语言大模型 / LLM

Introducing 'inrep': an R package that facilitates fully reproducible research workfows for survey-based assessments

Clievins Selva

专题命中 评测与基准 ：large language model(abstract)；language model(abstract)

Comments https://hilpub.uni-hildesheim.de/entities/publication/ee7642b0-03ee-4e59-8877-6bf5573124d5

Bench-2-CoP: Can We Trust Benchmarking for EU AI Compliance?

Matteo Prandi, Vincenzo Suriani, Federico Pierucci, Marcello Galisai, Daniele Nardi, Piercosma Bisconti

机构 * Sapienza University of Rome（罗马萨皮恩扎大学） ； DEXAI-Artificial Ethics（DEXAI人工智能伦理） ； Sant’Anna School of Advanced Studies（圣安娜高级研究学院） 纠错

专题命中 评测与基准 ：LLM(abstract)；分类 cs.CL、cs.AI

CAMEF: Causal-Augmented Multi-Modality Event-Driven Financial Forecasting by Integrating Time Series Patterns and Salient Macroeconomic Announcements

Yang Zhang, Wenbo Yang, Jun Wang, Qiang Ma, Jie Xiong

机构 * Southwestern University of Finance and Economics（西南财经大学） ； Kyoto Institute of Technology（京都技术大学） 纠错

专题命中 评测与基准 ：LLM(abstract)；分类 cs.AI、cs.LG

Comments Accepted in SIGKDD 2025

HySemRAG: A Hybrid Semantic Retrieval-Augmented Generation Framework for Automated Literature Synthesis and Methodological Gap Analysis

Alejandro Godinez

专题命中 评测与基准 ：LLM(abstract)；分类 cs.AI、cs.LG

Comments 47 pages, 10 figures. Code: https://github.com/agodinezmm2007/docling_mod. Demo: https://youtu.be/ZCy5ESJ1gVE?si=K8CttwgTj7yGrWjn. ETL+multi-agent RAG framework for literature synthesis, 35.1% improvement over PDF chunking. Real application: reduced 17,400 papers to 24 relevant ones (99.86%) in 10 minutes for wastewater epidemiology review

Enhancing Retrieval-Augmented Generation for Electric Power Industry Customer Support

Hei Yu Chan, Kuok Tou Ho, Chenglong Ma, Yujing Si, Hok Lai Lin, Sa Lei Lam

专题命中 评测与基准 ：language model(abstract)；分类 cs.CL、cs.AI

Comments 6 pages

EvidenceBench: A Benchmark for Extracting Evidence from Biomedical Papers

Jianyou Wang, Weili Cao, Kaicheng Wang, Xiaoyue Wang, Ashish Dalvi, Gino Prasad, Qishan Liang, Hsuan-lin Her, Ming Wang, Qin Yang, Gene W. Yeo, David E. Neal, Maxim Khan, Christopher D. Rosin, Ramamohan Paturi, Leon Bergen

机构 * Laboratory for Emerging Intelligence, University of California, San Diego（新兴智能实验室，加州大学圣地亚哥分校） ； Elsevier（埃塞洋） ； Department of Cellular and Molecular Medicine, University of California, San Diego（细胞与分子医学系，加州大学圣地亚哥分校） ； Sichuan Cancer Hospital & Institute（四川癌症医院与研究所） ； The Third People’s Hospital of Chengdu（成都第三人民医院） 纠错

专题命中 评测与基准 ：language model(abstract,comments)；分类 cs.CL

Comments Published at Conference on Language Modeling (COLM) 2025

AGI for the Earth, the path, possibilities and how to evaluate intelligence of models that work with Earth Observation Data?

Mojtaba Valipour, Kelly Zheng, James Lowman, Spencer Szabados, Mike Gartner, Bobby Braswell

专题命中 评测与基准 ：foundation model(abstract)；分类 cs.LG

Comments Accepted in IGARSS 2025!

Zero-Shot Retrieval for Scalable Visual Search in a Two-Sided Marketplace

Andre Rusli, Shoma Ishimoto, Sho Akiyama, Aman Kumar Singh

机构 * Mercari, Inc.（Mercari公司） 纠错

专题命中 评测与基准 ：language model(abstract)；分类 cs.AI

Comments 6 pages, KDD 2025 Workshop on Two-sided Marketplace Optimization: Search, Pricing, Matching & Growth (TSMO)

TryOffDiff: Virtual-Try-Off via High-Fidelity Garment Reconstruction using Diffusion Models

Riza Velioglu, Petra Bevandic, Robin Chan, Barbara Hammer

机构 * Machine Learning Group, CITEC Bielefeld University Germany（比勒菲尔德大学机器学习小组、CITEC） ； Institute of Mathematics Technical University Berlin Germany（柏林技术大学数学研究所） 纠错

专题命中 评测与基准 ：prompting(abstract)；分类 cs.AI

Comments Accepted at BMVC'25

Real-Time 3D Vision-Language Embedding Mapping

Christian Rauch, Björn Ellensohn, Linus Nwankwo, Vedant Dave, Elmar Rueckert

机构 * Technical University of Leoben（莱博恩技术大学） 纠错

专题命中 评测与基准 ：language model(abstract)

VISTAR:A User-Centric and Role-Driven Benchmark for Text-to-Image Evaluation

Kaiyuan Jiang, Ruoxi Sun, Ying Cao, Yuqi Xu, Xinran Zhang, Junyan Guo, ChengSheng Deng

机构 * Peking University（北京大学） ； LinkSure ； University of Glasgow（格拉斯哥大学） ； Boston University（波士顿大学） 纠错

专题命中 评测与基准 ：language model(abstract)

Comments 17 pages,8 figures

Embodied Intelligence for 3D Understanding: A Survey on 3D Scene Question Answering

Zechuan Li, Hongshan Yu, Yihao Ding, Yan Li, Yong He, Naveed Akhtar

机构 * organization= College of Electrical ； Information Engineering,Hunan University , city= Changsha , postcode= 410082 , state= Hunan , country= China ； organization= School of Computing \& Information Systems ,The University of Melbourne , city= Melbourne , postcode= VIC 3053 , state= VIC , country= Australia ； organization= School of Computer Science,The University of Sydney , city= Sydney , postcode= NSW 2006 , state= NSW , country= Australia ； organization= School of Artificial Intelligence ,Anhui University , city= Hefei , postcode= 230601 , state= Anhui , country= China 纠错

专题命中 评测与基准 ：instruction tuning(abstract)

Comments This is a submitted version of a paper accepted by Information Fusion

SAR Strikes Back: A New Hope for RSVQA

Lucrezia Tosato, Flora Weissgerber, Laurent Wendling, Sylvain Lobry

机构 * LIPADE, Université Paris Cité（巴黎Cité大学LIPADE研究所） ； GENCI-IDRIS ； French Aerospace Lab, ONERA（法国航空航天实验室ONERA） 纠错

专题命中 评测与基准 ：language model(abstract)

Comments Accepted at IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 13 pages, 6 figures

Journal ref 10.1109/JSTARS.2025.3596678

Towards Pareto Optimal Throughput in Small Language Model Serving

Pol G. Recasens, Yue Zhu, Chen Wang, Eun Kyung Lee, Olivier Tardieu, Alaa Youssef, Jordi Torres, Josep Ll. Berral

机构 * Barcelona Supercomputing Center（巴塞罗那超级计算中心） ； IBM Research（IBM研究院） 纠错

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

Comments Revised version of the paper published at EuroMLSys'24, fix figure 6 and 7

Less is More: Selective Reflection for Compatible and Efficient Knowledge Distillation in Large Language Models

Lingyuan Liu, Mengxiang Zhang

机构 * City University of Hong Kong（香港城市大学） ； 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.CL、cs.AI

QDyLoRA: Quantized Dynamic Low-Rank Adaptation for Efficient Large Language Model Tuning

Hossein Rajabzadeh, Mojtaba Valipour, Tianshu Zhu, Marzieh Tahaei, Hyock Ju Kwon, Ali Ghodsi, Boxing Chen, Mehdi Rezagholizadeh

机构 * University of Waterloo（滑铁卢大学） ； Huawei Noah’s Ark Lab（华为诺亚实验室） 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 Best Paper Award AAAI EIW Workshop

Journal ref https://aclanthology.org/2024.emnlp-industry.53.pdf

Integrating large language models and active inference to understand eye movements in reading and dyslexia

Francesco Donnarumma, Mirco Frosolone, Giovanni Pezzulo

机构 * Institute of Cognitive Sciences and Technologies, National Research Council（认知科学与技术研究所，国家研究院） 纠错

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

Comments Main Document - 30 pages, 1 Table, 10 Figures + Supplementary 16 pages, 17 Tables

Contextual Morphogenesis in Large Language Models: A Novel Approach to Self-Organizing Token Representations

Alistair Dombrowski, Beatrix Engelhardt, Dimitri Fairbrother, Henry Evidail

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

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

Structural Embedding Projection for Contextual Large Language Model Inference

Vincent Enoasmo, Cedric Featherstonehaugh, Xavier Konstantinopoulos, Zacharias Huntington

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

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

Adacc: An Adaptive Framework Unifying Compression and Activation Recomputation for LLM Training

Ping Chen, Zhuohong Deng, Ping Li, Shuibing He, Hongzi Zhu, Yi Zheng, Zhefeng Wang, Baoxing Huai, Minyi Guo

机构 * The State Key Laboratory of Blockchain and Data Security（区块链与数据安全国家重点实验室） ； Hangzhou High-Tech Zone (Binjiang) Institute of Blockchain and Data Security（杭州高新技术区（滨江）区块链与数据安全研究院） ； Shanghai Jiao Tong University（上海交通大学） ； Huawei Cloud（华为云） ； Zhejiang Lab（浙江实验室） 纠错

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

Comments 8 pages

NanoCodec: Towards High-Quality Ultra Fast Speech LLM Inference

Edresson Casanova, Paarth Neekhara, Ryan Langman, Shehzeen Hussain, Subhankar Ghosh, Xuesong Yang, Ante Jukić, Jason Li, Boris Ginsburg

机构 * NVIDIA Corporation（英伟达公司） 纠错

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

Comments Accepted to Interspeech 2025

Contextual Reinforcement in Multimodal Token Compression for Large Language Models

Naderdel Piero, Zacharias Cromwell, Nathaniel Wainwright, Matthias Nethercott

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

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

Can Test-Time Scaling Improve World Foundation Model?

Wenyan Cong, Hanqing Zhu, Peihao Wang, Bangya Liu, Dejia Xu, Kevin Wang, David Z. Pan, Yan Wang, Zhiwen Fan, Zhangyang Wang

机构 * University of Texas at Austin（德克萨斯大学奥斯汀分校） ； NVIDIA（英伟达） ； University of Wisconsin-Madison（威斯康星大学麦迪逊分校） ； Texas A&M University（德克萨斯阿姆斯特朗大学） 纠错

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

Comments Accepted by COLM2025

AALC: Large Language Model Efficient Reasoning via Adaptive Accuracy-Length Control

Ruosen Li, Ziming Luo, Quan Zhang, Ruochen Li, Ben Zhou, Ali Payani, Xinya Du

机构 * University of Texas at Dallas（德克萨斯大学达拉斯分校） ； Arizona State University（亚利桑那州立大学） ； Cisco Research（思科研究） 纠错

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

Structured Convergence in Large Language Model Representations via Hierarchical Latent Space Folding

Fenella Harcourt, Naderdel Piero, Gilbert Sutherland, Daphne Holloway, Harriet Bracknell, Julian Ormsby

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

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

Structural Reformation of Large Language Model Neuron Encapsulation for Divergent Information Aggregation

Denis Bakushev, Gideon Boultinghouse, Harriet Oppenheimer, Sebastian Gillingwater, Valentina Ashington, Wilfred Stanborough

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

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

Risk Analysis Techniques for Governed LLM-based Multi-Agent Systems

Alistair Reid, Simon O'Callaghan, Liam Carroll, Tiberio Caetano

机构 * Gradient Institute Ltd.（梯度研究所有限公司） 纠错

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

DONOD: Efficient and Generalizable Instruction Fine-Tuning for LLMs via Model-Intrinsic Dataset Pruning

Jucheng Hu, Surong Yang, Lijun Wu, Dongzhan Zhou

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

ETTA: Efficient Test-Time Adaptation for Vision-Language Models through Dynamic Embedding Updates

Hamidreza Dastmalchi, Aijun An, Ali cheraghian

机构 * York University（约克大学） ； The Australian National University（澳大利亚国立大学） ； Data61-CSIRO 纠错

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

Comments BMVC2025

Principle-Guided Verilog Optimization: IP-Safe Knowledge Transfer via Local-Cloud Collaboration

Jing Wang, Zheng Li, Lei Li, Fan He, Liyu Lin, Yao Lai, Yan Li, Xiaoyang Zeng, Yufeng Guo

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

Comments Our code and dataset are available at https://github.com/friyawang/VeriOptim