7 papers
Interactor: Agentic RL oriented Iterative Creation for Ad Description Generation in Sponsored Search
Penghui Wei, Jiayu Wu, Chao Ye +3
This paper focuses on automatically generating informative ad descriptions in sponsored search. Unlike ad titles which are usually optimized to attract user click feedbacks, ad des…
ANDRE: An Attention-based Neuro-symbolic Differentiable Rule Extractor for Inductive Logic Programming
Iman Sharifi, Peng Wei, Saber Fallah
Inductive Logic Programming (ILP) aims to learn interpretable first-order rules from data, but existing symbolic and neuro-symbolic approaches struggle to scale to noisy and probab…
Training a Large Language Model for Medical Coding Using Privacy-Preserving Synthetic Clinical Data
John Cook, Michael Wyatt, Peng Wei +11
Improving the accuracy and reliability of medical coding reduces clinician burnout and supports revenue cycle processes, freeing providers to focus more on patient care. However, a…
MedDialogRubrics: A Comprehensive Benchmark and Evaluation Framework for Multi-turn Medical Consultations in Large Language Models
Lecheng Gong, Weimin Fang, Ting Yang +9
Medical conversational AI (AI) plays a pivotal role in the development of safer and more effective medical dialogue systems. However, existing benchmarks and evaluation frameworks…
Multi-Agent Deep Research: Training Multi-Agent Systems with M-GRPO
Haoyang Hong, Jiajun Yin, Yuan Wang +14
Multi-agent systems perform well on general reasoning tasks. However, the lack of training in specialized areas hinders their accuracy. Current training methods train a unified lar…
Self-Rewarding Rubric-Based Reinforcement Learning for Open-Ended Reasoning
Zhiling Ye, Yun Yue, Haowen Wang +11
Open-ended evaluation is essential for deploying large language models in real-world settings. In studying HealthBench, we observe that using the model itself as a grader and gener…