8 citations · 10 across the 10 of their papers we have counts for
5 papers · 1 filter
Evaluating the Consistency of LLM Evaluators
Noah Lee, Jiwoo Hong, James Thorne
Large language models (LLMs) have shown potential as general evaluators along with the evident benefits of speed and cost. While their correlation against human annotators has been…
Cross-lingual Transfer of Reward Models in Multilingual Alignment
Jiwoo Hong, Noah Lee, Rodrigo Martínez-Castaño +2
Reinforcement learning with human feedback (RLHF) is shown to largely benefit from precise reward models (RMs). However, recent studies in reward modeling schemes are skewed toward…
Margin-aware Preference Optimization for Aligning Diffusion Models without Reference
Jiwoo Hong, Sayak Paul, Noah Lee +3
Modern preference alignment methods, such as DPO, rely on divergence regularization to a reference model for training stability-but this creates a fundamental problem we call "refe…
The BiGGen Bench: A Principled Benchmark for Fine-grained Evaluation of Language Models with Language Models
Seungone Kim, Juyoung Suk, Ji Yong Cho +29
As language models (LMs) become capable of handling a wide range of tasks, their evaluation is becoming as challenging as their development. Most generation benchmarks currently as…
ORPO: Monolithic Preference Optimization without Reference Model
Jiwoo Hong, Noah Lee, James Thorne
While recent preference alignment algorithms for language models have demonstrated promising results, supervised fine-tuning (SFT) remains imperative for achieving successful conve…