3 papers
cs.IR2026
ProRetrieval: Learning to Orchestrate Hybrid Search via Executable Program Synthesis
Chengsong You, Zhen Sun, Yunhai Hu +17
Real-world retrieval often composes structured constraints with semantic intents over text and images through arbitrary Boolean logic. Existing hybrid pipelines such as reciprocal…
cs.IR2026
DSL-R1: From SQL to DSL for Training Retrieval Agents across Structured and Unstructured Data with Reinforcement Learning
Yunhai Hu, Junwei Zhou, Yumo Cao +8
Effective retrieval in complex domains requires bridging the gap between structured metadata and unstructured content. Existing systems typically isolate these capabilities, relyin…
cs.CL2024
Knowledge Graph Reasoning with Self-supervised Reinforcement Learning
Ying Ma, Owen Burns, Mingqiu Wang +6
Reinforcement learning (RL) is an effective method of finding reasoning pathways in incomplete knowledge graphs (KGs). To overcome the challenges of a large action space, a self-su…