4 papers
Beyond Reference-Based Evaluation: Reward Models for Meta-Evaluation of Grammatical Error Correction
Ruotian Wu, Bill E. Johnson, Gene Saunders +3
Reference-based metrics for Grammatical Error Correction (GEC) such as M and ERRANT assume that the reference set enumerates all valid edits, and therefore often penalize corre…
Towards Cost-Effective Reward Guided Text Generation
Ahmad Rashid, Ruotian Wu, Rongqi Fan +3
Reward-guided text generation (RGTG) has emerged as a viable alternative to offline reinforcement learning from human feedback (RLHF). RGTG methods can align baseline language mode…
Uncertainty-Guided Likelihood Tree Search
Julia Grosse, Ruotian Wu, Ahmad Rashid +4
Tree search is a fundamental tool for planning, as many sequential decision-making problems can be framed as searching over tree-structured spaces. We propose an uncertainty-guided…
A Critical Look At Tokenwise Reward-Guided Text Generation
Ahmad Rashid, Ruotian Wu, Julia Grosse +2
Large language models (LLMs) can be improved by aligning with human preferences through fine-tuning -- the so-called reinforcement learning from human feedback (RLHF). However, the…