The authors propose an evaluation framework for LLM-generated structured search summaries and describe plans for implementing and testing it.
Proceedings of the 2017 Conference on Conference Human Information Interaction and Retrieval , pages =
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A multi-turn RAG system combines learned sparse retrieval with LLM-conditioned rewriting, listwise reranking, and generation to handle conversational QA and unanswerable queries across four domains.
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Plans for Evaluating Structured Generative Search Summaries
The authors propose an evaluation framework for LLM-generated structured search summaries and describe plans for implementing and testing it.
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uva-irlab-conv at SemEval-2026 Task 8: Multi-Turn RAG with Learned Sparse Retrieval and Listwise Reranking
A multi-turn RAG system combines learned sparse retrieval with LLM-conditioned rewriting, listwise reranking, and generation to handle conversational QA and unanswerable queries across four domains.