5 papers
Deep Dense Exploration for LLM Reinforcement Learning via Pivot-Driven Resampling
Yiran Guo, Zhongjian Qiao, Yingqi Xie +5
Effective exploration is a key challenge in reinforcement learning for large language models: discovering high-quality trajectories within a limited sampling budget from the vast n…
VehicleWorld: A Highly Integrated Multi-Device Environment for Intelligent Vehicle Interaction
Jie Yang, Jiajun Chen, Zhangyue Yin +7
Intelligent vehicle cockpits present unique challenges for API Agents, requiring coordination across tightly-coupled subsystems that exceed typical task environments' complexity. T…
FamilyTool: A Multi-hop Personalized Tool Use Benchmark
Yuxin Wang, Yiran Guo, Yining Zheng +7
The integration of tool learning with Large Language Models (LLMs) has expanded their capabilities in handling complex tasks by leveraging external tools. However, existing benchma…
Prior-Fitted Networks Scale to Larger Datasets When Treated as Weak Learners
Yuxin Wang, Botian Jiang, Yiran Guo +4
Prior-Fitted Networks (PFNs) have recently been proposed to efficiently perform tabular classification tasks. Although they achieve good performance on small datasets, they encount…
TablePuppet: A Generic Framework for Relational Federated Learning
Lijie Xu, Chulin Xie, Yiran Guo +6
Current federated learning (FL) approaches view decentralized training data as a single table, divided among participants either horizontally (by rows) or vertically (by columns).…