语言大模型 / LLM

PTQ1.61: Push the Real Limit of Extremely Low-Bit Post-Training Quantization Methods for Large Language Models

Jiaqi Zhao, Miao Zhang, Ming Wang, Yuzhang Shang, Kaihao Zhang, Weili Guan, Yaowei Wang, Min Zhang

机构 * Harbin Institute of Technology (Shenzhen)（哈尔滨工业大学（深圳）） ； Illinois Institute of Technology（伊利诺伊大学香槟分校） 纠错

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

Comments 20 pages, 11 figures

Efficient Strategy for Improving Large Language Model (LLM) Capabilities

Julián Camilo Velandia Gutiérrez

机构 * Universidad Nacional de Colombia（哥伦比亚国立大学） 纠错

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

Comments Based on master's thesis in Systems and Computer Engineering, Universidad Nacional de Colombia (2025)

Fine-Tuning and Deploying Large Language Models Over Edges: Issues and Approaches

Yanjie Dong, Haijun Zhang, Chengming Li, Song Guo, Victor C. M. Leung, Xiping Hu

机构 * Shenzhen MSU-BIT University（深圳MSU-BIT大学） ； University of Science and Technology Beijing（北京科技大学） ； The Hong Kong University of Science and Technology（香港科技大学） 纠错

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

TRAIL: Joint Inference and Refinement of Knowledge Graphs with Large Language Models

Xinkui Zhao, Haode Li, Yifan Zhang, Guanjie Cheng, Yueshen Xu

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

Improving Crash Data Quality with Large Language Models: Evidence from Secondary Crash Narratives in Kentucky

Xu Zhang, Mei Chen

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

Comments 19 pages, 2 figures

Learning to Inference Adaptively for Multimodal Large Language Models

Zhuoyan Xu, Khoi Duc Nguyen, Preeti Mukherjee, Saurabh Bagchi, Somali Chaterji, Yingyu Liang, Yin Li

机构 * University of Wisconsin-Madison（威斯康星大学麦迪逊分校） ； Purdue University（普渡大学） ； The University of Hong Kong（香港大学） 纠错

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

Comments Published at ICCV 2025

Efficient Scaling for LLM-based ASR

Bingshen Mu, Yiwen Shao, Kun Wei, Dong Yu, Lei Xie

机构 * Tencent AI Lab（腾讯人工智能实验室） 纠错

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

Comments Accepted by ASRU 2025

EdgeInfinite-Instruct: Bridging SFT-Based Optimization and NPU-Level Efficiency for Edge Devices

Jiyu Chen, Poh Seng Lim, Shuang Peng, Daxiong Luo, JungHau Foo, Yap Deep, Timothy Lee Jun Jie, Kelvin Teh Kae Wen, Fan Yang, Danyu Feng, Hao-Yun Chen, Peng-Wen Chen, Fangyuan Li, Xiaoxin Chen, Wong Wai Mun

专题命中 效率与部署 ：SFT(title,abstract)；large language model(abstract)；language model(abstract)；post-training(abstract)

Comments The data and method in the paper need to be re-audited

From Learning to Unlearning: Biomedical Security Protection in Multimodal Large Language Models

Dunyuan Xu, Xikai Yang, Yaoqian Li, Jinpeng Li, Pheng-Ann Heng

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

GeRe: Towards Efficient Anti-Forgetting in Continual Learning of LLM via General Samples Replay

Yunan Zhang, Shuoran Jiang, Mengchen Zhao, Yuefeng Li, Yang Fan, Xiangping Wu, Qingcai Chen

机构 * Department of Computer Science and Technology, Harbin Institute of Technology（计算机科学与技术系，哈尔滨工业大学） 纠错

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

Automatic LLM Red Teaming

Roman Belaire, Arunesh Sinha, Pradeep Varakantham

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

LLM-Prior: A Framework for Knowledge-Driven Prior Elicitation and Aggregation

Yongchao Huang

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

P-Aligner: Enabling Pre-Alignment of Language Models via Principled Instruction Synthesis

Feifan Song, Bofei Gao, Yifan Song, Yi Liu, Weimin Xiong, Yuyang Song, Tianyu Liu, Guoyin Wang, Houfeng Wang

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

Gather and Trace: Rethinking Video TextVQA from an Instance-oriented Perspective

Yan Zhang, Gangyan Zeng, Daiqing Wu, Huawen Shen, Binbin Li, Yu Zhou, Can Ma, Xiaojun Bi

机构 * Institute of Information Engineering, Chinese Academy of Sciences School of Cyber Security, University of Chinese Academy of Sciences Beijing China ； School of Cyber Science ； Engineering, Nanjing University of Science ； VCIP \& TMCC \& DISSec, College of Computer Science, Nankai University Tianjin China ； Key Laboratory of Ethnic Language Intelligent Analysis ； Security Governance of MOE, Minzu University of China Beijing China ； Institute of Information Engineering, Chinese Academy of Sciences ； School of Cyber Security, University of Chinese Academy of Sciences ； VCIP \& TMCC \& DISSec, College of Computer Science, Nankai University ； Security Governance of MOE, Minzu University of China 纠错

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

Comments Accepted by 2025 ACM MM

PAIRS: Parametric-Verified Adaptive Information Retrieval and Selection for Efficient RAG

Wang Chen, Guanqiang Qi, Weikang Li, Yang Li, Deguo Xia, Jizhou Huang

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

Beyond Manually Designed Pruning Policies with Second-Level Performance Prediction: A Pruning Framework for LLMs

Zuxin Ma, Yunhe Cui, Yongbin Qin

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

p-MoD: Building Mixture-of-Depths MLLMs via Progressive Ratio Decay

Jun Zhang, Desen Meng, Zhengming Zhang, Zhenpeng Huang, Tao Wu, Limin Wang

机构 * State Key Laboratory for Novel Software Technology, Nanjing University（南京大学新型软件技术国家重点实验室） ； China Mobile Research Institute（中国移动研究院） ； Shanghai AI Lab（上海AI实验室） 纠错

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

Comments Accepted by ICCV 2025; Code released at https://github.com/MCG-NJU/p-MoD

FrEVL: Leveraging Frozen Pretrained Embeddings for Efficient Vision-Language Understanding

Emmanuelle Bourigault, Pauline Bourigault

机构 * Department of Engineering Science, University of Oxford（牛津大学工程科学系） ； Department of Electrical Engineering, Imperial College London（伦敦帝国学院电子工程系） 纠错

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

Comments 8 pages, 4 figures

FlashCommunication V2: Bit Splitting and Spike Reserving for Any Bit Communication

Qingyuan Li, Bo Zhang, Hui Kang, Tianhao Xu, Yulei Qian, Yuchen Xie, Lin Ma

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

Comments 9 pages, 8 figures

Mixup Model Merge: Enhancing Model Merging Performance through Randomized Linear Interpolation

Yue Zhou, Yi Chang, Yuan Wu

专题命中 效率与部署 ：LLM(abstract)；分类 cs.CL

Comments 15 pages

Scaling Up Audio-Synchronized Visual Animation: An Efficient Training Paradigm

Lin Zhang, Zefan Cai, Yufan Zhou, Shentong Mo, Jinhong Lin, Cheng-En Wu, Yibing Wei, Yijing Zhang, Ruiyi Zhang, Wen Xiao, Tong Sun, Junjie Hu, Pedro Morgado

机构 * University of Wisconsin Madison（威斯康星大学麦迪逊分校） ； Carnegie Mellon University（卡内基梅隆大学） ； Luma AI ； Adobe Research（Adobe研究） ； Microsoft（微软） 纠错

专题命中 效率与部署 ：pretraining(abstract)

Foundation Neural-Networks Quantum States as a Unified Ansatz for Multiple Hamiltonians

Riccardo Rende, Luciano Loris Viteritti, Federico Becca, Antonello Scardicchio, Alessandro Laio, Giuseppe Carleo

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

Comments 10 pages, 6 figures, 1 table

Journal ref Nature Communications 16, 7213 (2025)