语言大模型 / LLM

Pre-trained Language Models for the Legal Domain: A Case Study on Indian Law

Shounak Paul, Arpan Mandal, Pawan Goyal, Saptarshi Ghosh

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

Comments To be published in the 19th International Conference on Artificial Intelligence and Law - ICAIL 2023

Advancing Medical Imaging with Language Models: A Journey from N-grams to ChatGPT

Mingzhe Hu, Shaoyan Pan, Yuheng Li, Xiaofeng Yang

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

Learning Domain Invariant Prompt for Vision-Language Models

Cairong Zhao, Yubin Wang, Xinyang Jiang, Yifei Shen, Kaitao Song, Dongsheng Li, Duoqian Miao

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

Comments 12 pages, 6 figures, 5 tables

Medical Image Understanding with Pretrained Vision Language Models: A Comprehensive Study

Ziyuan Qin, Huahui Yi, Qicheng Lao, Kang Li

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

Comments Accepted to ICLR2023

GatorTron: A Large Clinical Language Model to Unlock Patient Information from Unstructured Electronic Health Records

Xi Yang, Aokun Chen, Nima PourNejatian, Hoo Chang Shin, Kaleb E Smith, Christopher Parisien, Colin Compas, Cheryl Martin, Mona G Flores, Ying Zhang, Tanja Magoc, Christopher A Harle, Gloria Lipori, Duane A Mitchell, William R Hogan, Elizabeth A Shenkman, Jiang Bian, Yonghui Wu

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

Comments 24 pages, 2 figures, 3 tables

WHEN FLUE MEETS FLANG: Benchmarks and Large Pre-trained Language Model for Financial Domain

Raj Sanjay Shah, Kunal Chawla, Dheeraj Eidnani, Agam Shah, Wendi Du, Sudheer Chava, Natraj Raman, Charese Smiley, Jiaao Chen, Diyi Yang

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

Exploring the Limits of Domain-Adaptive Training for Detoxifying Large-Scale Language Models

Boxin Wang, Wei Ping, Chaowei Xiao, Peng Xu, Mostofa Patwary, Mohammad Shoeybi, Bo Li, Anima Anandkumar, Bryan Catanzaro

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

Comments NeurIPS 2022

Annotated Dataset Creation through General Purpose Language Models for non-English Medical NLP

Johann Frei, Frank Kramer

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

LG4AV: Combining Language Models and Graph Neural Networks for Author Verification

Maximilian Stubbemann, Gerd Stumme

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

Comments 9 pages, 1 figure

Pretrained Domain-Specific Language Model for General Information Retrieval Tasks in the AEC Domain

Zhe Zheng, Xin-Zheng Lu, Ke-Yin Chen, Yu-Cheng Zhou, Jia-Rui Lin

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

Journal ref Computers in Industry, 2022

E-BERT: A Phrase and Product Knowledge Enhanced Language Model for E-commerce

Denghui Zhang, Zixuan Yuan, Yanchi Liu, Fuzhen Zhuang, Haifeng Chen, Hui Xiong

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

Towards Understanding and Mitigating Social Biases in Language Models

Paul Pu Liang, Chiyu Wu, Louis-Philippe Morency, Ruslan Salakhutdinov

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

Comments ICML 2021, code available at https://github.com/pliang279/LM_bias

Internal Language Model Training for Domain-Adaptive End-to-End Speech Recognition

Zhong Meng, Naoyuki Kanda, Yashesh Gaur, Sarangarajan Parthasarathy, Eric Sun, Liang Lu, Xie Chen, Jinyu Li, Yifan Gong

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

Comments 5 pages, ICASSP 2021

Journal ref 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Toronto, Canada

Customizing Contextualized Language Models forLegal Document Reviews

Shohreh Shaghaghian, Luna, Feng, Borna Jafarpour, Nicolai Pogrebnyakov

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

Neural Mask Generator: Learning to Generate Adaptive Word Maskings for Language Model Adaptation

Minki Kang, Moonsu Han, Sung Ju Hwang

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

Comments 19 pages, 9 figures, EMNLP 2020

Enabling Language Models to Fill in the Blanks

Chris Donahue, Mina Lee, Percy Liang

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

Comments Published as a conference paper at ACL 2020

EduBERT: Pretrained Deep Language Models for Learning Analytics

Benjamin Clavié, Kobi Gal

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

Comments Accepted for poster presentation at the 10th International Learning Analytics and Knowledge (LAK20) Conference

HUKUKBERT: Domain-Specific Language Model for Turkish Law

HUKUKBERT：土耳其法律领域的专用语言模型

Mehmet Utku Öztürk, Tansu Türkoğlu, Buse Buz-Yalug

机构 * Kalitte Inc.（Kalitte公司） ； Aibrite Inc.（Aibrite公司） ； University of Eastern Finland（东芬兰大学） 纠错

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

AI总结 本文提出HUKUKBERT，首个针对土耳其法律的全面语言模型，通过混合领域自适应预训练方法，在18GB法律语料上训练，实现84.40%的Top-1准确率，并在官方土耳其法院判决结构分割任务中达到92.8%的文档通过率。

Comments 15 pages

Journal ref Öztürk, M. U., Türkoğlu, T., & Buz-Yalug, B. (2026). HukukBERT: Domain-Specific Language Model for Turkish Law. Journal of Computational Law and Legal Technology, 1-15

From 100,000+ images to winning the first brain MRI foundation model challenges: Sharing lessons and models

从10万张图像到赢得首个脑部MRI基础模型挑战：分享经验与模型

Pedro M. Gordaliza, Jaume Banus, Benoît Gérin, Maxence Wynen, Nataliia Molchanova, Jonas Richiardi, Meritxell Bach Cuadra

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

AI总结 本文提出了一种结合解剖学先验和神经影像知识的U-Net CNN架构，在3D脑部MRI挑战中取得领先，模型训练速度快且体积小。

Comments Work presented at the SSL3D Challenge (1st place, ResEnc-L track) and FOMO Challenge (1st place, Methods track) on Brain MRI Foundation Models at MICCAI 2025

Cross-device Zero-shot Label Transfer via Alignment of Time Series Foundation Model Embeddings

Neal G. Ravindra, Arijit Sehanobish

机构 * Independent Researcher（独立研究者） 纠错

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

Comments 5 pages, 3 figures, 1 table. tl;dr: Adversarial alignment of Time-Series Foundation Model (TSFM) embeddings enables transfer of high-quality clinical labels from medical-grade to consumer-grade wearables, enabling zero-shot prediction of gestational age without requiring paired data

Consistency in Language Models: Current Landscape, Challenges, and Future Directions

Jekaterina Novikova, Carol Anderson, Borhane Blili-Hamelin, Domenic Rosati, Subhabrata Majumdar

机构 * Dalhousie University（达尔豪斯大学） ； Vanguard, Enteprise AI Research（先锋企业人工智能研究所） 纠错

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

Comments Accepted in ICML 2025 Workshop on Reliable and Responsible Foundation Models

Navigating Data Scarcity using Foundation Models: A Benchmark of Few-Shot and Zero-Shot Learning Approaches in Medical Imaging

Stefano Woerner, Christian F. Baumgartner

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

Comments Accepted as an oral presentation in MICCAI 2024 2nd International Workshop on Foundation Models for General Medical AI

Bringing order into the realm of Transformer-based language models for artificial intelligence and law

Candida M. Greco, Andrea Tagarelli

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

Comments Please refer to the published version: Greco, C.M., Tagarelli, A. (2023) Bringing order into the realm of Transformer-based language models for artificial intelligence and law. Artif Intell Law, Springer Nature. November 2023. https://doi.org/10.1007/s10506-023-09374-7

Journal ref Artif Intell Law, Springer Nature. November 2023

FDAPT: Federated Domain-adaptive Pre-training for Language Models

Lekang Jiang, Filip Svoboda, Nicholas D. Lane

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

Comments Accepted at International Workshop on Federated Learning in the Age of Foundation Models in Conjunction with NeurIPS 2023

On the Opportunities and Risks of Foundation Models

Rishi Bommasani, Drew A. Hudson, Ehsan Adeli, Russ Altman, Simran Arora, Sydney von Arx, Michael S. Bernstein, Jeannette Bohg, Antoine Bosselut, Emma Brunskill, Erik Brynjolfsson, Shyamal Buch, Dallas Card, Rodrigo Castellon, Niladri Chatterji, Annie Chen, Kathleen Creel, Jared Quincy Davis, Dora Demszky, Chris Donahue, Moussa Doumbouya, Esin Durmus, Stefano Ermon, John Etchemendy, Kawin Ethayarajh, Li Fei-Fei, Chelsea Finn, Trevor Gale, Lauren Gillespie, Karan Goel, Noah Goodman, Shelby Grossman, Neel Guha, Tatsunori Hashimoto, Peter Henderson, John Hewitt, Daniel E. Ho, Jenny Hong, Kyle Hsu, Jing Huang, Thomas Icard, Saahil Jain, Dan Jurafsky, Pratyusha Kalluri, Siddharth Karamcheti, Geoff Keeling, Fereshte Khani, Omar Khattab, Pang Wei Koh, Mark Krass, Ranjay Krishna, Rohith Kuditipudi, Ananya Kumar, Faisal Ladhak, Mina Lee, Tony Lee, Jure Leskovec, Isabelle Levent, Xiang Lisa Li, Xuechen Li, Tengyu Ma, Ali Malik, Christopher D. Manning, Suvir Mirchandani, Eric Mitchell, Zanele Munyikwa, Suraj Nair, Avanika Narayan, Deepak Narayanan, Ben Newman, Allen Nie, Juan Carlos Niebles, Hamed Nilforoshan, Julian Nyarko, Giray Ogut, Laurel Orr, Isabel Papadimitriou, Joon Sung Park, Chris Piech, Eva Portelance, Christopher Potts, Aditi Raghunathan, Rob Reich, Hongyu Ren, Frieda Rong, Yusuf Roohani, Camilo Ruiz, Jack Ryan, Christopher Ré, Dorsa Sadigh, Shiori Sagawa, Keshav Santhanam, Andy Shih, Krishnan Srinivasan, Alex Tamkin, Rohan Taori, Armin W. Thomas, Florian Tramèr, Rose E. Wang, William Wang, Bohan Wu, Jiajun Wu, Yuhuai Wu, Sang Michael Xie, Michihiro Yasunaga, Jiaxuan You, Matei Zaharia, Michael Zhang, Tianyi Zhang, Xikun Zhang, Yuhui Zhang, Lucia Zheng, Kaitlyn Zhou, Percy Liang

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

Comments Authored by the Center for Research on Foundation Models (CRFM) at the Stanford Institute for Human-Centered Artificial Intelligence (HAI). Report page with citation guidelines: https://crfm.stanford.edu/report.html

Structured but Fragile: On the Limits of LLMs in Cybersecurity Decision-Making

结构化但脆弱：大型语言模型（LLMs）在网络安全决策中的局限性

Pasquale Malacaria, Yunxiao Zhang

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

AI总结 该研究探讨LLMs在网络安全决策中的表现，发现其在明确攻击图结构时能产生接近优化基线的策略，但随复杂度增加而脆弱，对提示敏感，且无法稳健应用结构化推理，为AI辅助安全决策系统设计评估提供参考。

Comments 31 pages, 10 figures

LLMs as Acquisition Policies for Finite-Pool Materials Optimization: A Controlled Study

大语言模型作为有限池材料优化的获取策略：一项对照研究

Dino-Rober Demir, Florian Le Bronnec, Rio Yokota

机构 * RIKEN（理化学研究所） 纠错

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

AI总结 该研究探究开放权重大语言模型能否作为有限池材料优化的独立获取策略，经对照实验发现其无需任务特定训练即可提供有用获取信号，虽可靠性受多因素影响但显示出应用潜力。

PACE: Policy-Attested Contract Execution for Safe AI Agents in Decentralized Finance

PACE：用于去中心化金融中安全AI智能体的策略验证合约执行

Rabimba Karanjai, Yang Lu, Richard Williamson, Hemanth Hm, Prakhar Mehrotra, Lei Xu, Weidong, Shi

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

AI总结 该研究提出PACE框架，通过引入类型化交易意图等机制，实现去中心化金融中AI智能体的安全交易授权，在确定性沙箱中实现0.00不安全执行率和0.00误报率，提升了DeFi场景下AI智能体的安全性。

Valhalla: A Layered Knowledge-State and Service-Governance Framework for Long-Term Scientific Knowledge Work

Valhalla：面向长期科学知识工作的分层知识状态与服务治理框架

Yuyang Zheng, Nan Li, Wenxia Deng, Lige Yan, Xiang Li, Si Chen

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

AI总结 Valhalla是面向长期科学知识工作的分层框架，采用FREG模型与服务治理架构，经抗体设计任务验证，可将个性化知识结构转化为可共享重组的协作知识状态。

Competing at Every Price Point with Agentic Evolution over a Menu of LLMs

基于LLMs菜单的智能体进化，在每个价格点展开竞争

Andrew Borthwick

专题命中 领域大模型 ：LLM(summary_cn,abstract)；分类 cs.AI

AI总结 本研究提出进化元智能体RoboPhD，通过对含9个LLM端点的菜单进行智能体进化，在DS-1000和PaperFindingBench两个任务上，除一个位置外占据所有帕累托前沿槽位，实现各价格点的竞争优势。