7 papers
MemCalib: Benchmarking and Optimizing Memory Use in LLM Agents
Ruike Cao, Fanyu Zhao, Fugen Yao +6
The effectiveness of agent memory ultimately depends on whether the underlying LLM gives each memory in context an appropriate degree of influence over its response. Yet this capab…
RPMem: Learning Long-Term Recurrent Parametric Memory Across Sessions for LLM Agents
Fanyu Zhao, Ruike Cao, Liang Dong +6
Long-running LLM agents require memory that persists and evolves across sessions. Text-based memory retrieves and reconstructs past interactions at every query, making long-horizon…
QuarkMedSearch: A Long-Horizon Deep Search Agent for Exploring Medical Intelligence
Zhichao Lin, Zhichao Liang, Gaoqiang Liu +6
As agentic foundation models continue to evolve, how to further improve their performance in vertical domains has become an important challenge. To this end, building upon Tongyi D…
QuarkMedBench: A Real-World Scenario Driven Benchmark for Evaluating Large Language Models
Yao Wu, Kangping Yin, Liang Dong +13
While Large Language Models (LLMs) excel on standardized medical exams, high scores often fail to translate to high-quality responses for real-world medical queries. Current evalua…
ATPO: Adaptive Tree Policy Optimization for Multi-Turn Medical Dialogue
Ruike Cao, Shaojie Bai, Fugen Yao +3
Effective information seeking in multi-turn medical dialogues is critical for accurate diagnosis, especially when dealing with incomplete information. Aligning Large Language Model…
Generation-Augmented Generation: A Plug-and-Play Framework for Private Knowledge Injection in Large Language Models
Rongji Li, Jian Xu, Yi Chen +7
In domains such as materials science, biomedicine, and finance, high-stakes deployment of large language models (LLMs) requires injecting private, domain-specific knowledge that is…
AgriDoctor: A Multimodal Intelligent Assistant for Agriculture
Mingqing Zhang, Zhuoning Xu, Peijie Wang +6
Accurate crop disease diagnosis is essential for sustainable agriculture and global food security. Existing methods, which primarily rely on unimodal models such as image-based cla…