104 citations · 140 across the 15 of their papers we have counts for
15 papers
Evaluating Criterion-Conditioned Behaviour of Large Language Models in Content Moderation
Danting Zhang, Bei Peng, Robert Loftin
Large language models (LLMs) demonstrate strong performance on standard content moderation benchmarks. However, these benchmarks often aggregate multiple moderation criteria into a…
ConventionPlay: Capability-Limited Training for Robust Ad-Hoc Collaboration
Abhishek Sriraman, Eleni Vasilaki, Robert Loftin
Ad-hoc collaboration often relies on identifying and adhering to shared conventions. However, when partners can follow multiple conventions, agents must do more than simply adapt;…
Counterfactual Conditional Likelihood Rewards for Multiagent Exploration
Ayhan Alp Aydeniz, Robert Loftin, Kagan Tumer
Efficient exploration is critical for multiagent systems to discover coordinated strategies, particularly in open-ended domains such as search and rescue or planetary surveying. Ho…
How Does the Lagrangian Guide Safe Reinforcement Learning through Diffusion Models?
Xiaoyuan Cheng, Wenxuan Yuan, Boyang Li +7
Diffusion policy sampling enables reinforcement learning (RL) to represent multimodal action distributions beyond suboptimal unimodal Gaussian policies. However, existing diffusion…
Social Cooperation in Conversational AI Agents
Mustafa Mert Çelikok, Saptarashmi Bandyopadhyay, Robert Loftin
The development of AI agents based on large, open-domain language models (LLMs) has paved the way for the development of general-purpose AI assistants that can support human in tas…
Safe Multiagent Coordination via Entropic Exploration
Ayhan Alp Aydeniz, Enrico Marchesini, Robert Loftin +2
Many real-world multiagent learning problems involve safety concerns. In these setups, typical safe reinforcement learning algorithms constrain agents' behavior, limiting explorati…