大模型对齐与安全

Post-hoc Reward Calibration: A Case Study on Length Bias

Zeyu Huang, Zihan Qiu, Zili Wang, Edoardo M. Ponti, Ivan Titov

机构 * University of Edinburgh（爱丁堡大学） ； Alibaba Group（阿里巴巴集团） ； INF Technology（INF技术） ； University of Amsterdam（阿姆斯特丹大学） 纠错

专题命中 幻觉与事实性 ：alignment(abstract)；RLHF(abstract)；分类 cs.CL、cs.AI

Comments ICLR 2025

Turk-LettuceDetect: A Hallucination Detection Models for Turkish RAG Applications

Selva Taş, Mahmut El Huseyni, Özay Ezerceli, Reyhan Bayraktar, Fatma Betül Terzioğlu

机构 * Hidden for Review（保密） 纠错

专题命中 幻觉与事实性 ：trustworthy(abstract)；分类 cs.CL、cs.AI

Decoding Uncertainty: The Impact of Decoding Strategies for Uncertainty Estimation in Large Language Models

Wataru Hashimoto, Hidetaka Kamigaito, Taro Watanabe

机构 * Nara Institute of Science and Technology（奈良科学技术大学） 纠错

专题命中 幻觉与事实性 ：alignment(abstract)；分类 cs.CL、cs.LG

Comments Accepted at EMNLP 2025 Findings

Sycophancy Mitigation Through Reinforcement Learning with Uncertainty-Aware Adaptive Reasoning Trajectories

Mohammad Beigi, Ying Shen, Parshin Shojaee, Qifan Wang, Zichao Wang, Chandan Reddy, Ming Jin, Lifu Huang

机构 * University of California, Davis（加州大学戴维斯分校） ； University of Illinois Urbana-Champaign（伊利诺伊大学厄巴纳-香槟分校） ； Virginia Tech（弗吉尼亚理工大学） ； Meta AI ； Adobe Research（Adobe研究） 纠错

专题命中 幻觉与事实性 ：alignment(abstract)；分类 cs.AI

Enhancing Financial RAG with Agentic AI and Multi-HyDE: A Novel Approach to Knowledge Retrieval and Hallucination Reduction

Akshay Govind Srinivasan, Ryan Jacob George, Jayden Koshy Joe, Hrushikesh Kant, Harshith M R, Sachin Sundar, Sudharshan Suresh, Rahul Vimalkanth, Vijayavallabh

机构 * Indian Institute of Technology Madras（印度理工学院马德拉斯学院） 纠错

专题命中 幻觉与事实性 ：trustworthy(abstract)；分类 cs.AI

Comments 14 Pages, 8 Tables, 2 Figures. Accepted and to be published in the proceedings of FinNLP, Empirical Methods in Natural Language Processing 2025

Factuality Beyond Coherence: Evaluating LLM Watermarking Methods for Medical Texts

Rochana Prih Hastuti, Rian Adam Rajagede, Mansour Al Ghanim, Mengxin Zheng, Qian Lou

机构 * University of Central Florida（中央佛罗里达大学） 纠错

专题命中 幻觉与事实性 ：safety(abstract)；分类 cs.CL

Comments Accepted at EMNLP 2025 Findings. Camera Ready

Co-STAR: Collaborative Curriculum Self-Training with Adaptive Regularization for Source-Free Video Domain Adaptation

Amirhossein Dadashzadeh, Parsa Esmati, Majid Mirmehdi

机构 * University of Bristol, UK（布里斯托大学） 纠错

专题命中 幻觉与事实性 ：alignment(abstract)