语言大模型 / LLM

SLM-SQL: An Exploration of Small Language Models for Text-to-SQL

Lei Sheng, Shuai-Shuai Xu

机构 * Wuhan University of Technology（武汉理工大学） ； University of Science and Technology of China（中国科学技术大学） 纠错

专题命中 效率与部署 ：language model(title,abstract)；small language model(title,abstract)；SLM(title,abstract)；large language model(abstract)

Comments 16 pages, 2 figures, work in progress

OFCnetLLM: Large Language Model for Network Monitoring and Alertness

Hong-Jun Yoon, Mariam Kiran, Danial Ebling, Joe Breen

机构 * Oak Ridge National Laboratory（奥克兰国家实验室） ； Utah Education Network（犹他州教育网络） ； University of Utah（犹他大学） 纠错

专题命中 效率与部署 ：large language model(title,abstract)；language model(title,abstract)；LLM(abstract)；分类 cs.AI

A Survey on Large Language Model Acceleration based on KV Cache Management

Haoyang Li, Yiming Li, Anxin Tian, Tianhao Tang, Zhanchao Xu, Xuejia Chen, Nicole Hu, Wei Dong, Qing Li, Lei Chen

机构 * Department of Computing, The Hong Kong Polytechnic University（计算系，香港理工大学） ； Department of Computer Science and Engineering（计算机科学与工程系） ； Department of Computer Science and Technology（计算机科学与技术系） ； Department of Computing and Data Science（计算与数据科学系） 纠错

专题命中 效率与部署 ：large language model(title,abstract)；language model(title,abstract)；LLM(abstract)；分类 cs.AI

Comments Accepted to TMLR 2025. The revised version incorporates more papers and has been further polished

SmallThinker: A Family of Efficient Large Language Models Natively Trained for Local Deployment

Yixin Song, Zhenliang Xue, Dongliang Wei, Feiyang Chen, Jianxiang Gao, Junchen Liu, Hangyu Liang, Guangshuo Qin, Chengrong Tian, Bo Wen, Longyu Zhao, Xinrui Zheng, Zeyu Mi, Haibo Chen

机构 * Institute of Parallel and Distributed Systems, Shanghai Jiao Tong University（并行与分布式系统研究所，上海交通大学） ； School of Artificial Intelligence, Shanghai Jiao Tong University（人工智能学院，上海交通大学） ； Zenergize AI 纠错

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

Enhancing Ultra-Low-Bit Quantization of Large Language Models Through Saliency-Aware Partial Retraining

Deyu Cao, Samin Aref

机构 * The University of Tokyo（东京大学） ； Department of Mechanical and Industrial Engineering, University of Toronto（多伦多大学机械与工业工程系） 纠错

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

Comments This is a post-peer-review accepted manuscript from the proceedings of the 22nd International Conference on Modeling Decisions for Artificial Intelligence (MDAI'25). The publisher authenticated version and full citation details are available on Springer's website (LNAI 15957). https://doi.org/10.1007/978-3-032-00891-6_28

Fuzzing: Randomness? Reasoning! Efficient Directed Fuzzing via Large Language Models

Xiaotao Feng, Xiaogang Zhu, Kun Hu, Jincheng Wang, Yingjie Cao, Guang Gong, Jianfeng Pan

机构 * Security Technology Inc.（360安全技术公司） ； School of Science Edith Cowan University（科学学院，埃迪斯科文大学） 纠错

专题命中 效率与部署 ：large language model(title,abstract)；language model(title,abstract)；分类 cs.AI

An Explainable Emotion Alignment Framework for LLM-Empowered Agent in Metaverse Service Ecosystem

Qun Ma, Xiao Xue, Ming Zhang, Yifan Shen, Zihan Zhao

机构 * College of Intelligence and Computing（智能与计算学院） ； Tianjin University（天津大学） ； Tianjin Key Laboratory of Healhy Habitat and Smart Technology（天津健康人居环境与智能技术重点实验室） ； Laboratory of Computation and Analytics of Complex Management Systems（复杂管理系统计算与分析实验室） ； Faculty of Environment, Science and Economy（环境、科学与经济学院） 纠错

专题命中 效率与部署 ：LLM(title,abstract)；large language model(abstract)；language model(abstract)；分类 cs.AI

Towards the Law of Capacity Gap in Distilling Language Models

Chen Zhang, Qiuchi Li, Dawei Song, Zheyu Ye, Yan Gao, Yan Hu

机构 * Beijing Institute of Technology（北京理工大学） ； University of Copenhagen（哥本哈根大学） ； The Open University（开放大学） ； Xiaohongshu（小红书） 纠错

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

Comments 32 pages, 10 figures, 15 tables, accepted to ACL 2025. Code and checkpoints are available at https://github.com/GeneZC/MiniMA

Application of Vision-Language Model to Pedestrians Behavior and Scene Understanding in Autonomous Driving

Haoxiang Gao, Li Zhang, Yu Zhao, Zhou Yang, Jinghan Cao

机构 * ECE Department（电子工程系） ； Carnegie Mellon University（卡内基梅隆大学） ； Computer Science Department（计算机科学系） ； Columbia University（哥伦比亚大学） ； Rotman School of Management（罗特曼管理学院） ； University of Toronto（多伦多大学） ； Department of Statistics（统计学系） ； George Washington University（乔治华盛顿大学） ； Department of Computer Science（计算机科学系） ； San Francisco State University（旧金山州立大学） 纠错

专题命中 效率与部署 ：language model(title,abstract)；foundation model(abstract)；分类 cs.AI、cs.LG

Falcon-H1: A Family of Hybrid-Head Language Models Redefining Efficiency and Performance

Jingwei Zuo, Maksim Velikanov, Ilyas Chahed, Younes Belkada, Dhia Eddine Rhayem, Guillaume Kunsch, Hakim Hacid, Hamza Yous, Brahim Farhat, Ibrahim Khadraoui, Mugariya Farooq, Giulia Campesan, Ruxandra Cojocaru, Yasser Djilali, Shi Hu, Iheb Chaabane, Puneesh Khanna, Mohamed El Amine Seddik, Ngoc Dung Huynh, Phuc Le Khac, Leen AlQadi, Billel Mokeddem, Mohamed Chami, Abdalgader Abubaker, Mikhail Lubinets, Kacper Piskorski, Slim Frikha

机构 * Falcon LLM Team（Falcon LLM团队） 纠错

专题命中 效率与部署 ：language model(title,abstract)；large language model(abstract)；分类 cs.CL

Comments Technical report of Falcon-H1 model series

TypyBench: Evaluating LLM Type Inference for Untyped Python Repositories

Honghua Dong, Jiacheng Yang, Xun Deng, Yuhe Jiang, Gennady Pekhimenko, Fan Long, Xujie Si

机构 * University of Toronto（多伦多大学） ； Vector Institute（向量研究所） ； CIFAR AI Chair（CIFAR人工智能主席） 纠错

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

Journal ref Proceedings of the 42nd International Conference on Machine Learning, Vancouver, Canada. PMLR 267, 2025

Mitigating Response Delays in Free-Form Conversations with LLM-powered Intelligent Virtual Agents

Mykola Maslych, Mohammadreza Katebi, Christopher Lee, Yahya Hmaiti, Amirpouya Ghasemaghaei, Christian Pumarada, Janneese Palmer, Esteban Segarra Martinez, Marco Emporio, Warren Snipes, Ryan P. McMahan, Joseph J. LaViola

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

Comments 15 pages, 8 figures. Published at the 7th ACM Conference on Conversational User Interfaces (CUI '25), July 8-10, 2025, Waterloo, Canada. Open-source code available at https://github.com/ISUE/iva-cui

Journal ref Proceedings of the 7th ACM Conference on Conversational User Interfaces (CUI '25), 2025, Article 49, 1-15

Lightweight Online Adaption for Time Series Foundation Model Forecasts

Thomas L. Lee, William Toner, Rajkarn Singh, Artjom Joosen, Martin Asenov

机构 * intern（实习生） ； Huawei SIR Lab, Edinburgh Research Centre, UK（华为SIR实验室，爱丁堡研究中心，英国） ； School of Informatics, University of Edinburgh, UK（信息学院，爱丁堡大学，英国） 纠错

专题命中 效率与部署 ：foundation model(title,abstract)；分类 cs.LG

Comments 9 pages, Published at ICML 2025

ViM-VQ: Efficient Post-Training Vector Quantization for Visual Mamba

Juncan Deng, Shuaiting Li, Zeyu Wang, Kedong Xu, Hong Gu, Kejie Huang

机构 * Zhejiang University（浙江大学） ； vivo Mobile Communication Co., Ltd（vivo移动通信有限公司） 纠错

专题命中 效率与部署 ：post-training(title,abstract)

Repair-R1: Better Test Before Repair

Haichuan Hu, Xiaochen Xie, Quanjun Zhang

机构 * Nanjing University of Science and Technology（南京理工大学） 纠错

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

Efficient Differentially Private Fine-Tuning of LLMs via Reinforcement Learning

Afshin Khadangi, Amir Sartipi, Igor Tchappi, Ramin Bahmani, Gilbert Fridgen

机构 * SnT, University of Luxembourg（卢森堡大学SnT学院） 纠错

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

BlockFFN: Towards End-Side Acceleration-Friendly Mixture-of-Experts with Chunk-Level Activation Sparsity

Chenyang Song, Weilin Zhao, Xu Han, Chaojun Xiao, Yingfa Chen, Yuxuan Li, Zhiyuan Liu, Maosong Sun

机构 * Dept. of Comp. Sci. & Tech., Institute for AI, Tsinghua University, Beijing, China（计算机科学与技术系，人工智能研究院，清华大学，北京，中国） 纠错

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

Comments 21 pages, 7 figures, 15 tables

Magentic-UI: Towards Human-in-the-loop Agentic Systems

Hussein Mozannar, Gagan Bansal, Cheng Tan, Adam Fourney, Victor Dibia, Jingya Chen, Jack Gerrits, Tyler Payne, Matheus Kunzler Maldaner, Madeleine Grunde-McLaughlin, Eric Zhu, Griffin Bassman, Jacob Alber, Peter Chang, Ricky Loynd, Friederike Niedtner, Ece Kamar, Maya Murad, Rafah Hosn, Saleema Amershi

机构 * Microsoft Research AI Frontiers（微软研究院人工智能前沿） 纠错

专题命中 效率与部署 ：large language model(abstract)；language model(abstract)；分类 cs.AI

Basic Reading Distillation

Zhi Zhou, Sirui Miao, Xiangyu Duan, Hao Yang, Min Zhang

机构 * School of Computer Science and Technology, Soochow University（苏州大学计算机科学与技术学院） ； Huawei Translation Services Center（华为翻译服务中心） 纠错

专题命中 效率与部署 ：large language model(abstract)；language model(abstract)；分类 cs.CL

Comments Accepted by ACL2025

Local Mixtures of Experts: Essentially Free Test-Time Training via Model Merging

Ryo Bertolissi, Jonas Hübotter, Ido Hakimi, Andreas Krause

机构 * ETH Zürich（苏黎世联邦理工学院） 纠错

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

TextSAM-EUS: Text Prompt Learning for SAM to Accurately Segment Pancreatic Tumor in Endoscopic Ultrasound

Pascal Spiegler, Taha Koleilat, Arash Harirpoush, Corey S. Miller, Hassan Rivaz, Marta Kersten-Oertel, Yiming Xiao

机构 * Concordia University（康科迪亚大学） ； Jewish General Hospital（犹太总医院） ； McGill University Faculty of Medicine（麦吉尔大学医学院） ； Lady Davis Institute for Medical Research（拉德克利夫医学研究 institute） 纠错

专题命中 效率与部署 ：foundation model(abstract)；分类 cs.AI

Comments Accepted to ICCV 2025 Workshop CVAMD

ReverBERT: A State Space Model for Efficient Text-Driven Speech Style Transfer

Michael Brown, Sofia Martinez, Priya Singh

专题命中 效率与部署 ：language model(abstract)；分类 cs.CL

Comments arXiv admin note: This paper has been withdrawn by arXiv due to disputed and unverifiable authorship and affiliation

RecConv: Efficient Recursive Convolutions for Multi-Frequency Representations

Mingshu Zhao, Yi Luo, Yong Ouyang

机构 * Sichuan Energy Internet Research Institute, Tsinghua University（四川能源互联网研究院，清华大学） 纠错

专题命中 效率与部署 ：prompting(abstract)

Comments Tech report; Added supplementary material; Added more experiments;