OASIS: Outlier-Aware LUT-Based GEMM with Dual-Side Quantization for LLM Inference Acceleration | Paper Citation Record

Observation 847f1ac4-5c7d-4ff8-a611-3eab56f97699 · outbound

This paper cites GPT-4 Technical Report.

OASIS: Outlier-Aware LUT-Based GEMM with Dual-Side Quantization for LLM Inference Acceleration GPT-4 Technical Report

Reference 1

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Observation 1d4a66b1-8c6c-41c6-8bb1-b40af839071f · outbound

This paper cites Introducing nvfp4 for efficient and accurate low-precision inference,.

OASIS: Outlier-Aware LUT-Based GEMM with Dual-Side Quantization for LLM Inference Acceleration Introducing nvfp4 for efficient and accurate low-precision inference,

Reference 2

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Observation ffa98e14-2ef6-4e5b-8568-ab043fda4390 · outbound

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

OASIS: Outlier-Aware LUT-Based GEMM with Dual-Side Quantization for LLM Inference Acceleration QuaRot: Outlier-Free 4-Bit Inference in Rotated LLMs

Reference 3

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Observation 26c611be-c7b4-4e90-b0c5-c42224593a74 · outbound

This paper cites Piqa: Reasoning about physical commonsense in natural language,.

OASIS: Outlier-Aware LUT-Based GEMM with Dual-Side Quantization for LLM Inference Acceleration Piqa: Reasoning about physical commonsense in natural language,

Reference 4

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Observation 676550be-860f-4102-8a7d-8e7a3e331415 · outbound

This paper cites Language mod- els are few-shot learners,.

OASIS: Outlier-Aware LUT-Based GEMM with Dual-Side Quantization for LLM Inference Acceleration Language mod- els are few-shot learners,

Reference 5

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This paper cites Boolq: Exploring the surprising difficulty of natural yes/no questions,.

OASIS: Outlier-Aware LUT-Based GEMM with Dual-Side Quantization for LLM Inference Acceleration Boolq: Exploring the surprising difficulty of natural yes/no questions,

Reference 6

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Observation 091fade5-25e8-4b5c-b535-1174f1e6af4d · outbound

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

OASIS: Outlier-Aware LUT-Based GEMM with Dual-Side Quantization for LLM Inference Acceleration Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge

Reference 7

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Observation 9ba754d0-ccb3-48ad-ac87-d48b1cd9cb79 · outbound

This paper cites Nvidia rtx blackwell gpu architecture: Built for neural rendering,.

OASIS: Outlier-Aware LUT-Based GEMM with Dual-Side Quantization for LLM Inference Acceleration Nvidia rtx blackwell gpu architecture: Built for neural rendering,

Reference 8

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Observation c19aadb0-2152-4b45-8a97-5b20991a2b7e · outbound

This paper cites Documenting Large Webtext Corpora: A Case Study on the Colossal Clean Crawled Corpus.

OASIS: Outlier-Aware LUT-Based GEMM with Dual-Side Quantization for LLM Inference Acceleration Documenting Large Webtext Corpora: A Case Study on the Colossal Clean Crawled Corpus

Reference 9

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Observation 0bd92ba3-0419-4950-820f-d15dca7882e6 · outbound

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

OASIS: Outlier-Aware LUT-Based GEMM with Dual-Side Quantization for LLM Inference Acceleration GPTQ: Accurate Post-Training Quantization for Generative Pre-trained Transformers

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-06T11:15:33.931222Z

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Observation b66d7ef3-3d63-40c7-a76c-b41da2412312 · outbound

This paper cites Gpt4aigchip: Towards next-generation ai accelerator design automation via large language models,.

OASIS: Outlier-Aware LUT-Based GEMM with Dual-Side Quantization for LLM Inference Acceleration Gpt4aigchip: Towards next-generation ai accelerator design automation via large language models,

Reference 12

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Observation 83587800-befc-4eef-973a-acb387a7edb1 · outbound

This paper cites The language model evaluation harness,.

OASIS: Outlier-Aware LUT-Based GEMM with Dual-Side Quantization for LLM Inference Acceleration The language model evaluation harness,

Reference 13

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Observation 01476bca-db5c-4939-ade7-9ff0cef4583e · outbound

This paper cites Disaggregated machine learning via in-physics computing at radio frequency,.

OASIS: Outlier-Aware LUT-Based GEMM with Dual-Side Quantization for LLM Inference Acceleration Disaggregated machine learning via in-physics computing at radio frequency,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:15:34.544343Z

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Observation 0df24342-d211-44e0-b568-5c04c93ff571 · outbound

This paper cites The Llama 3 Herd of Models.

OASIS: Outlier-Aware LUT-Based GEMM with Dual-Side Quantization for LLM Inference Acceleration The Llama 3 Herd of Models

Reference 15

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Observation fa62e0b2-0f26-4eb9-9c55-b2f71afd2313 · outbound

This paper cites A survey: Collaborative hardware and software design in the era of large language models,.

OASIS: Outlier-Aware LUT-Based GEMM with Dual-Side Quantization for LLM Inference Acceleration A survey: Collaborative hardware and software design in the era of large language models,

Reference 16

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Observation 4bd7d299-2c50-4f70-8bda-050d8482a453 · outbound

This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.

OASIS: Outlier-Aware LUT-Based GEMM with Dual-Side Quantization for LLM Inference Acceleration DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-06T11:15:33.945972Z

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Observation 10c1d9ca-9662-4750-87f2-957ad7e750d6 · outbound

This paper cites Chateda: A large language model powered autonomous agent for eda,.

OASIS: Outlier-Aware LUT-Based GEMM with Dual-Side Quantization for LLM Inference Acceleration Chateda: A large language model powered autonomous agent for eda,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:15:34.532245Z

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Observation b78e0d83-6f47-466f-8038-3a25652de897 · outbound

This paper cites KVQuant: Towards 10 Million Context Length LLM Inference with KV Cache Quantization.

OASIS: Outlier-Aware LUT-Based GEMM with Dual-Side Quantization for LLM Inference Acceleration KVQuant: Towards 10 Million Context Length LLM Inference with KV Cache Quantization

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-06T11:15:33.951900Z

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Observation f973aac6-c8f8-4b38-b7ec-73c49efcea13 · outbound

This paper cites Mistral 7B.

OASIS: Outlier-Aware LUT-Based GEMM with Dual-Side Quantization for LLM Inference Acceleration Mistral 7B

Reference 20

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

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

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

Reference 21

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Observation 0e91b256-0d82-4bcd-ad0d-353c4c24d757 · outbound

This paper cites Scaling Laws for Precision.

OASIS: Outlier-Aware LUT-Based GEMM with Dual-Side Quantization for LLM Inference Acceleration Scaling Laws for Precision

Reference 22

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Observation 474dd206-9f2e-44dc-8e38-d267b0d2e348 · outbound

This paper cites Maeri: Enabling flexible dataflow mapping over dnn accelerators via reconfigurable intercon- nects,.

OASIS: Outlier-Aware LUT-Based GEMM with Dual-Side Quantization for LLM Inference Acceleration Maeri: Enabling flexible dataflow mapping over dnn accelerators via reconfigurable intercon- nects,

Reference 23

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Observation fdfd1d2e-742e-4a9e-8129-4d58ba90fdf6 · outbound

This paper cites Efficient memory management for large language model serving with pagedattention,.

OASIS: Outlier-Aware LUT-Based GEMM with Dual-Side Quantization for LLM Inference Acceleration Efficient memory management for large language model serving with pagedattention,

Reference 24

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Observation 99348218-225c-4b9b-af02-865527d3b435 · outbound

This paper cites Fast and Efficient 2-bit LLM Inference on GPU: 2/4/16-bit in a Weight Matrix with Asynchronous Dequantization.

OASIS: Outlier-Aware LUT-Based GEMM with Dual-Side Quantization for LLM Inference Acceleration Fast and Efficient 2-bit LLM Inference on GPU: 2/4/16-bit in a Weight Matrix with Asynchronous Dequantization

Reference 25

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Observation 32f0d38e-909f-4f6b-8443-288630bd664c · outbound

This paper cites Dramsim3: A cycle-accurate, thermal-capable dram simulator,.

OASIS: Outlier-Aware LUT-Based GEMM with Dual-Side Quantization for LLM Inference Acceleration Dramsim3: A cycle-accurate, thermal-capable dram simulator,

Reference 26

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This paper cites Cacti- p: Architecture-level modeling for sram-based structures with advanced leakage reduction techniques,.

OASIS: Outlier-Aware LUT-Based GEMM with Dual-Side Quantization for LLM Inference Acceleration Cacti- p: Architecture-level modeling for sram-based structures with advanced leakage reduction techniques,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:15:34.508718Z

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Observation 9945d51a-502d-49c7-ab4d-69aaa5b8ce20 · outbound

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

OASIS: Outlier-Aware LUT-Based GEMM with Dual-Side Quantization for LLM Inference Acceleration Duquant: Distributing outliers via dual transformation makes stronger quantized llms,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:15:34.502129Z

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Observation 4913921f-23cb-45be-80c3-b6e41a69d8ea · outbound

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

OASIS: Outlier-Aware LUT-Based GEMM with Dual-Side Quantization for LLM Inference Acceleration Awq: Activation-aware weight quanti- zation for on-device llm compression and acceleration,

Reference 29

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Observation 6bca994c-09f1-444a-99eb-a2fe6badb1f1 · outbound

This paper cites QServe: W4A8KV4 Quantization and System Co-design for Efficient LLM Serving.

OASIS: Outlier-Aware LUT-Based GEMM with Dual-Side Quantization for LLM Inference Acceleration QServe: W4A8KV4 Quantization and System Co-design for Efficient LLM Serving

Reference 30

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Observation 890a1171-f933-4662-951e-180cecf31f3a · outbound

This paper cites LLM-FP4: 4-Bit Floating-Point Quantized Transformers.

OASIS: Outlier-Aware LUT-Based GEMM with Dual-Side Quantization for LLM Inference Acceleration LLM-FP4: 4-Bit Floating-Point Quantized Transformers

Reference 31

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Observation ae5fbade-769f-4cb2-9da3-c7f6c0eaaced · outbound

This paper cites Micromix: Efficient mixed-precision quantization with microscaling formats for large lan- guage models,.

OASIS: Outlier-Aware LUT-Based GEMM with Dual-Side Quantization for LLM Inference Acceleration Micromix: Efficient mixed-precision quantization with microscaling formats for large lan- guage models,

Reference 32

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Observation 38ab1e3d-f98f-4f09-a5cd-2073a5c0d73e · outbound

This paper cites SpinQuant: LLM quantization with learned rotations.

OASIS: Outlier-Aware LUT-Based GEMM with Dual-Side Quantization for LLM Inference Acceleration SpinQuant: LLM quantization with learned rotations

Reference 33

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Observation e9c1bb92-f21a-4fc2-b7ed-f8ded2fd9925 · outbound

This paper cites Some methods for classification and analysis of mul- tivariate observations,.

OASIS: Outlier-Aware LUT-Based GEMM with Dual-Side Quantization for LLM Inference Acceleration Some methods for classification and analysis of mul- tivariate observations,

Reference 34

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Observation f2ef1d18-e455-4ce2-8e0b-c4501104cd6c · outbound

This paper cites The penn treebank: Anno- tating predicate argument structure,.

OASIS: Outlier-Aware LUT-Based GEMM with Dual-Side Quantization for LLM Inference Acceleration The penn treebank: Anno- tating predicate argument structure,

Reference 35

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Observation 53d58b4d-4c3a-4d28-9050-b01fc0c896db · outbound

This paper cites Pointer Sentinel Mixture Models.

OASIS: Outlier-Aware LUT-Based GEMM with Dual-Side Quantization for LLM Inference Acceleration Pointer Sentinel Mixture Models

Reference 36

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Observation ed7a9133-be5c-4554-a0cb-2e41b845ce77 · outbound

This paper cites Lut tensor core: A software-hardware co-design for lut-based low-bit llm inference,.

OASIS: Outlier-Aware LUT-Based GEMM with Dual-Side Quantization for LLM Inference Acceleration Lut tensor core: A software-hardware co-design for lut-based low-bit llm inference,

Reference 37

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Observation 8b5b2eea-1a5d-4e71-9f56-f8eef89ca9e1 · outbound

This paper cites Flexagon: A multi-dataflow sparse-sparse matrix multiplication accelerator for efficient dnn processing,.

OASIS: Outlier-Aware LUT-Based GEMM with Dual-Side Quantization for LLM Inference Acceleration Flexagon: A multi-dataflow sparse-sparse matrix multiplication accelerator for efficient dnn processing,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:15:34.474197Z

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Observation eac6ef34-4cf6-4290-ac41-ef9c3bcb953a · outbound

This paper cites Tensor core performance: The ultimate guide,.

OASIS: Outlier-Aware LUT-Based GEMM with Dual-Side Quantization for LLM Inference Acceleration Tensor core performance: The ultimate guide,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:15:34.467837Z

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Observation acaa0eff-aaa0-4ed9-ad1e-b82c1d9d7738 · outbound

This paper cites Nvidia a100 tensor core gpu architecture,.

OASIS: Outlier-Aware LUT-Based GEMM with Dual-Side Quantization for LLM Inference Acceleration Nvidia a100 tensor core gpu architecture,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:15:34.461515Z

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Observation 79775c60-7ee3-46d3-99da-2aec46b3deaf · outbound

This paper cites Nvidia turing gpu architecture whitepaper,.

OASIS: Outlier-Aware LUT-Based GEMM with Dual-Side Quantization for LLM Inference Acceleration Nvidia turing gpu architecture whitepaper,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:15:34.454754Z

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Observation 9a5f4477-ab6c-46ce-8f59-c759b49a7646 · outbound

This paper cites Figlut: An energy-efficient accelerator design for fp-int gemm using look-up tables,.

OASIS: Outlier-Aware LUT-Based GEMM with Dual-Side Quantization for LLM Inference Acceleration Figlut: An energy-efficient accelerator design for fp-int gemm using look-up tables,

Reference 42

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Observation c403adaa-dcb0-43ee-ad15-14d0688474fc · outbound

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

OASIS: Outlier-Aware LUT-Based GEMM with Dual-Side Quantization for LLM Inference Acceleration LUT-GEMM: Quantized Matrix Multiplication based on LUTs for Efficient Inference in Large-Scale Generative Language Models

Reference 43

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Observation c8689608-4ed0-4553-8a34-81cec0ae2380 · outbound

This paper cites Pytorch: An imperative style, high-performance deep learning library,.

OASIS: Outlier-Aware LUT-Based GEMM with Dual-Side Quantization for LLM Inference Acceleration Pytorch: An imperative style, high-performance deep learning library,

Reference 44

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Observation 26c6ef4f-79ec-455a-917d-d2dd090e8f2b · outbound

This paper cites The spectrum of the fisher information matrix of a single-hidden-layer neural network,.

OASIS: Outlier-Aware LUT-Based GEMM with Dual-Side Quantization for LLM Inference Acceleration The spectrum of the fisher information matrix of a single-hidden-layer neural network,

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:15:34.439003Z

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Observation f229ea5a-8b62-487e-bfa3-3749f265cab1 · outbound

This paper cites Code Llama: Open Foundation Models for Code.

OASIS: Outlier-Aware LUT-Based GEMM with Dual-Side Quantization for LLM Inference Acceleration Code Llama: Open Foundation Models for Code

Reference 46

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Observation 5ed5fbe7-3998-44da-9c87-92171d12317a · outbound

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

OASIS: Outlier-Aware LUT-Based GEMM with Dual-Side Quantization for LLM Inference Acceleration Winogrande: An adversarial winograd schema challenge at scale,

Reference 47

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Observation 3e8fc9e3-9e3b-42f2-93e8-fb4b672eedae · outbound

This paper cites From high-level deep neural models to fpgas,.

OASIS: Outlier-Aware LUT-Based GEMM with Dual-Side Quantization for LLM Inference Acceleration From high-level deep neural models to fpgas,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:15:34.426375Z

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Observation af992595-daa8-4976-927e-11a4586467a6 · outbound

This paper cites Using tournament trees to sort,.

OASIS: Outlier-Aware LUT-Based GEMM with Dual-Side Quantization for LLM Inference Acceleration Using tournament trees to sort,

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:15:34.419142Z

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Observation ccd3cce7-639b-436b-b6df-46d6abd5dcd6 · outbound

This paper cites FlatQuant: Flatness Matters for LLM Quantization.

OASIS: Outlier-Aware LUT-Based GEMM with Dual-Side Quantization for LLM Inference Acceleration FlatQuant: Flatness Matters for LLM Quantization

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-06T11:15:34.021581Z

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Observation 3d92a750-e61d-4f56-8bc8-191e6652ad31 · outbound

This paper cites Crystal: Illuminating LLM Abilities on Language and Code.

OASIS: Outlier-Aware LUT-Based GEMM with Dual-Side Quantization for LLM Inference Acceleration Crystal: Illuminating LLM Abilities on Language and Code

Reference 51

Resolution: verified exact; local_arxiv, observed 2026-08-06T11:15:34.105303Z

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 ac7a5324-4274-4cab-8520-2661799740bd · outbound

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

OASIS: Outlier-Aware LUT-Based GEMM with Dual-Side Quantization for LLM Inference Acceleration LLaMA: Open and Efficient Foundation Language Models

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-06T11:15:34.026962Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0328b448-115f-40cd-bbfc-6204c94d80f2 · outbound

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

OASIS: Outlier-Aware LUT-Based GEMM with Dual-Side Quantization for LLM Inference Acceleration Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-06T11:15:34.029186Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ca415c67-07c8-4bb1-bf9b-d9649486e814 · outbound

This paper cites Training LLMs with MXFP4.

OASIS: Outlier-Aware LUT-Based GEMM with Dual-Side Quantization for LLM Inference Acceleration Training LLMs with MXFP4

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-06T11:15:34.031488Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a5e8def4-b552-453b-a57f-78b0e69e68de · outbound

This paper cites Spatten: Efficient sparse attention architecture with cascade token and head pruning,.

OASIS: Outlier-Aware LUT-Based GEMM with Dual-Side Quantization for LLM Inference Acceleration Spatten: Efficient sparse attention architecture with cascade token and head pruning,

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:15:34.411949Z

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 c2de2862-1679-441e-b993-7cfcf9e66440 · outbound

This paper cites Transformers: State- of-the-art natural language processing,.

OASIS: Outlier-Aware LUT-Based GEMM with Dual-Side Quantization for LLM Inference Acceleration Transformers: State- of-the-art natural language processing,

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-06T11:15:34.035550Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8dfb485f-b35d-4ac7-ba3e-55b33b8f6c72 · outbound

This paper cites Block- wise mixed-precision quantization: Enabling high efficiency for practical reram-based dnn accelerators,.

OASIS: Outlier-Aware LUT-Based GEMM with Dual-Side Quantization for LLM Inference Acceleration Block- wise mixed-precision quantization: Enabling high efficiency for practical reram-based dnn accelerators,

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:15:34.401129Z

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 fce3dd4c-b901-4376-9ad9-194b8fe19afc · outbound

This paper cites Smoothquant: Accurate and efficient post-training quantization for large language models,.

OASIS: Outlier-Aware LUT-Based GEMM with Dual-Side Quantization for LLM Inference Acceleration Smoothquant: Accurate and efficient post-training quantization for large language models,

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-06T11:15:34.039849Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8ed5d561-1e23-4b49-94d1-8c349e8dd2e8 · outbound

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

OASIS: Outlier-Aware LUT-Based GEMM with Dual-Side Quantization for LLM Inference Acceleration HellaSwag: Can a Machine Really Finish Your Sentence?

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-06T11:15:34.041839Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f0c0c966-a8ae-4717-b45d-67c7d0e6e38b · outbound

This paper cites Lq-nets: Learned quantization for highly accurate and compact deep neural networks,.

OASIS: Outlier-Aware LUT-Based GEMM with Dual-Side Quantization for LLM Inference Acceleration Lq-nets: Learned quantization for highly accurate and compact deep neural networks,

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:15:34.387928Z

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 f4ae1c58-19aa-45ab-b601-7249c9c27193 · outbound

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

OASIS: Outlier-Aware LUT-Based GEMM with Dual-Side Quantization for LLM Inference Acceleration OPT: Open Pre-trained Transformer Language Models

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-06T11:15:34.045763Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 08062e34-8710-45a4-b3cf-5cd7fd723fce · outbound

This paper cites Atom: Low-bit quantization for efficient and accurate llm serving,.

OASIS: Outlier-Aware LUT-Based GEMM with Dual-Side Quantization for LLM Inference Acceleration Atom: Low-bit quantization for efficient and accurate llm serving,

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-06T11:15:34.047943Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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