3 papers
cs.CL2026
Self-Evolving LLM Memory Extraction Across Heterogeneous Tasks
Yuqing Yang, Tengxiao Liu, Wang Bill Zhu +3
As LLM-based assistants become persistent and personalized, they must extract and retain useful information from past conversations as memory. However, the types of information wor…
cs.AI2026
WildSci: Advancing Scientific Reasoning from In-the-Wild Literature
Tengxiao Liu, Deepak Nathani, Zekun Li +2
Recent progress in large language model (LLM) reasoning has focused on domains like mathematics and coding, where abundant high-quality data and objective evaluation metrics are re…
cs.AI2025
Budget-Aware Tool Use Enables Effective Agent Scaling
Tengxiao Liu, Zifeng Wang, Jin Miao +12
Scaling test-time computation has been extended from language model reasoning to tool-augmented agents, where scaling involves not only thinking in tokens but also acting via tool…