activity
20242026
most citedMed-R: Crafting Trustworthy LLM Physicians via Retrieval and Reasoning of Evidence-Based Medicine

4 citations · 4 across the 8 of their papers we have counts for

collaborators

8 papers

cs.CL2026

REAL: A Reasoning-Enhanced Graph Framework for Long-Term Memory Management of LLMs

Keer Lu, Liwei Chen, Guoqing Jiang +3

Large Language Models (LLMs) are increasingly expected to interact with users over long time horizons. However, due to their finite context window, LLMs cannot retain all past inte…

cs.CL2025

PilotRL: Training Language Model Agents via Global Planning-Guided Progressive Reinforcement Learning

Keer Lu, Chong Chen, Bin Cui +2

Large Language Models (LLMs) have shown remarkable advancements in tackling agent-oriented tasks. Despite their potential, existing work faces challenges when deploying LLMs in age…

cs.CL2025

Med-R: Enhancing Medical Retrieval-Augmented Reasoning of LLMs via Progressive Reinforcement Learning

Keer Lu, Zheng Liang, Youquan Li +7

In medical scenarios, effectively retrieving external knowledge and leveraging it for rigorous logical reasoning is of significant importance. Despite their potential, existing wor…

cs.CL2025★ 4 cited

Med-R: Crafting Trustworthy LLM Physicians via Retrieval and Reasoning of Evidence-Based Medicine

Keer Lu, Zheng Liang, Da Pan +6

Large Language Models (LLMs) have exhibited remarkable capabilities in clinical scenarios. Despite their potential, existing works face challenges when applying LLMs to medical set…

cs.CL2024

VersaTune: An Efficient Data Composition Framework for Training Multi-Capability LLMs

Keer Lu, Keshi Zhao, Zhuoran Zhang +8

As demonstrated by the proprietary Large Language Models (LLMs) such as GPT and Claude series, LLMs have the potential to achieve remarkable proficiency across a wide range of doma…

cs.CL2024

DataSculpt: Crafting Data Landscapes for Long-Context LLMs through Multi-Objective Partitioning

Keer Lu, Xiaonan Nie, Zheng Liang +8

In recent years, Large Language Models (LLMs) have demonstrated significant improvements across a variety of tasks, one of which is the long-context capability. The key to improvin…

cs.CL2024

Facilitating Multi-turn Function Calling for LLMs via Compositional Instruction Tuning

Mingyang Chen, Haoze Sun, Tianpeng Li +7

Large Language Models (LLMs) have exhibited significant potential in performing diverse tasks, including the ability to call functions or use external tools to enhance their perfor…

cs.AI2024

Baichuan-Omni Technical Report

Yadong Li, Haoze Sun, Mingan Lin +23

The salient multimodal capabilities and interactive experience of GPT-4o highlight its critical role in practical applications, yet it lacks a high-performing open-source counterpa…