2 citations · 2 across the 1 of their papers we have counts for
5 papers
EditGRPO: Reinforcement Learning with Post-Rollout Edits for Clinically Accurate Chest X-Ray Report Generation
Kai Zhang, Christopher Malon, Lichao Sun +1
Radiology report generation requires advanced medical image analysis, effective temporal reasoning, and accurate text generation. Although recent innovations, particularly multimod…
DiscussLLM: Teaching Large Language Models When to Speak
Deep Anil Patel, Iain Melvin, Christopher Malon +1
Large Language Models (LLMs) have demonstrated remarkable capabilities in understanding and generating human-like text, yet they largely operate as reactive agents, responding only…
Reducing Hallucinations of Medical Multimodal Large Language Models with Visual Retrieval-Augmented Generation
Yun-Wei Chu, Kai Zhang, Christopher Malon +1
Multimodal Large Language Models (MLLMs) have shown impressive performance in vision and text tasks. However, hallucination remains a major challenge, especially in fields like hea…
Exploring the Role of Reasoning Structures for Constructing Proofs in Multi-Step Natural Language Reasoning with Large Language Models
Zi'ou Zheng, Christopher Malon, Martin Renqiang Min +1
When performing complex multi-step reasoning tasks, the ability of Large Language Models (LLMs) to derive structured intermediate proof steps is important for ensuring that the mod…
DICE: Discrete Inversion Enabling Controllable Editing for Multinomial Diffusion and Masked Generative Models
Xiaoxiao He, Quan Dao, Ligong Han +14
Discrete diffusion models have achieved success in tasks like image generation and masked language modeling but face limitations in controlled content editing. We introduce DICE (D…