8 citations · 27 across the 14 of their papers we have counts for
3 papers · 1 filter
Olmo Hybrid: From Theory to Practice and Back
William Merrill, Yanhong Li, Tyler Romero +19
Recent work has demonstrated the potential of non-transformer language models, especially linear recurrent neural networks (RNNs) and hybrid models that mix recurrence and attentio…
Meta-Reinforcement Learning with Self-Reflection for Agentic Search
Teng Xiao, Yige Yuan, Hamish Ivison +6
This paper introduces MR-Search, an in-context meta reinforcement learning (RL) formulation for agentic search with self-reflection. Instead of optimizing a policy within a single…
RewardBench: Evaluating Reward Models for Language Modeling
Nathan Lambert, Valentina Pyatkin, Jacob Morrison +9
Reward models (RMs) are at the crux of successfully using RLHF to align pretrained models to human preferences, yet there has been relatively little study that focuses on evaluatio…