语言大模型 / LLM - arXivDaily 专题

2312.02119 2024-11-01 cs.LG cs.AI cs.CL cs.CR stat.ML 80%

Tree of Attacks: Jailbreaking Black-Box LLMs Automatically

Anay Mehrotra, Manolis Zampetakis, Paul Kassianik, Blaine Nelson, Hyrum Anderson, Yaron Singer, Amin Karbasi

机构 * Yale University（耶鲁大学）； Robust Intelligence ； Google Research（谷歌研究院）

专题命中效率与部署：LLM(abstract)；large language model(abstract)；language model(abstract)；分类 cs.CL、cs.AI、cs.LG

Comments Accepted for presentation at NeurIPS 2024. Code: https://github.com/RICommunity/TAP

2410.18952 2024-10-31 cs.CL cs.AI cs.LG 80%

Dynamic Vocabulary Pruning in Early-Exit LLMs

Jort Vincenti, Karim Abdel Sadek, Joan Velja, Matteo Nulli, Metod Jazbec

机构 * University of Amsterdam（阿姆斯特丹大学）； Krueger AI Safety Lab (KASL)（克鲁格人工智能安全实验室（KASL））； UvA-Bosch Delta Lab（阿姆斯特丹大学-博世三角洲实验室）

专题命中效率与部署：LLM(abstract)；large language model(abstract)；language model(abstract)；分类 cs.CL、cs.AI、cs.LG

Journal ref NeurIPS 2024 ENLSP Workshop

2405.16122 2024-10-30 cs.AI cs.CL cs.LG stat.ML 80%

Prompt Optimization with EASE? Efficient Ordering-aware Automated Selection of Exemplars

Zhaoxuan Wu, Xiaoqiang Lin, Zhongxiang Dai, Wenyang Hu, Yao Shu, See-Kiong Ng, Patrick Jaillet, Bryan Kian Hsiang Low

专题命中效率与部署：LLM(abstract)；large language model(abstract)；language model(abstract)；分类 cs.CL、cs.AI、cs.LG

Comments 28 pages, 1 figure, 35 tables

2406.17415 2024-10-29 cs.CL cs.AI cs.LG 80%

Layer-Wise Quantization: A Pragmatic and Effective Method for Quantizing LLMs Beyond Integer Bit-Levels

Razvan-Gabriel Dumitru, Vikas Yadav, Rishabh Maheshwary, Paul-Ioan Clotan, Sathwik Tejaswi Madhusudhan, Mihai Surdeanu

专题命中效率与部署：LLM(abstract)；large language model(abstract)；language model(abstract)；分类 cs.CL、cs.AI、cs.LG

2404.16710 2024-10-21 cs.CL cs.AI cs.LG 80%

LayerSkip: Enabling Early Exit Inference and Self-Speculative Decoding

Mostafa Elhoushi, Akshat Shrivastava, Diana Liskovich, Basil Hosmer, Bram Wasti, Liangzhen Lai, Anas Mahmoud, Bilge Acun, Saurabh Agarwal, Ahmed Roman, Ahmed A Aly, Beidi Chen, Carole-Jean Wu

专题命中效率与部署：large language model(abstract)；language model(abstract)；pretraining(abstract)；分类 cs.CL、cs.AI、cs.LG

Comments ACL 2024

2406.15786 2024-10-18 cs.LG cs.AI cs.CL 80%

What Matters in Transformers? Not All Attention is Needed

Shwai He, Guoheng Sun, Zheyu Shen, Ang Li

专题命中效率与部署：LLM(abstract)；large language model(abstract)；language model(abstract)；分类 cs.CL、cs.AI、cs.LG

Comments 15 pages, 13 figures, 6 tables

2406.11890 2024-10-16 cs.LG cs.AI cs.CL 80%

Unraveling the Mechanics of Learning-Based Demonstration Selection for In-Context Learning

Hui Liu, Wenya Wang, Hao Sun, Chris Xing Tian, Chenqi Kong, Xin Dong, Haoliang Li

专题命中效率与部署：LLM(abstract)；large language model(abstract)；language model(abstract)；分类 cs.CL、cs.AI、cs.LG

Comments 17 pages, 7 figures and 9 tables

2403.02966 2024-10-10 cs.CL cs.AI cs.LG 80%

Evidence-Focused Fact Summarization for Knowledge-Augmented Zero-Shot Question Answering

Sungho Ko, Hyunjin Cho, Hyungjoo Chae, Jinyoung Yeo, Dongha Lee

专题命中效率与部署：LLM(abstract)；large language model(abstract)；language model(abstract)；分类 cs.CL、cs.AI、cs.LG

2410.05603 2024-10-10 cs.LG cs.AI cs.CL 80%

Everything Everywhere All at Once: LLMs can In-Context Learn Multiple Tasks in Superposition

Zheyang Xiong, Ziyang Cai, John Cooper, Albert Ge, Vasilis Papageorgiou, Zack Sifakis, Angeliki Giannou, Ziqian Lin, Liu Yang, Saurabh Agarwal, Grigorios G Chrysos, Samet Oymak, Kangwook Lee, Dimitris Papailiopoulos

专题命中效率与部署：LLM(abstract)；large language model(abstract)；language model(abstract)；分类 cs.CL、cs.AI、cs.LG

2309.05516 2024-10-10 cs.CL cs.AI cs.LG 80%

Optimize Weight Rounding via Signed Gradient Descent for the Quantization of LLMs

Wenhua Cheng, Weiwei Zhang, Haihao Shen, Yiyang Cai, Xin He, Kaokao Lv, Yi Liu

专题命中效率与部署：large language model(abstract)；language model(abstract)；post-training(abstract)；分类 cs.CL、cs.AI、cs.LG

Comments EMNLP24 Findings

2410.03111 2024-10-07 cs.LG cs.AI cs.CL 80%

LoRC: Low-Rank Compression for LLMs KV Cache with a Progressive Compression Strategy

Rongzhi Zhang, Kuang Wang, Liyuan Liu, Shuohang Wang, Hao Cheng, Chao Zhang, Yelong Shen

专题命中效率与部署：LLM(abstract)；large language model(abstract)；language model(abstract)；分类 cs.CL、cs.AI、cs.LG

Comments 15 pages, 4 figures

2410.02725 2024-10-04 cs.CL cs.AI cs.LG 80%

Adaptive Inference-Time Compute: LLMs Can Predict if They Can Do Better, Even Mid-Generation

Rohin Manvi, Anikait Singh, Stefano Ermon

专题命中效率与部署：LLM(abstract)；large language model(abstract)；language model(abstract)；分类 cs.CL、cs.AI、cs.LG

2409.05152 2024-10-03 cs.CL cs.AI cs.DB cs.IR cs.LG 80%

OneGen: Efficient One-Pass Unified Generation and Retrieval for LLMs

Jintian Zhang, Cheng Peng, Mengshu Sun, Xiang Chen, Lei Liang, Zhiqiang Zhang, Jun Zhou, Huajun Chen, Ningyu Zhang

专题命中效率与部署：LLM(abstract)；large language model(abstract)；language model(abstract)；分类 cs.CL、cs.AI、cs.LG

Comments EMNLP 2024 Findings; code is available at https://github.com/zjunlp/OneGen

2409.04081 2024-10-03 cs.CL cs.AI cs.HC cs.LG 80%

UI-JEPA: Towards Active Perception of User Intent through Onscreen User Activity

Yicheng Fu, Raviteja Anantha, Prabal Vashisht, Jianpeng Cheng, Etai Littwin

专题命中效率与部署：LLM(abstract)；large language model(abstract)；language model(abstract)；分类 cs.CL、cs.AI、cs.LG

2409.11424 2024-09-19 cs.AR 80%

LlamaF: An Efficient Llama2 Architecture Accelerator on Embedded FPGAs

Han Xu, Yutong Li, Shihao Ji

专题命中效率与部署：LLM(abstract)；large language model(abstract)；language model(abstract)；post-training(abstract)

2409.04831 2024-09-10 cs.SE cs.AI cs.CL cs.CR cs.LG 80%

MILE: A Mutation Testing Framework of In-Context Learning Systems

Zeming Wei, Yihao Zhang, Meng Sun

专题命中效率与部署：LLM(abstract)；large language model(abstract)；language model(abstract)；分类 cs.CL、cs.AI、cs.LG

2408.13621 2024-08-28 cs.CV cs.AI cs.CL cs.LG 80%

Preliminary Investigations of a Multi-Faceted Robust and Synergistic Approach in Semiconductor Electron Micrograph Analysis: Integrating Vision Transformers with Large Language and Multimodal Models

Sakhinana Sagar Srinivas, Geethan Sannidhi, Sreeja Gangasani, Chidaksh Ravuru, Venkataramana Runkana

专题命中效率与部署：large language model(abstract)；language model(abstract)；prompting(abstract)；分类 cs.CL、cs.AI、cs.LG

Comments Published at Deployable AI (DAI) Workshop at AAAI-2024

2408.11865 2024-08-23 cs.CL cs.AI cs.LG 80%

How Susceptible are LLMs to Influence in Prompts?

Sotiris Anagnostidis, Jannis Bulian

专题命中效率与部署：LLM(abstract)；large language model(abstract)；language model(abstract)；分类 cs.CL、cs.AI、cs.LG

2402.07812 2024-08-09 cs.CL cs.AI cs.IR cs.LG 80%

Retrieval Augmented Thought Process for Private Data Handling in Healthcare

Thomas Pouplin, Hao Sun, Samuel Holt, Mihaela van der Schaar

专题命中效率与部署：LLM(abstract)；large language model(abstract)；language model(abstract)；分类 cs.CL、cs.AI、cs.LG

Comments 17 pages, 18 figures

2309.01249 2024-08-06 cs.AI cs.CL cs.LG 80%

Large AI Model Empowered Multimodal Semantic Communications

Feibo Jiang, Li Dong, Yubo Peng, Kezhi Wang, Kun Yang, Cunhua Pan, Xiaohu You

专题命中效率与部署：LLM(abstract)；large language model(abstract)；language model(abstract)；分类 cs.CL、cs.AI、cs.LG

Comments Accepted by IEEE CM

2408.01417 2024-08-05 cs.CL cs.AI cs.CV cs.LG 80%

Talk Less, Interact Better: Evaluating In-context Conversational Adaptation in Multimodal LLMs

Yilun Hua, Yoav Artzi

专题命中效率与部署：large language model(abstract)；language model(abstract)；prompting(abstract)；分类 cs.CL、cs.AI、cs.LG

Comments Accepted to COLM 2024

2405.17430 2024-07-30 cs.CV cs.AI cs.CL cs.LG 80%

Matryoshka Multimodal Models

Mu Cai, Jianwei Yang, Jianfeng Gao, Yong Jae Lee

专题命中效率与部署：LLM(abstract)；large language model(abstract)；language model(abstract)；分类 cs.CL、cs.AI、cs.LG

Comments Project Page: https://matryoshka-mm.github.io/

2407.14622 2024-07-23 cs.LG cs.AI cs.CL 80%

BOND: Aligning LLMs with Best-of-N Distillation

Pier Giuseppe Sessa, Robert Dadashi, Léonard Hussenot, Johan Ferret, Nino Vieillard, Alexandre Ramé, Bobak Shariari, Sarah Perrin, Abe Friesen, Geoffrey Cideron, Sertan Girgin, Piotr Stanczyk, Andrea Michi, Danila Sinopalnikov, Sabela Ramos, Amélie Héliou, Aliaksei Severyn, Matt Hoffman, Nikola Momchev, Olivier Bachem

专题命中效率与部署：large language model(abstract)；language model(abstract)；RLHF(abstract)；分类 cs.CL、cs.AI、cs.LG

2407.12866 2024-07-19 cs.CL cs.AI cs.LG 80%

Beyond KV Caching: Shared Attention for Efficient LLMs

Bingli Liao, Danilo Vasconcellos Vargas

专题命中效率与部署：large language model(abstract)；language model(abstract)；pretraining(abstract)；分类 cs.CL、cs.AI、cs.LG

2407.11030 2024-07-17 cs.LG cs.AI cs.CL 80%

DLO: Dynamic Layer Operation for Efficient Vertical Scaling of LLMs

Zhen Tan, Daize Dong, Xinyu Zhao, Jie Peng, Yu Cheng, Tianlong Chen

专题命中效率与部署：large language model(abstract)；language model(abstract)；SFT(abstract)；分类 cs.CL、cs.AI、cs.LG

2407.09527 2024-07-16 cs.CV cs.AI cs.CL cs.LG 80%

BitNet b1.58 Reloaded: State-of-the-art Performance Also on Smaller Networks

Jacob Nielsen, Peter Schneider-Kamp

专题命中效率与部署：large language model(abstract)；language model(abstract)；small language model(abstract)；分类 cs.CL、cs.AI、cs.LG

Comments 17 pages, 4 Tables, 14 grafs. Accepted to DeLTA

2403.02181 2024-07-10 cs.CL cs.AI cs.LG 80%

Not All Layers of LLMs Are Necessary During Inference

Siqi Fan, Xin Jiang, Xiang Li, Xuying Meng, Peng Han, Shuo Shang, Aixin Sun, Yequan Wang, Zhongyuan Wang

专题命中效率与部署：LLM(abstract)；large language model(abstract)；language model(abstract)；分类 cs.CL、cs.AI、cs.LG

2406.10101 2024-06-18 cs.SE 80%

Requirements are All You Need: From Requirements to Code with LLMs

Bingyang Wei

专题命中效率与部署：LLM(abstract)；large language model(abstract)；language model(abstract)；prompting(abstract)

2406.10290 2024-06-18 cs.CL cs.AI cs.LG 80%

MobileAIBench: Benchmarking LLMs and LMMs for On-Device Use Cases

Rithesh Murthy, Liangwei Yang, Juntao Tan, Tulika Manoj Awalgaonkar, Yilun Zhou, Shelby Heinecke, Sachin Desai, Jason Wu, Ran Xu, Sarah Tan, Jianguo Zhang, Zhiwei Liu, Shirley Kokane, Zuxin Liu, Ming Zhu, Huan Wang, Caiming Xiong, Silvio Savarese

专题命中效率与部署：LLM(abstract)；large language model(abstract)；language model(abstract)；分类 cs.CL、cs.AI、cs.LG

2405.20835 2024-06-06 cs.LG cs.AI cs.CL 80%

Outliers and Calibration Sets have Diminishing Effect on Quantization of Modern LLMs

Davide Paglieri, Saurabh Dash, Tim Rocktäschel, Jack Parker-Holder

专题命中效率与部署：large language model(abstract)；language model(abstract)；post-training(abstract)；分类 cs.CL、cs.AI、cs.LG

1. 效率与部署 22614 篇

Tree of Attacks: Jailbreaking Black-Box LLMs Automatically

Dynamic Vocabulary Pruning in Early-Exit LLMs

Prompt Optimization with EASE? Efficient Ordering-aware Automated Selection of Exemplars

Layer-Wise Quantization: A Pragmatic and Effective Method for Quantizing LLMs Beyond Integer Bit-Levels

LayerSkip: Enabling Early Exit Inference and Self-Speculative Decoding

What Matters in Transformers? Not All Attention is Needed

Unraveling the Mechanics of Learning-Based Demonstration Selection for In-Context Learning

Evidence-Focused Fact Summarization for Knowledge-Augmented Zero-Shot Question Answering

Everything Everywhere All at Once: LLMs can In-Context Learn Multiple Tasks in Superposition

Optimize Weight Rounding via Signed Gradient Descent for the Quantization of LLMs

LoRC: Low-Rank Compression for LLMs KV Cache with a Progressive Compression Strategy

Adaptive Inference-Time Compute: LLMs Can Predict if They Can Do Better, Even Mid-Generation

OneGen: Efficient One-Pass Unified Generation and Retrieval for LLMs

UI-JEPA: Towards Active Perception of User Intent through Onscreen User Activity

LlamaF: An Efficient Llama2 Architecture Accelerator on Embedded FPGAs

MILE: A Mutation Testing Framework of In-Context Learning Systems

Preliminary Investigations of a Multi-Faceted Robust and Synergistic Approach in Semiconductor Electron Micrograph Analysis: Integrating Vision Transformers with Large Language and Multimodal Models

How Susceptible are LLMs to Influence in Prompts?

Retrieval Augmented Thought Process for Private Data Handling in Healthcare

Large AI Model Empowered Multimodal Semantic Communications

Talk Less, Interact Better: Evaluating In-context Conversational Adaptation in Multimodal LLMs

Matryoshka Multimodal Models

BOND: Aligning LLMs with Best-of-N Distillation

Beyond KV Caching: Shared Attention for Efficient LLMs

DLO: Dynamic Layer Operation for Efficient Vertical Scaling of LLMs

BitNet b1.58 Reloaded: State-of-the-art Performance Also on Smaller Networks

Not All Layers of LLMs Are Necessary During Inference

Requirements are All You Need: From Requirements to Code with LLMs

MobileAIBench: Benchmarking LLMs and LMMs for On-Device Use Cases

Outliers and Calibration Sets have Diminishing Effect on Quantization of Modern LLMs