3 citations · 3 across the 8 of their papers we have counts for
4 papers · 1 filter
IDRBench: Benchmarking the Interactive Capabilities of Deep Research Agents
Yingchaojie Feng, Qiang Huang, Xiaoya Xie +4
Large Language Model (LLM)-based deep research agents perform multi-step reasoning, web exploration, and long-form report generation. In these long-horizon workflows, early deviati…
Planner and Executor: Collaboration between Discrete Diffusion And Autoregressive Models in Reasoning
Lina Berrayana, Ahmed Heakl, Muhammad Abdullah Sohail +3
Current autoregressive language models (ARMs) achieve high accuracy but require long token sequences, making them costly. Discrete diffusion language models (DDLMs) enable parallel…
Enhancing Large Language Model Reasoning with Reward Models: An Analytical Survey
Qiyuan Liu, Hao Xu, Xuhong Chen +3
Reward models (RMs) play a critical role in enhancing the reasoning performance of LLMs. For example, they can provide training signals to finetune LLMs during reinforcement learni…
LLMs Can Simulate Standardized Patients via Agent Coevolution
Zhuoyun Du, Lujie Zheng, Renjun Hu +7
Training medical personnel using standardized patients (SPs) remains a complex challenge, requiring extensive domain expertise and role-specific practice. Previous research on Larg…