19 citations · 26 across the 7 of their papers we have counts for
3 papers · 1 filter
NATURAL PLAN: Benchmarking LLMs on Natural Language Planning
Huaixiu Steven Zheng, Swaroop Mishra, Hugh Zhang +8
We introduce NATURAL PLAN, a realistic planning benchmark in natural language containing 3 key tasks: Trip Planning, Meeting Planning, and Calendar Scheduling. We focus our evaluat…
Easy as ABCs: Unifying Boltzmann Q-Learning and Counterfactual Regret Minimization
Luca D'Amico-Wong, Hugh Zhang, Marc Lanctot +1
We propose ABCs (Adaptive Branching through Child stationarity), a best-of-both-worlds algorithm combining Boltzmann Q-learning (BQL), a classic reinforcement learning algorithm fo…
Q-Probe: A Lightweight Approach to Reward Maximization for Language Models
Kenneth Li, Samy Jelassi, Hugh Zhang +3
We present an approach called Q-probing to adapt a pre-trained language model to maximize a task-specific reward function. At a high level, Q-probing sits between heavier approache…