4 papers
Training Documents Reranker with Search Rubrics for Deep Research Agent
Wenhan Liu, Yu Lu, Qiaolin Xia +8
Retrieval systems help deep research agents generate high-quality answers by providing relevant documents. However, existing retrievers typically select documents through relevance…
Search-G1: Grounded Search Agents via Representation-Based Intrinsic Rewards
Ruoxi Cheng, Cheng Ruoxi, Ma Haoxuan +17
Search-augmented language agents should retrieve external information only when necessary and ground their answers in retrieved evidence. Existing external rewards provide either s…
Vertical Semi-Federated Learning for Efficient Online Advertising
Wenjie Li, Shu-Tao Xia, Jiangke Fan +2
Traditional vertical federated learning schema suffers from two main issues: 1) restricted applicable scope to overlapped samples and 2) high system challenge of real-time federate…
Laser: Governing Long-Horizon Agentic Search via Structured Protocol and Context Register
Shuting Wang, Qiaolin Xia, Vich Wang +3
Recent advances in Large Language Models (LLMs) and Large Reasoning Models (LRMs) have enabled agentic search systems that interleave multi-step reasoning with external tool use. H…