大模型对齐与安全

AI Safety, Alignment, and Ethics (AI SAE)

Dylan Waldner

专题命中 AI治理与伦理 ：alignment(title,abstract)；safety(title)；AI safety(title)；分类 cs.CY

Comments 46 pages, 9 figures (including appendix), 1 table

Robust or Suggestible? Exploring Non-Clinical Induction in LLM Drug-Safety Decisions

Siying Liu, Shisheng Zhang, Indu Bala

专题命中 AI治理与伦理 ：safety(title,abstract)；分类 cs.CL

Comments Preprint of a paper accepted as a poster at the NeurIPS 2025 Workshop on Generative AI for Health (GenAI4Health). The final camera-ready workshop version may differ. Licensed under CC BY 4.0

Benchmarking Adversarial Robustness to Bias Elicitation in Large Language Models: Scalable Automated Assessment with LLM-as-a-Judge

Riccardo Cantini, Alessio Orsino, Massimo Ruggiero, Domenico Talia

机构 * University of Calabria（卡利博利亚大学） 纠错

专题命中 AI治理与伦理 ：safety(abstract)；jailbreak(abstract)；分类 cs.CL、cs.AI

Journal ref Cantini, R., Orsino, A., Ruggiero, M., Talia, D. Benchmarking adversarial robustness to bias elicitation in large language models: scalable automated assessment with LLM-as-a-judge. Mach Learn 114, 249 (2025)

Position: Require Frontier AI Labs To Release Small "Analog" Models

Shriyash Upadhyay, Chaithanya Bandi, Narmeen Oozeer, Philip Quirke

机构 * Frontier AI Labs（前沿人工智能实验室） 纠错

专题命中 AI治理与伦理 ：safety(abstract)；AI safety(abstract)；分类 cs.AI

Generating Fair Consensus Statements with Social Choice on Token-Level MDPs

Carter Blair, Kate Larson

专题命中 AI治理与伦理 ：alignment(abstract)；分类 cs.CL、cs.AI

The Hidden Bias: A Study on Explicit and Implicit Political Stereotypes in Large Language Models

Konrad Löhr, Shuzhou Yuan, Michael Färber

机构 * Technische Universität Dresden（德累斯顿技术大学） ； Center for Scalable Data Analytics and Artificial Intelligence (ScaDS.AI)（可扩展数据与人工智能研究中心（ScaDS.AI）） 纠错

专题命中 AI治理与伦理 ：alignment(abstract)；分类 cs.AI、cs.LG

Big Data Approaches to Bovine Bioacoustics: A FAIR-Compliant Dataset and Scalable ML Framework for Precision Livestock Welfare

Mayuri Kate, Suresh Neethirajan

专题命中 AI治理与伦理 ：alignment(abstract)；分类 cs.AI

Comments 40 pages, 14 figures, 9 Tables

Flows and Diffusions on the Neural Manifold

Daniel Saragih, Deyu Cao, Tejas Balaji

机构 * Queen’s University and Vector Institute（女王大学和向量研究所） ； University of Tokyo（东京大学） ； University of Toronto（多伦多大学） 纠错

专题命中 AI治理与伦理 ：safety(abstract)；分类 cs.LG

Comments 43 pages, 11 figures, 14 tables

A Comprehensive Review of Recommender Systems: Transitioning from Theory to Practice

Shaina Raza, Mizanur Rahman, Safiullah Kamawal, Armin Toroghi, Ananya Raval, Farshad Navah, Amirmohammad Kazemeini

机构 * Vector Institute（向量研究所） ； Independent Researcher（独立研究者） 纠错

专题命中 AI治理与伦理 ：trustworthy(abstract)；分类 cs.AI

Comments we quarterly update of this literature