2 citations · 2 across the 13 of their papers we have counts for
4 papers · 1 filter
Online Learning with LLM Experts from Limited Feedback
Wang Wei, Soumyabrata Pal, Koyel Mukherjee +4
We study adaptive routing of prompts to large language model (LLM) experts to maximize response quality in an online setting with limited feedback. We formulate it as a bandit prob…
Orthrus: Memory-Efficient Parallel Token Generation via Dual-View Diffusion
Chien Van Nguyen, Chaitra Hegde, Van Cuong Pham +3
We introduce Orthrus, a simple and efficient dual-architecture framework that unifies the exact generation fidelity of autoregressive Large Language Models (LLMs) with the high-spe…
Skill-R1: Agent Skill Evolution via Reinforcement Learning
Yash Vishe, Rohan Surana, Xunyi Jiang +8
Agentic large language models often rely on skills, reusable natural language procedures that guide planning, action, and tool use. In practice, skills are typically improved throu…
Learning to Reason in LLMs by Expectation Maximization
Junghyun Lee, Branislav Kveton, Anup Rao +4
Large language models (LLMs) solve reasoning problems by first generating a rationale and then answering. We formalize reasoning as a latent variable model and derive a reward-base…