coding enables Low-bit LLM Quantization SqueezeLLM: Dense-and-Sparse Quantization

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-16T04:43:49.735389Z

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Observation 929dcb5e-aab5-4020-aca7-84de10b3c0bc · inbound

EntroLLM: Entropy Encoded Weight Compression for Efficient Large Language Model Inference on Edge Devices cites this paper.

EntroLLM: Entropy Encoded Weight Compression for Efficient Large Language Model Inference on Edge Devices SqueezeLLM: Dense-and-Sparse Quantization

Reference 10

Resolution: metadata mismatch; arxiv_id, observed 2026-05-22T16:34:59.261977Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 47088b09-0a0a-4c35-a053-7c53473f74be · inbound

MoEQuant: Enhancing Quantization for Mixture-of-Experts Large Language Models via Expert-Balanced Sampling and Affinity Guidance cites this paper.

MoEQuant: Enhancing Quantization for Mixture-of-Experts Large Language Models via Expert-Balanced Sampling and Affinity Guidance SqueezeLLM: Dense-and-Sparse Quantization

Reference 1994

Resolution: unresolved; no resolver link, observed 2026-08-16T04:31:56.870632Z

Source-reported events for the cited work

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Observation 41c61031-866a-4907-bf8c-50104bd6c46d · inbound

MxMoE: Mixed-precision Quantization for MoE with Accuracy and Performance Co-Design cites this paper.

MxMoE: Mixed-precision Quantization for MoE with Accuracy and Performance Co-Design SqueezeLLM: Dense-and-Sparse Quantization

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-15T23:01:20.100645Z

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Observation bfaae37a-2dbb-4bac-9dff-6cb3a04119de · inbound

Ecco: Improving Memory Bandwidth and Capacity for LLMs via Entropy-aware Cache Compression cites this paper.

Ecco: Improving Memory Bandwidth and Capacity for LLMs via Entropy-aware Cache Compression SqueezeLLM: Dense-and-Sparse Quantization

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-15T22:36:42.294573Z

Source-reported events for the cited work

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Observation 776bbb39-0683-4ba8-a428-617b2fe31cc3 · inbound

Dual Precision Quantization for Efficient and Accurate Deep Neural Networks Inference cites this paper.

Dual Precision Quantization for Efficient and Accurate Deep Neural Networks Inference SqueezeLLM: Dense-and-Sparse Quantization

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-07T15:36:05.656359Z

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Observation 61b27dfa-542c-4af4-b9dc-1325f222f8d7 · inbound

NQKV: A KV Cache Quantization Scheme Based on Normal Distribution Characteristics cites this paper.

NQKV: A KV Cache Quantization Scheme Based on Normal Distribution Characteristics SqueezeLLM: Dense-and-Sparse Quantization

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-07T15:09:28.498086Z

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Observation c33b91b4-7076-4fed-839a-2d4ea3d92494 · 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 SqueezeLLM: Dense-and-Sparse Quantization

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-07T14:42:21.069575Z

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Observation 522070b8-6cf0-4e0d-a01a-26bae17ff451 · inbound

Can Compressed LLMs Truly Act? An Empirical Evaluation of Agentic Capabilities in LLM Compression cites this paper.

Can Compressed LLMs Truly Act? An Empirical Evaluation of Agentic Capabilities in LLM Compression SqueezeLLM: Dense-and-Sparse Quantization

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-07T14:17:56.372336Z

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Observation d2d1cc3b-7958-4a42-afa3-9fa22aa93fd5 · inbound

Can Compressed LLMs Truly Act? An Empirical Evaluation of Agentic Capabilities in LLM Compression cites this paper.

Can Compressed LLMs Truly Act? An Empirical Evaluation of Agentic Capabilities in LLM Compression SqueezeLLM: Dense-and-Sparse Quantization

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-07T14:17:56.464514Z

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Observation 8667e534-2518-4bf2-954d-47bdcf62d9c7 · inbound

FPTQuant: Function-Preserving Transforms for LLM Quantization cites this paper.

FPTQuant: Function-Preserving Transforms for LLM Quantization SqueezeLLM: Dense-and-Sparse Quantization

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-07T10:43:46.395454Z

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Observation 35aa94be-e2a4-4b81-aa83-0b824d01744a · inbound

BAQ: Efficient Bit Allocation Quantization for Large Language Models cites this paper.

BAQ: Efficient Bit Allocation Quantization for Large Language Models SqueezeLLM: Dense-and-Sparse Quantization

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-07T10:18:52.624716Z

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Observation 0c4f7916-3238-492b-bb86-7a95c6562580 · inbound

Attribution-Guided Pruning for Insight and Control: Circuit Discovery and Targeted Correction in Small-scale LLMs cites this paper.

Attribution-Guided Pruning for Insight and Control: Circuit Discovery and Targeted Correction in Small-scale LLMs SqueezeLLM: Dense-and-Sparse Quantization

Reference 16

Resolution: verified exact; arxiv_id, observed 2026-05-19T08:53:04.144810Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 7b9aea9f-f074-4b9c-83ed-13b6c938936a · inbound

Efficient Serving of LLM Applications with Probabilistic Demand Modeling cites this paper.

Efficient Serving of LLM Applications with Probabilistic Demand Modeling SqueezeLLM: Dense-and-Sparse Quantization

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-15T19:59:46.512823Z

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Observation 53dfb406-e291-4a4b-badf-f4e1a106241a · inbound

Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models cites this paper.

Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models SqueezeLLM: Dense-and-Sparse Quantization

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-06T23:00:19.558832Z

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Observation deb9f2da-2284-4ec8-bf66-743303f6bb47 · inbound

Information-Bottleneck Driven Binary Neural Network for Change Detection cites this paper.

Information-Bottleneck Driven Binary Neural Network for Change Detection SqueezeLLM: Dense-and-Sparse Quantization

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-06T20:15:24.158945Z

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Observation 14813428-cb77-415d-9713-4f4d6f3f670b · inbound

CCQ: Convolutional Code for Extreme Low-bit Quantization in LLMs cites this paper.

CCQ: Convolutional Code for Extreme Low-bit Quantization in LLMs SqueezeLLM: Dense-and-Sparse Quantization

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-06T19:09:14.550295Z

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Observation e84da4c0-1e3d-4d94-82c6-e8450d5c288a · inbound

OASIS: Outlier-Aware LUT-Based GEMM with Dual-Side Quantization for LLM Inference Acceleration cites this paper.

OASIS: Outlier-Aware LUT-Based GEMM with Dual-Side Quantization for LLM Inference Acceleration SqueezeLLM: Dense-and-Sparse Quantization

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-06T11:15:33.956446Z

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Observation 7aa8ef5c-c2e7-459f-b440-804064a16c33 · inbound

Quantized but Deceptive? A Multi-Dimensional Truthfulness Evaluation of Quantized LLMs cites this paper.

Quantized but Deceptive? A Multi-Dimensional Truthfulness Evaluation of Quantized LLMs SqueezeLLM: Dense-and-Sparse Quantization

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-05T15:52:44.950132Z

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Observation 5345532e-07ac-4710-acc3-c0145d49c1b6 · inbound

PuzzleMoE: Efficient Compression of Large Mixture-of-Experts Models via Sparse Expert Merging and Bit-packed inference cites this paper.

PuzzleMoE: Efficient Compression of Large Mixture-of-Experts Models via Sparse Expert Merging and Bit-packed inference SqueezeLLM: Dense-and-Sparse Quantization

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-03T23:41:52.877669Z

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Observation 0985625e-76f9-437f-ad97-54c08b11d733 · inbound

Towards the Holographic Characteristic of LLMs for Efficient Short-text Generation cites this paper.

Towards the Holographic Characteristic of LLMs for Efficient Short-text Generation SqueezeLLM: Dense-and-Sparse Quantization

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-03T06:38:22.663076Z

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Observation bd74cafc-1369-4735-b1e1-8dc004cf81fc · inbound

CoreQ: Learning-Free Mismatch Correction and Successive Rounding for Quantization cites this paper.

CoreQ: Learning-Free Mismatch Correction and Successive Rounding for Quantization SqueezeLLM: Dense-and-Sparse Quantization

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-05-16T06:52:28.393534Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 4f1281b2-6e40-4ab6-8b75-236e1bbd952f · inbound

On the Quantization Robustness of Diffusion Language Models in Coding Benchmarks cites this paper.

On the Quantization Robustness of Diffusion Language Models in Coding Benchmarks SqueezeLLM: Dense-and-Sparse Quantization

Reference 15

Resolution: metadata mismatch; arxiv_id, observed 2026-05-10T00:24:47.003271Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 4de3b8e2-c80f-463d-a5d6-a86773e97d0d · inbound

Coverage-Based Calibration for Post-Training Quantization via Weighted Set Cover over Outlier Channels cites this paper.

Coverage-Based Calibration for Post-Training Quantization via Weighted Set Cover over Outlier Channels SqueezeLLM: Dense-and-Sparse Quantization

Reference 13

Resolution: verified exact; arxiv_id, observed 2026-05-11T21:41:16.200257Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation e07df099-eae8-4bee-9a7e-d68669a9ec3a · inbound

BitRL: Reinforcement Learning with 1-bit Quantized Language Models for Resource-Constrained Edge Deployment cites this paper.

BitRL: Reinforcement Learning with 1-bit Quantized Language Models for Resource-Constrained Edge Deployment SqueezeLLM: Dense-and-Sparse Quantization

Reference 2

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T21:46:42.443324Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 8f50f0c4-d94e-433f-ab19-6021234e0e44 · inbound

DurableUn: Quantization-Induced Recovery Attacks in Machine Unlearning cites this paper.

DurableUn: Quantization-Induced Recovery Attacks in Machine Unlearning SqueezeLLM: Dense-and-Sparse Quantization

Reference 24

Resolution: metadata mismatch; arxiv_id, observed 2026-05-09T06:10:42.160072Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 39e3d22d-1c77-4575-9115-5a4f1c462bc9 · inbound

DurableUn: Quantization-Induced Recovery Attacks in Machine Unlearning cites this paper.

DurableUn: Quantization-Induced Recovery Attacks in Machine Unlearning SqueezeLLM: Dense-and-Sparse Quantization

Reference 24

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T01:50:51.165324Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 99e832e7-3ec7-4588-b1ac-415de378cc29 · inbound

WindowQuant: Mixed-Precision KV Cache Quantization based on Window-Level Similarity for VLMs Inference Optimization cites this paper.

WindowQuant: Mixed-Precision KV Cache Quantization based on Window-Level Similarity for VLMs Inference Optimization SqueezeLLM: Dense-and-Sparse Quantization

Reference 18

Resolution: verified exact; arxiv_id, observed 2026-05-11T16:36:08.029916Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 0d0da963-e2f9-4554-b344-1f115737f3f5 · inbound

MP-ISMoE: Mixed-Precision Interactive Side Mixture-of-Experts for Efficient Transfer Learning cites this paper.

MP-ISMoE: Mixed-Precision Interactive Side Mixture-of-Experts for Efficient Transfer Learning SqueezeLLM: Dense-and-Sparse Quantization

Reference 121

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T07:01:10.321373Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation ee2ac829-f9e2-4fd6-ad98-c96f3e2bc34f · inbound

OSAQ: Outlier Self-Absorption for Accurate Low-bit LLM Quantization cites this paper.

OSAQ: Outlier Self-Absorption for Accurate Low-bit LLM Quantization SqueezeLLM: Dense-and-Sparse Quantization

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-05-09T06:30:44.142303Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 2740b635-abd5-496a-a944-9bdd0dd5b5ea · inbound

OSAQ: Outlier Self-Absorption for Accurate Low-bit LLM Quantization cites this paper.

OSAQ: Outlier Self-Absorption for Accurate Low-bit LLM Quantization SqueezeLLM: Dense-and-Sparse Quantization

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-05-12T03:01:18.210120Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation d16da3e7-de78-4192-8548-66862fc2ff1b · inbound

XFP: Quality-Targeted Adaptive Codebook Quantization with Sparse Outlier Separation for LLM Inference cites this paper.

XFP: Quality-Targeted Adaptive Codebook Quantization with Sparse Outlier Separation for LLM Inference SqueezeLLM: Dense-and-Sparse Quantization

Reference 14

Resolution: verified exact; arxiv_id, observed 2026-06-30T21:35:04.690279Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 7ec28d36-0207-4a96-98b0-9217129dccff · 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 SqueezeLLM: Dense-and-Sparse Quantization

Reference 20

Resolution: metadata mismatch; arxiv_id, observed 2026-05-20T05:23:03.625863Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 9bd3ab0c-6349-4222-a3c0-7f1dfd3eba6d · inbound

GEMQ: Global Expert-Level Mixed-Precision Quantization for MoE LLMs cites this paper.

GEMQ: Global Expert-Level Mixed-Precision Quantization for MoE LLMs SqueezeLLM: Dense-and-Sparse Quantization

Reference 15

Resolution: verified exact; arxiv_id, observed 2026-05-25T05:36:39.872360Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation bf0cc52c-1c31-4da3-9a8e-9cba87bf348f · inbound

ActQuant: Sub-4-bit Action-Guided Quantization for Vision-Language-Action Models cites this paper.

ActQuant: Sub-4-bit Action-Guided Quantization for Vision-Language-Action Models SqueezeLLM: Dense-and-Sparse Quantization

Reference 17

Resolution: metadata mismatch; arxiv_id, observed 2026-06-30T18:04:58.491515Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 9f262736-e8cc-4a2d-ada2-88c261a3f7b2 · inbound

DREAM-S: Speculative Decoding with Searchable Drafting and Target-Aware Refinement for Multimodal Generation cites this paper.

DREAM-S: Speculative Decoding with Searchable Drafting and Target-Aware Refinement for Multimodal Generation SqueezeLLM: Dense-and-Sparse Quantization

Reference 73

Resolution: metadata mismatch; arxiv_id, observed 2026-06-28T19:02:34.617720Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation d4b4ba6f-6db8-4589-807f-f054a40c3feb · inbound

GPTQ-intrinsic LoRA: A Near-optimal Algorithm for Low-precision Quantization with Low-rank Adaptation cites this paper.

GPTQ-intrinsic LoRA: A Near-optimal Algorithm for Low-precision Quantization with Low-rank Adaptation SqueezeLLM: Dense-and-Sparse Quantization

Reference 36

Resolution: verified exact; arxiv_id, observed 2026-07-01T21:06:14.475000Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation cb5672a2-5a67-43de-ac03-95457cefd64a · inbound

Minimizing the Hidden Cost of Scales: Graph-Guided Ultra-Low-Bit Quantization for Large Language Models cites this paper.

Minimizing the Hidden Cost of Scales: Graph-Guided Ultra-Low-Bit Quantization for Large Language Models SqueezeLLM: Dense-and-Sparse Quantization

Reference 27

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T08:16:48.293704Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation cc0d0cdb-359f-4fbf-a642-c00e4281e965 · inbound

When AI Reviews Its Own Code: Recursive Self-Training Collapse in Code LLMs cites this paper.

When AI Reviews Its Own Code: Recursive Self-Training Collapse in Code LLMs SqueezeLLM: Dense-and-Sparse Quantization

Reference 141

Resolution: metadata mismatch; arxiv_id, observed 2026-07-01T15:25:48.408417Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 1bac6c64-6ee8-4ee4-a0bd-310a5e10279c · inbound

GSRQ: Gain-Shape Residual Quantization for Sub-1-bit KV Cache cites this paper.

GSRQ: Gain-Shape Residual Quantization for Sub-1-bit KV Cache SqueezeLLM: Dense-and-Sparse Quantization

Reference 24

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T15:57:06.403971Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 807090fd-1b0e-484d-b714-c291eb299548 · inbound

SAB-LVLM: Significance-Aware Binarization for Large Vision-Language Models cites this paper.

SAB-LVLM: Significance-Aware Binarization for Large Vision-Language Models SqueezeLLM: Dense-and-Sparse Quantization

Reference 8

Resolution: metadata mismatch; arxiv_id, observed 2026-07-03T16:18:37.341488Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 0e56bdc7-8bc2-4799-9fed-944eb3b39dbb · inbound

OrbitQuant: Data-Agnostic Quantization for Image and Video Diffusion Transformers cites this paper.

OrbitQuant: Data-Agnostic Quantization for Image and Video Diffusion Transformers SqueezeLLM: Dense-and-Sparse Quantization

Reference 21

Resolution: metadata mismatch; arxiv_id, observed 2026-07-03T14:58:32.417750Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 91ab3514-5ab9-417b-bd6b-a58cc4aea220 · inbound

StreamDQ: Near-Memory Weight DeQuantization in Custom HBM for Scalable AI Inference Acceleration cites this paper.

StreamDQ: Near-Memory Weight DeQuantization in Custom HBM for Scalable AI Inference Acceleration SqueezeLLM: Dense-and-Sparse Quantization

Reference 40

Resolution: unresolved; no resolver link, observed 2026-07-13T01:10:03.032181Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 25b40a43-1701-4822-b146-c3fd2fdc511c · inbound

MXSens: Sensitivity-Aware Mixed-Precision Quantization for Efficient LLM Inference cites this paper.

MXSens: Sensitivity-Aware Mixed-Precision Quantization for Efficient LLM Inference SqueezeLLM: Dense-and-Sparse Quantization

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-01T17:12:27.941291Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a32228b5-c235-4152-960b-a3ebecdb9bf7 · inbound

Edge Intelligence in Civil Aviation: Paradigms, Techniques, and Applications cites this paper.

Edge Intelligence in Civil Aviation: Paradigms, Techniques, and Applications SqueezeLLM: Dense-and-Sparse Quantization

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-01T12:04:14.348367Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 97eec831-accd-4d0d-81d9-b292476d3de8 · inbound

AdaMTP: An Adaptive Training Paradigm for Multi-Token Prediction cites this paper.

AdaMTP: An Adaptive Training Paradigm for Multi-Token Prediction SqueezeLLM: Dense-and-Sparse Quantization

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-15T15:25:35.561194Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ae555642-7422-4b52-bcb6-322e78b476d7 · inbound

NANQ: Noise-Floor-Aware Mixed-Precision Non-Uniform Quantization for Analog Compute-in-Memory cites this paper.

NANQ: Noise-Floor-Aware Mixed-Precision Non-Uniform Quantization for Analog Compute-in-Memory SqueezeLLM: Dense-and-Sparse Quantization

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-15T15:07:27.121364Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c46894f7-5422-494f-8ba4-abcadcbcafc3 · inbound

Recurrent Residual Quantization: A Progressive Multi-Precision Representation for LLMs cites this paper.

Recurrent Residual Quantization: A Progressive Multi-Precision Representation for LLMs SqueezeLLM: Dense-and-Sparse Quantization

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-08T00:50:44.530504Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a7416f9b-af4f-4111-8886-f14a698dd9e2 · inbound

CubicQuant: Parametric Non-Uniform Codebooks for High-Throughput LLM Inference with 1-8-Bit Weights cites this paper.

CubicQuant: Parametric Non-Uniform Codebooks for High-Throughput LLM Inference with 1-8-Bit Weights SqueezeLLM: Dense-and-Sparse Quantization

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-15T14:37:51.911058Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 97c6bcb4-8125-4bfa-aff4-e3ba4efc8a6c · inbound

Riemann GeoResolver: A Non-Euclidean Attention Framework from Euclidean Resolver to Hyperbolic-Spherical Geometry cites this paper.

Riemann GeoResolver: A Non-Euclidean Attention Framework from Euclidean Resolver to Hyperbolic-Spherical Geometry SqueezeLLM: Dense-and-Sparse Quantization

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-15T14:29:49.272723Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Coverage vector

Reference resolution

Outbound references

Pith citing papers