8 papers
Strategic Bargaining in Multi-Buyer Markets: Reinforcement Learning from Verifiable Rewards for LLM Negotiations
Shuze Daniel Liu, Claire Chen, Jiabao Sean Xiao +2
Negotiation is a fundamental strategic interaction in management science, characterized by agents attempting to reach agreements while protecting private information, such as reser…
An Embarrassingly Simple Detector for Model Extraction Attacks in Large Language Model API Traffic
Shuze Liu, Qianwen Guo, Yushun Dong
Large language models (LLMs) are increasingly deployed through hosted APIs, making model extraction a practical threat to model ownership and service security. However, individual…
Convergence of Two-Timescale Markovian Stochastic Approximations with Applications in Reinforcement Learning
Vagul Mahadevan, Claire Chen, Shuze Daniel Liu +1
This work studies the convergence of two-timescale stochastic approximations (SA), a class of iterative algorithms that update two sets of parameters in fast and slow timescales re…
Beyond Linear Attention: Softmax Transformers Implement In-Context Reinforcement Learning
Zixuan Xie, Xinyu Liu, Claire Chen +3
In-context reinforcement learning (ICRL) studies agents that, after pretraining, adapt to new tasks by conditioning on additional context without parameter updates. Existing theore…
Offline Two-Player Zero-Sum Markov Games with KL Regularization
Claire Chen, Yuheng Zhang, Xinyu Liu +3
We study the problem of learning Nash equilibria in offline two-player zero-sum Markov games. While existing approaches often rely on explicit pessimism to address distribution shi…
Predicting Plasticity in Deep Continual Learning: A Theoretical Perspective
Jiuqi Wang, Jayanth Srinivasa, Claire Chen +3
Deep continual learning requires models to adapt to new tasks without retraining from scratch. However, neural networks can lose their ability to adapt to new tasks after training…