18 citations · 18 across the 5 of their papers we have counts for
3 papers · 1 filter
ARES: Adaptive Red-Teaming and End-to-End Repair of Policy-Reward System
Jiacheng Liang, Yao Ma, Tharindu Kumarage +5
Reinforcement Learning from Human Feedback (RLHF) is central to aligning Large Language Models (LLMs), yet it introduces a critical vulnerability: an imperfect Reward Model (RM) ca…
Emergent Strategic Reasoning Risks in AI: A Taxonomy-Driven Evaluation Framework
Tharindu Kumarage, Lisa Bauer, Yao Ma +7
As reasoning capacity and deployment scope grow in tandem, large language models (LLMs) gain the capacity to engage in behaviors that serve their own objectives, a class of risks w…
Beyond Benchmarks: The Economics of AI Inference
Boqin Zhuang, Jiacheng Qiao, Mingqian Liu +8
The inference cost of Large Language Models (LLMs) has become a critical factor in determining their commercial viability and widespread adoption. This paper introduces a quantitat…