语言大模型 / LLM

CSPLADE: Learned Sparse Retrieval with Causal Language Models

Zhichao Xu, Aosong Feng, Yijun Tian, Haibo Ding, Lin Lee Cheong

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

Comments IJCNLP-AACL 2025 Main

Communication-Efficient Collaborative LLM Inference via Distributed Speculative Decoding

Ce Zheng, Tingting Yang

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

Comments Accepted in the Seventeenth International Conference on Wireless Communications and Signal Processing Oct. 23-25, 2025

SkyWalker: A Locality-Aware Cross-Region Load Balancer for LLM Inference

Tian Xia, Ziming Mao, Jamison Kerney, Ethan J. Jackson, Zhifei Li, Jiarong Xing, Scott Shenker, Ion Stoica

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

Efficient LLM Context Distillation

Rajesh Upadhayaya, Manish Raj Osti, Zachary Smith, Chritopher Kottmyer

机构 * School of Computer Science, Georgia Institute of Technology（计算机科学学院，佐治亚理工学院） 纠错

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

Wider or Deeper? Scaling LLM Inference-Time Compute with Adaptive Branching Tree Search

Yuichi Inoue, Kou Misaki, Yuki Imajuku, So Kuroki, Taishi Nakamura, Takuya Akiba

机构 * Sakana AI, Japan（日本Sakana AI） 纠错

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

Comments Accepted as a spotlight at NeurIPS 2025

Multi-modal Loop Closure Detection with Foundation Models in Severely Unstructured Environments

Laura Alejandra Encinar Gonzalez, John Folkesson, Rudolph Triebel, Riccardo Giubilato

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

Comments Under review for ICRA 2026

PPG-Distill: Efficient Photoplethysmography Signals Analysis via Foundation Model Distillation

Juntong Ni, Saurabh Kataria, Shengpu Tang, Carl Yang, Xiao Hu, Wei Jin

机构 * Department of Computer Science, Emory University（计算机科学系，埃默里大学） ； Nell Hodgson Woodruff School of Nursing, Emory University（Nell Hodgson Woodruff护理学院，埃默里大学） 纠错

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

Comments Accepted at NeurIPS 2025 TS4H, we release our code publicly at https://github.com/LingFengGold/PPG-Distill

DARN: Dynamic Adaptive Regularization Networks for Efficient and Robust Foundation Model Adaptation

Dhenenjay Yadav, Rohan Sawai

机构 * AxionOrbital Space（AxionOrbital空间） ； Virginia Tech（弗吉尼亚理工学院） 纠错

专题命中 效率与部署 ：foundation model(title,abstract)

SelaVPR++: Towards Seamless Adaptation of Foundation Models for Efficient Place Recognition

Feng Lu, Tong Jin, Xiangyuan Lan, Lijun Zhang, Yunpeng Liu, Yaowei Wang, Chun Yuan

机构 * Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen, China（清华大学深圳国际研究生院，清华大学，深圳，中国） ； Pengcheng Laboratory, Shenzhen, China（鹏城实验室，深圳，中国） ； Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, China（沈阳自动化研究所，中国科学院，沈阳，中国） ； Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, Chongqing, China（重庆绿色智能技术研究所，中国科学院，重庆，中国） ； Pazhou Laboratory (Huangpu), Guangzhou, China（琶洲实验室（黄埔），广州，中国） 纠错

专题命中 效率与部署 ：foundation model(title,abstract)

Comments accepted by T-PAMI

Journal ref IEEE Transactions on Pattern Analysis and Machine Intelligence, 2025

When retrieval outperforms generation: Dense evidence retrieval for scalable fake news detection

Alamgir Munir Qazi, John P. McCrae, Jamal Abdul Nasir

机构 * School of Computer Science, University of Galway, Ireland（Galway大学计算机科学学院） ； Research Ireland Insight Centre and ADAPT Centre, University of Galway, Ireland（Galway大学爱尔兰研究洞察中心和ADAPT研究中心） 纠错

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

Journal ref Proceedings of the 5th Conference on Language, Data and Knowledge, pages 255-265, Naples, Italy. Unior Press, September 2025

LLM4FaaS: No-Code Application Development using LLMs and FaaS

Minghe Wang, Tobias Pfandzelter, Trever Schirmer, David Bermbach

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

Comments Accepted for publication in 2025 IEEE/ACM 18th International Conference on Utility and Cloud Computing

EncouRAGe: Evaluating RAG Local, Fast, and Reliable

Jan Strich, Adeline Scharfenberg, Chris Biemann, Martin Semmann

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

Comments Currently under review

Cognitive Edge Computing: A Comprehensive Survey on Optimizing Large Models and AI Agents for Pervasive Deployment

Xubin Wang, Qing Li, Weijia Jia

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

Turning Adversaries into Allies: Reversing Typographic Attacks for Multimodal E-Commerce Product Retrieval

Janet Jenq, Hongda Shen

机构 * PitchBook USA（PitchBook美国公司） 纠错

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

LiveStar: Live Streaming Assistant for Real-World Online Video Understanding

Zhenyu Yang, Kairui Zhang, Yuhang Hu, Bing Wang, Shengsheng Qian, Bin Wen, Fan Yang, Tingting Gao, Weiming Dong, Changsheng Xu

机构 * Institute of Automation, Chinese Academy of Sciences（中国科学院自动化研究所） ； University of Chinese Academy of Sciences（中国科学院大学） ； ShanghaiTech University（上海科技大学） ； Kuaishou Technology（快手科技） ； Peng Cheng Laboratory（鹏城实验室） 纠错

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

Comments NeurIPS 2025 Accepted

Nonparametric Inference on Unlabeled Histograms

Yun Ma, Pengkun Yang

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

OvA-LP: A Simple and Efficient Framework for Federated Learning on Non-IID Data

Dongjin Park, Hasung Yeo, Joon-Woo Lee

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

MDM: Manhattan Distance Mapping of DNN Weights for Parasitic-Resistance-Resilient Memristive Crossbars

Matheus Farias, Wanghley Martins, H. T. Kung

机构 * Harvard University（哈佛大学） ； Duke University（杜克大学） 纠错

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

Comments 5 pages, 6 figures

NVIDIA Nemotron Nano V2 VL

NVIDIA, :, Amala Sanjay Deshmukh, Kateryna Chumachenko, Tuomas Rintamaki, Matthieu Le, Tyler Poon, Danial Mohseni Taheri, Ilia Karmanov, Guilin Liu, Jarno Seppanen, Guo Chen, Karan Sapra, Zhiding Yu, Adi Renduchintala, Charles Wang, Peter Jin, Arushi Goel, Mike Ranzinger, Lukas Voegtle, Philipp Fischer, Timo Roman, Wei Ping, Boxin Wang, Zhuolin Yang, Nayeon Lee, Shaokun Zhang, Fuxiao Liu, Zhiqi Li, Di Zhang, Greg Heinrich, Hongxu Yin, Song Han, Pavlo Molchanov, Parth Mannan, Yao Xu, Jane Polak Scowcroft, Tom Balough, Subhashree Radhakrishnan, Paris Zhang, Sean Cha, Ratnesh Kumar, Zaid Pervaiz Bhat, Jian Zhang, Darragh Hanley, Pritam Biswas, Jesse Oliver, Kevin Vasques, Roger Waleffe, Duncan Riach, Oluwatobi Olabiyi, Ameya Sunil Mahabaleshwarkar, Bilal Kartal, Pritam Gundecha, Khanh Nguyen, Alexandre Milesi, Eugene Khvedchenia, Ran Zilberstein, Ofri Masad, Natan Bagrov, Nave Assaf, Tomer Asida, Daniel Afrimi, Amit Zuker, Netanel Haber, Zhiyu Cheng, Jingyu Xin, Di Wu, Nik Spirin, Maryam Moosaei, Roman Ageev, Vanshil Atul Shah, Yuting Wu, Daniel Korzekwa, Unnikrishnan Kizhakkemadam Sreekumar, Wanli Jiang, Padmavathy Subramanian, Alejandra Rico, Sandip Bhaskar, Saeid Motiian, Kedi Wu, Annie Surla, Chia-Chih Chen, Hayden Wolff, Matthew Feinberg, Melissa Corpuz, Marek Wawrzos, Eileen Long, Aastha Jhunjhunwala, Paul Hendricks, Farzan Memarian, Benika Hall, Xin-Yu Wang, David Mosallanezhad, Soumye Singhal, Luis Vega, Katherine Cheung, Krzysztof Pawelec, Michael Evans, Katherine Luna, Jie Lou, Erick Galinkin, Akshay Hazare, Kaustubh Purandare, Ann Guan, Anna Warno, Chen Cui, Yoshi Suhara, Shibani Likhite, Seph Mard, Meredith Price, Laya Sleiman, Saori Kaji, Udi Karpas, Kari Briski, Joey Conway, Michael Lightstone, Jan Kautz, Mohammad Shoeybi, Mostofa Patwary, Jonathen Cohen, Oleksii Kuchaiev, Andrew Tao, Bryan Catanzaro

机构 * NVIDIA 纠错

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

Efficient and Unbiased Sampling from Boltzmann Distributions via Variance-Tuned Diffusion Models

Fengzhe Zhang, Laurence I. Midgley, José Miguel Hernández-Lobato

机构 * University of Cambridge（剑桥大学） ； Ångström AI（安格斯特罗姆人工智能） 纠错

专题命中 效率与部署 ：post-training(abstract)；分类 cs.LG

8bit-GPT: Exploring Human-AI Interaction on Obsolete Macintosh Operating Systems

Hala Sheta

机构 * Department of Computer Science University of Waterloo（计算机科学系大学水力学院） 纠错

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

Comments NeurIPS Creative AI Track 2025: Humanity

DMA: Online RAG Alignment with Human Feedback

Yu Bai, Yukai Miao, Dawei Wang, Li Chen, Fei Long, Rundi Zhai, Dan Li, Yanyu Ren, Tianfeng Liu, Hongtao Xie, Ce Yang, Xuhui Cai

机构 * Zhongguancun Laboratory（中关村实验室） ； Tsinghua University（清华大学） ； China Mobile Communications Group Co., Ltd.（中国移动通信集团有限公司） ； Beijing University of Posts and Telecommunications（北京邮电大学） 纠错

专题命中 效率与部署 ：LLM(abstract)；分类 cs.AI

Generalizable, real-time neural decoding with hybrid state-space models

Avery Hee-Woon Ryoo, Nanda H. Krishna, Ximeng Mao, Mehdi Azabou, Eva L. Dyer, Matthew G. Perich, Guillaume Lajoie

专题命中 效率与部署 ：pretraining(abstract)；分类 cs.LG

Comments NeurIPS 2025

Journal ref The Thirty-ninth Annual Conference on Neural Information Processing Systems, 2025

Semantic-Guided Natural Language and Visual Fusion for Cross-Modal Interaction Based on Tiny Object Detection

Xian-Hong Huang, Hui-Kai Su, Chi-Chia Sun, Jun-Wei Hsieh

机构 * Department of Electrical Engineering, National Formosa University, Taiwan（台湾国立Formosa大学电子工程系） ； Department of Electrical Engineering, National Taipei University, Taiwan（台湾国立台北大学电子工程系） ； College of Artificial Intelligence and Green Energy, National Yang Ming Chiao Tung University, Taiwan（台湾国立阳明交通大学人工智能与再生能源学院） 纠错

专题命中 效率与部署 ：language model(abstract)

Black-box Context-free Grammar Inference for Readable & Natural Grammars

Mohammad Rifat Arefin, Shanto Rahman, Christoph Csallner

专题命中 效率与部署 ：LLM(abstract)

Comments 20 pages

Large Language Models for Explainable Threat Intelligence

Tiago Dinis, Miguel Correia, Roger Tavares

专题命中 领域大模型 ：large language model(title,abstract)；language model(title,abstract)；LLM(abstract)；分类 cs.CL

Generating Computational Cognitive Models using Large Language Models

Milena Rmus, Akshay K. Jagadish, Marvin Mathony, Tobias Ludwig, Eric Schulz

机构 * Helmholtz Munich（海德堡-慕尼黑研究中心） ； Princeton University（普林斯顿大学） ； Tübingen University（图宾根大学） 纠错

专题命中 领域大模型 ：large language model(title,abstract)；language model(title,abstract)；LLM(abstract)；分类 cs.LG

Cleaning Maintenance Logs with LLM Agents for Improved Predictive Maintenance

Valeriu Dimidov, Faisal Hawlader, Sasan Jafarnejad, Raphaël Frank

机构 * Interdisciplinary Centre for Security, Reliability ； Trust (SnT) University of Luxembourg 29 Avenue J.F. Kennedy L-1855, Luxembourg 纠错

专题命中 领域大模型 ：LLM(title,abstract)；large language model(abstract)；language model(abstract)；分类 cs.AI、cs.LG

Leveraging Large Language Models for Code Translation and Software Development in Scientific Computing

Akash Dhruv, Anshu Dubey

机构 * Institute for Clarity in Documentation（清晰文档研究所） ； Inria Paris-Rocquencourt（巴黎-罗克琴特研究所） ； Rajiv Gandhi University（拉贾·甘地大学） ； Tsinghua University（清华大学） ； Palmer Research Laboratories（帕勒尔研究实验室） ； Argonne National Laboratory（阿贡国家实验室） 纠错

专题命中 领域大模型 ：large language model(title)；language model(title)；分类 cs.AI

AIRepr: An Analyst-Inspector Framework for Evaluating Reproducibility of LLMs in Data Science

Qiuhai Zeng, Claire Jin, Xinyue Wang, Yuhan Zheng, Qunhua Li

机构 * Pennsylvania State University（宾夕法尼亚州立大学） ； Carnegie Mellon University（卡内基梅隆大学） ； International Monetary Fund（国际货币基金组织） 纠错

专题命中 领域大模型 ：LLM(abstract)；large language model(abstract)；language model(abstract)；prompting(abstract)

Comments Accepted to 2025 EMNLP findings