2 citations · 2 across the 7 of their papers we have counts for
7 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…
On Synthesizing Data for Context Attribution in Question Answering
Gorjan Radevski, Kiril Gashteovski, Shahbaz Syed +11
Question Answering (QA) accounts for a significant portion of LLM usage "in the wild". However, LLMs sometimes produce false or misleading responses, also known as "hallucinations"…
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…
Multi-hop Evidence Pursuit Meets the Web: Team Papelo at FEVER 2024
Christopher Malon
Separating disinformation from fact on the web has long challenged both the search and the reasoning powers of humans. We show that the reasoning power of large language models (LL…
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…
Self-Consistent Decoding for More Factual Open Responses
Christopher Malon, Xiaodan Zhu
Self-consistency has emerged as a powerful method for improving the accuracy of short answers generated by large language models. As previously defined, it only concerns the accura…