10 papers
Skill-Pro: Learning Reusable Skills from Experience via Non-Parametric PPO for LLM Agents
Qirui Mi, Zhijian Ma, Mengyue Yang +4
LLM-driven agents excel at sequential decision-making but often rely on on-the-fly reasoning, re-deriving solutions even in recurring scenarios. This insufficient experience reuse…
HiVid-Narrator: Hierarchical Video Narrative Generation with Scene-Primed ASR-anchored Compression
Haoxuan Li, Mengyan Li, Junjun Zheng
Generating structured narrations for real-world e-commerce videos requires models to perceive fine-grained visual details and organize them into coherent, high-level stories--capab…
Which Type of Students can LLMs Act? Investigating Authentic Simulation with Graph-based Human-AI Collaborative System
Haoxuan Li, Jifan Yu, Xin Cong +6
While rapid advances in large language models (LLMs) are reshaping data-driven intelligent education, accurately simulating students remains an important but challenging bottleneck…
MTIR-SQL: Multi-turn Tool-Integrated Reasoning Reinforcement Learning for Text-to-SQL
Zekun Xu, Siyu Xia, Chuhuai Yue +6
As large language models (LLMs) are increasingly used in Text-to-SQL tasks, Reinforcement Learning (RL) has become a common method for improving performance. Existing methods prima…
Beyond Normality: Reliable A/B Testing with Non-Gaussian Data
Junpeng Gong, Chunkai Wang, Hao Li +3
A/B testing has become the cornerstone of decision-making in online markets, guiding how platforms launch new features, optimize pricing strategies, and improve user experience. In…
Federated Multi-Objective Learning with Controlled Pareto Frontiers
Jiansheng Rao, Jiayi Li, Zhizhi Gong +2
Federated learning (FL) is a widely adopted paradigm for privacy-preserving model training, but FedAvg optimise for the majority while under-serving minority clients. Existing meth…