mlsanityData to 7 Oct 2026

uva-irlab-conv at SemEval-2026 Task 8: Multi-Turn RAG with Learned Sparse Retrieval and Listwise Reranking

arXiv 2606.11945 ↗First posted 10 Jun 2026cs.CL cs.IRcited by 0

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Abstract (arXiv)

This report describes our participation in SemEval-2026 Task 8 on multi-turn retrieval and question answering. The task evaluates conversational systems across four domains (finance, cloud documentation, government, Wikipedia), and includes unanswerable queries where the available collection does not contain sufficient evidence to produce a complete response. We propose a multi-turn retrieval-augmented generation pipeline that combines learned sparse retrieval with LLM-based reranking and generation. Using sparse retrieval as the primary retrieval method, we leverage its strong generalization across domains. In addition, we make use of the long-context capabilities of LLMs for conversational query rewriting, pointwise and listwise reranking, and generating the final response, each conditioned on the full conversational history. This multi-step design enables effective integration of conversational context throughout retrieval and generation, improving robustness across domains.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 26 of its 44 references that are in the map. First posted on arXiv 10 Jun 2026.

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26 of 44 references.

References · 26

  1. 2022ReAct: Synergizing Reasoning and Acting in Language Modelscited by 8,355
  2. 2023Self-RAG: Learning to Retrieve, Generate, and Critique through Self-Reflectioncited by 1,800
  3. 2022Interleaving Retrieval with Chain-of-Thought Reasoning for Knowledge-Intensive Multi-Step Questionscited by 911
  4. 2025LLMs Get Lost In Multi-Turn Conversationcited by 400
  5. 2021SPLADE: Sparse Lexical and Expansion Model for First Stage Rankingcited by 283
  6. 2023Evaluating Correctness and Faithfulness of Instruction-Following Models for Question Answeringcited by 150
  7. 2020Open-Domain Question Answering Goes Conversational via Question Rewritingcited by 147
  8. 2022From Distillation to Hard Negative Sampling: Making Sparse Neural IR Models More Effectivecited by 98
  9. 2021TopiOCQA: Open-domain Conversational Question Answering with Topic Switchingcited by 95
  10. 2020Question Rewriting for Conversational Question Answeringcited by 93
  11. 2023Large Language Models Know Your Contextual Search Intent: A Prompting Framework for Conversational Searchcited by 74
  12. 2024CHIQ: Contextual History Enhancement for Improving Query Rewriting in Conversational Searchcited by 29
14 more
  1. 2024Efficient Inverted Indexes for Approximate Retrieval over Learned Sparse Representationscited by 23
  2. 2024RAD-Bench: Evaluating Large Language Models Capabilities in Retrieval Augmented Dialoguescited by 19
  3. 2023A Unified Framework for Learned Sparse Retrievalcited by 17
  4. 2024TREC iKAT 2023: A Test Collection for Evaluating Conversational and Interactive Knowledge Assistantscited by 16
  5. 2025Scaling Sparse and Dense Retrieval in Decoder-Only LLMscited by 12
  6. 2025UniConv: Unifying Retrieval and Response Generation for Large Language Models in Conversationscited by 11
  7. 2025Lightweight and Direct Document Relevance Optimization for Generative Information Retrievalcited by 9
  8. 2024DiSCo: LLM Knowledge Distillation for Efficient Sparse Retrieval in Conversational Searchcited by 8
  9. 2025Conversational Gold: Evaluating Personalized Conversational Search System using Gold Nuggetscited by 8
  10. 2026MTRAG-UN: A Benchmark for Open Challenges in Multi-Turn RAG Conversationscited by 8
  11. 2024Generating Multi-Aspect Queries for Conversational Searchcited by 7
  12. 2025ChatR1: Reinforcement Learning for Conversational Reasoning and Retrieval Augmented Question Answeringcited by 4
  13. 2024IRLab@iKAT24: Learned Sparse Retrieval with Multi-aspect LLM Query Generation for Conversational Searchcited by 3
  14. 2025Investigating LLM Variability in Personalized Conversational Information Retrievalcited by 2

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  1. 2024Learning When to Retrieve, What to Rewrite, and How to Respond in Conversational QA
  2. 2026Re-ranking and Late Interaction Drive Retrieval Quality: A Controlled Comparison of RAG Strategies for Scientific Question Answering
  3. 2026Comprehensive Comparison of RAG Methods Across Multi-Domain Conversational QA
  4. 2026Sifei at SemEval-2026 Task 8: Hybrid Retrieval and Query Rewriting for Multi-Turn RAG
  5. 2026AILS-NTUA at SemEval-2026 Task 8: Evaluating Multi-Turn RAG Conversations
  6. 2025MTRAG: A Multi-Turn Conversational Benchmark for Evaluating Retrieval-Augmented Generation Systems
  7. 2026SciRet: A Compute-Aware Empirical Study of Retrieval and Reranking for Scientific RAG
  8. 2024Boosting Conversational Question Answering with Fine-Grained Retrieval-Augmentation and Self-Check