语言大模型 / LLM

Play by the Type Rules: Inferring Constraints for LLM Functions in Declarative Programs

Parker Glenn, Alfy Samuel, Daben Liu

机构 * Capital One 纠错

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

Why Do Some Inputs Break Low-Bit LLM Quantization?

Ting-Yun Chang, Muru Zhang, Jesse Thomason, Robin Jia

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

Comments EMNLP 2025

Enhancing Targeted Adversarial Attacks on Large Vision-Language Models via Intermediate Projector

Yiming Cao, Yanjie Li, Kaisheng Liang, Bin Xiao

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

Long Video Understanding with Learnable Retrieval in Video-Language Models

Jiaqi Xu, Cuiling Lan, Wenxuan Xie, Xuejin Chen, Yan Lu

机构 * School of Information Science and Technology, University of Science and Technology of China（信息科学与技术学院，中国科学技术大学） ； Microsoft Research Asia（微软亚洲研究院） 纠错

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

Comments Accepted by IEEE Transactions on Multimedia (TMM)

Adaptive Guidance Semantically Enhanced via Multimodal LLM for Edge-Cloud Object Detection

Yunqing Hu, Zheming Yang, Chang Zhao, Wen Ji

机构 * Institute of Computing Technology, Chinese Academy of Sciences（中国科学院计算技术研究所） ； Institute of AI for Industries（工业人工智能研究所） ； University of Chinese Academy of Sciences（中国科学院大学） 纠错

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

CollaPipe: Adaptive Segment-Optimized Pipeline Parallelism for Collaborative LLM Training in Heterogeneous Edge Networks

Jiewei Chen, Xiumei Deng, Zehui Xiong, Shaoyong Guo, Xuesong Qiu, Ping Wang, Dusit Niyato

机构 * State Key Laboratory of Networking and Switching Technology（网络与交换技术国家重点实验室） ； Beijing University of Posts and Telecommunications（北京邮电大学） ； Singapore University of Technology and Design（新加坡科技设计大学） ； School of Electronics, Electrical Engineering and Computer Science（电子、电气与计算机科学学院） ； Queen’s University Belfast（贝尔法斯特女王大学） ； Dept. of Electrical Engineering & Computer Science（电气与计算机科学系） ； Lassonde School of Engineering（拉索nde 工程学院） ； York University（约克大学） ； College of Computing and Data Science（计算与数据科学学院） ； Nanyang Technological University（南洋理工大学） 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 Submitted to IEEE for review

To Trust Or Not To Trust Your Vision-Language Model's Prediction

Hao Dong, Moru Liu, Jian Liang, Eleni Chatzi, Olga Fink

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

CANDLE: A Cross-Modal Agentic Knowledge Distillation Framework for Interpretable Sarcopenia Diagnosis

Yuqi Jin, Zhenhao Shuai, Zihan Hu, Weiteng Zhang, Weihao Xie, Jianwei Shuai, Xian Shen, Zhen Feng

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

Comments 11 pages, 4 figures, 5 tables

Pipeline Parallelism is All You Need for Optimized Early-Exit Based Self-Speculative Decoding

Ruanjun Li, Ziheng Liu, Yuanming Shi, Jiawei Shao, Chi Zhang, Xuelong Li

机构 * TeleAI ； ShanghaiTech University（上海科技大学） ； Shanghai Jiao Tong University（上海交通大学） 纠错

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

Comments 17 pages, 7 figures

ShinkaEvolve: Towards Open-Ended And Sample-Efficient Program Evolution

Robert Tjarko Lange, Yuki Imajuku, Edoardo Cetin

机构 * Sakana AI 纠错

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

Comments 52 pages, 14 figures

Compression Strategies for Efficient Multimodal LLMs in Medical Contexts

Tanvir A. Khan, Aranya Saha, Ismam N. Swapnil, Mohammad A. Haque

机构 * Department of Electrical and Electronic Engineering, Bangladesh University of Engineering and Technology (BUET)（电子与电气工程系，孟加拉国工程与技术大学） 纠错

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

Comments 16 pages, 7 figures

FedOne: Query-Efficient Federated Learning for Black-box Discrete Prompt Learning

Ganyu Wang, Jinjie Fang, Maxwell J. Yin, Bin Gu, Xi Chen, Boyu Wang, Yi Chang, Charles Ling

机构 * Western University（温莎大学） ； Jilin University（吉林大学） ； McGill University（麦吉尔大学） ； Vector Institute（向量研究所） 纠错

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

Comments Published in Proceedings of the 42nd International Conference on Machine Learning

Journal ref Proceedings of the 42nd International Conference on Machine Learning, Vancouver, Canada, PMLR267, 2025

MVVM: Deploy Your AI Agents-Securely, Efficiently, Everywhere

Yiwei Yang, Aibo Hu, Yusheng Zheng, Brian Zhao, Xinqi Zhang, Dawei Xiang, Kexin Chu, Wei Zhang, Andi Quinn

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

Enhancing RAG Efficiency with Adaptive Context Compression

Shuyu Guo, Shuo Zhang, Zhaochun Ren

机构 * Shandong University（山东大学） ； Bloomberg（彭博） ； Leiden University（莱顿大学） 纠错

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

Advancing Speech Summarization in Multi-modal LLMs with Reinforcement Learning

Shaoshi Ling, Gang Liu, Guoli Ye, Jinyu Li

机构 * Microsoft CoreAI（微软核心人工智能） 纠错

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

Are We Scaling the Right Thing? A System Perspective on Test-Time Scaling

Youpeng Zhao, Jinpeng LV, Di Wu, Jun Wang, Christopher Gooley

机构 * University of Central Florida（中央佛罗里达大学） ； Microsoft Research（微软研究院） 纠错

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

Bridging Information Gaps with Comprehensive Answers: Improving the Diversity and Informativeness of Follow-Up Questions

Zhe Liu, Taekyu Kang, Haoyu Wang, Seyed Hossein Alavi, Vered Shwartz

机构 * University of British Columbia（不列颠哥伦比亚大学） ； Vector Insitute（向量研究所） 纠错

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

Comments 9 pages, 3 figures, 8 tables, submitted to StarSEM 2025

BurstEngine: an Efficient Distributed Framework for Training Transformers on Extremely Long Sequences of over 1M Tokens

Ao Sun, Weilin Zhao, Xu Han, Cheng Yang, Zhiyuan Liu, Chuan Shi, Maosong sun

专题命中 效率与部署 ：language model(abstract)

Learning Contextual Retrieval for Robust Conversational Search

Seunghan Yang, Juntae Lee, Jihwan Bang, Kyuhong Shim, Minsoo Kim, Simyung Chang

专题命中 效率与部署 ：LLM(abstract)

Comments EMNLP 2025 main conference

From Slow Bidirectional to Fast Autoregressive Video Diffusion Models

Tianwei Yin, Qiang Zhang, Richard Zhang, William T. Freeman, Fredo Durand, Eli Shechtman, Xun Huang

机构 * MIT（麻省理工学院） ； Adobe（Adobe公司） 纠错

专题命中 效率与部署 ：prompting(abstract)

Comments CVPR 2025. Project Page: https://causvid.github.io/

Context-Masked Meta-Prompting for Privacy-Preserving LLM Adaptation in Finance

Sayash Raaj Hiraou

机构 * Fidelity Investments（富达投资） ； Bengaluru, India（印度班加罗尔） 纠错

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

Efficient Fine-Tuning of Large Language Models for Automated Medical Documentation

Hui Yi Leong, Yi Fan Gao, Ji Shuai, Yang Zhang, Uktu Pamuksuz

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

Comments 4 pages, 3 Figures, 3 Tables. The final version will be published in the proceedings of the IEEE conference

Performance of Large Language Models in Answering Critical Care Medicine Questions

Mahmoud Alwakeel, Aditya Nagori, An-Kwok Ian Wong, Neal Chaisson, Vijay Krishnamoorthy, Rishikesan Kamaleswaran

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

The Knowledge-Behaviour Disconnect in LLM-based Chatbots

Jan Broersen

机构 * Jan Broersen 纠错

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

SAFE: Improving LLM Systems using Sentence-Level In-generation Attribution

João Eduardo Batista, Emil Vatai, Mohamed Wahib

机构 * RIKEN-CCS Kobe, Japan（日本神户RIKEN-CCS） 纠错

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

Comments 30 pages (9 pages of content, 5 pages of references, 16 pages of supplementary material), 7 figures, 13 tables

LLM-Powered AI Tutors with Personas for d/Deaf and Hard-of-Hearing Online Learners

Haocong Cheng, Si Chen, Christopher Perdriau, Shriya Mokkapati, Yun Huang

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

EchoBench: Benchmarking Sycophancy in Medical Large Vision-Language Models

Botai Yuan, Yutian Zhou, Yingjie Wang, Fushuo Huo, Yongcheng Jing, Li Shen, Ying Wei, Zhiqi Shen, Ziwei Liu, Tianwei Zhang, Jie Yang, Dacheng Tao

机构 * Nanyang Technological University（南洋理工大学） ； Shanghai Jiao Tong University（上海交通大学） ； Fudan University（复旦大学） ； Sun Yat-sen University（中山大学） ； Zhejiang University（浙江大学） 纠错

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

Comments 29 pages, 6 figures

Modeling Subjectivity in Cognitive Appraisal with Language Models

Yuxiang Zhou, Hainiu Xu, Desmond C. Ong, Maria Liakata, Petr Slovak, Yulan He

机构 * Queen Mary University of London（伦敦大学玛丽女王学院） ； King’s College London（伦敦大学国王学院） ； The University of Texas at Austin（德克萨斯大学奥斯汀分校） ； The Alan Turing Institute（艾伦·图灵研究所） 纠错

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

Comments EMNLP 2025 Findings

Unveiling the Merits and Defects of LLMs in Automatic Review Generation for Scientific Papers

Ruochi Li, Haoxuan Zhang, Edward Gehringer, Ting Xiao, Junhua Ding, Haihua Chen

机构 * North Carolina State University（北卡罗来纳州立大学） ； University of North Texas（德克萨斯大学） 纠错

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

Comments Accepted as short paper at 25th IEEE International Conference on Data Mining

Towards Self-Supervised Foundation Models for Critical Care Time Series

Katja Naasunnguaq Jagd, Rachael DeVries, Ole Winther

机构 * David S. Hippocampus Department of Computer Science Cranberry-Lemon University（Cranberry-Lemon大学计算机科学系） 纠错

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

Comments Accepted to NeurIPS 2025 workshop Learning from Time Series for Health (TS4H)