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cs.IR2026
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…
cs.IR2026
SumRank: Aligning Summarization Models for Long-Document Listwise Reranking
Jincheng Feng, Wenhan Liu, Zhicheng Dou
Large Language Models (LLMs) have demonstrated superior performance in listwise passage reranking task. However, directly applying them to rank long-form documents introduces both…
cs.IR2026
Agentic-R: Learning to Retrieve for Agentic Search
Wenhan Liu, Xinyu Ma, Yutao Zhu +4
Agentic search has recently emerged as a powerful paradigm, where an agent interleaves multi-step reasoning with on-demand retrieval to solve complex questions. Despite its success…