1 citations · 1 across the 2 of their papers we have counts for
5 papers
CogManip: Benchmarking Manipulative Behavior in Multi-Turn Interactions with Large Language Model
Zeyang Yue, Chenfei Yan, Feifei Zhao +5
Whether Large Language Models (LLMs) exhibit covert psychological manipulation in complex human-AI interactions has garnered increasing safety concerns. However, existing AI safety…
Evaluating LLMs for Demographic-Targeted Social Bias Detection: A Comprehensive Benchmark Study
Ayan Majumdar, Feihao Chen, Jinghui Li +1
Large-scale web-scraped text corpora used to train general-purpose AI models often contain harmful demographic-targeted social biases, creating a regulatory need for data auditing…
fastbmRAG: A Fast Graph-Based RAG Framework for Efficient Processing of Large-Scale Biomedical Literature
Guofeng Meng, Li Shen, Qiuyan Zhong +3
Large language models (LLMs) are rapidly transforming various domains, including biomedicine and healthcare, and demonstrate remarkable potential from scientific research to new dr…
Diverse Human Value Alignment for Large Language Models via Ethical Reasoning
Jiahao Wang, Songkai Xue, Jinghui Li +1
Ensuring that Large Language Models (LLMs) align with the diverse and evolving human values across different regions and cultures remains a critical challenge in AI ethics. Current…
Dynamic Perturbed Adaptive Method for Infinite Task-Conflicting Time Series
Jiang You, Xiaozhen Wang, Arben Cela
We formulate time series tasks as input-output mappings under varying objectives, where the same input may yield different outputs. This challenges a model's generalization and ada…