most citedMedDialogRubrics: A Comprehensive Benchmark and Evaluation Framework for Multi-turn Medical Consultations in Large Language Models

1 citations · 2 across the 8 of their papers we have counts for

collaborators

8 papers

cs.AI2026

Bridging the Detection-to-Abstention Gap in Reasoning Models under Insufficient Information

Renjie Gu, Jiaxu Li, Yihao Wang +8

We highlight a failure mode of large reasoning models on questions with insufficient information: models may recognize that a problem is under-specified, yet still continue reasoni…

cs.AI2026

MedMemoryBench: Benchmarking Agent Memory in Personalized Healthcare

Yihao Wang, Haoran Xu, Renjie Gu +10

The large-scale deployment of personalized healthcare agents demands memory mechanisms that are exceptionally precise, safe, and capable of long-term clinical tracking. However, ex…

cs.CL2026★ 1 cited

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…

cs.AI2025

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…

cs.CL2025

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…

cs.CL2025

MedResearcher-R1: Expert-Level Medical Deep Researcher via A Knowledge-Informed Trajectory Synthesis Framework

Ailing Yu, Lan Yao, Jingnan Liu +13

Recent developments in Large Language Model (LLM)-based agents have shown impressive capabilities spanning multiple domains, exemplified by deep research systems that demonstrate s…

cs.LG2025

Learning to Align, Aligning to Learn: A Unified Approach for Self-Optimized Alignment

Haowen Wang, Yun Yue, Zhiling Ye +12

Alignment methodologies have emerged as a critical pathway for enhancing language model alignment capabilities. While SFT (supervised fine-tuning) accelerates convergence through d…

cs.IR2025★ 1 cited

DIVER: A Multi-Stage Approach for Reasoning-intensive Information Retrieval

Duolin Sun, Meixiu Long, Dan Yang +9

Retrieval-augmented generation has achieved strong performance on knowledge-intensive tasks where query-document relevance can be identified through direct lexical or semantic matc…