@inproceedings{shrestha-aryal-2026-howard,
    title = "{H}oward {U}niversity-{AI}4{PC} at {S}em{E}val-2026 Task 8: Query Reformulation and Dense-Lexical Retrieval Fusion for Multi-Turn Retrieval-Augmented Generation",
    author = "Shrestha, Sijan  and
      Aryal, Saurav",
    editor = "Kochmar, Ekaterina  and
      Ghosh, Debanjan  and
      North, Kai  and
      Komachi, Mamoru",
    booktitle = "Proceedings of the 20th {I}nternational {W}orkshop on {S}emantic {E}valuation (2026)",
    month = jul,
    year = "2026",
    address = "San Diego, California, USA",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-acl-workshops/2026.semeval-1.320/",
    pages = "2533--2539",
    ISBN = "979-8-89176-414-9",
    abstract = "We present a training-free hybrid retrieve-then-rerank system for multi-turn retrieval-augmented generation, submitted to allthree subtasks of SemEval-2026 Task 8(MTRAGEval): passage retrieval (Task A),generation with reference passages (Task B),and end-to-end RAG (Task C). Our system ad-dresses the core multi-turn challenges{---}non-standalone questions, unanswerable queries,and shifting passage relevance{---}across fourdomain-specific corpora: ClapNQ, Cloud,FiQA, and Govt. Queries are reformulatedthrough LLM-driven rewriting, decompositioninto sub-queries, and Hypothetical DocumentEmbeddings (HyDE). Retrieved candidatesfrom dense vector search (BGE-base-en-v1.5)and BM25 lexical matching are fused via Re-ciprocal Rank Fusion and reranked by a cross-encoder (BGE-reranker-large). Llama-3.3-70B-Instruct generates extractive, context-groundedresponses with built-in abstention for unanswer-able queries. Using only open-source mod-els without fine-tuning, the system achievesnDCG@5 of 0.4098 on Task A (22nd/38), aharmonic mean of 0.7462 on Task B (9th/26),and 0.5796 on Task C (2nd/29), coming within1.1{\%} of the top submission. We attribute thestrong Task C result to the synergy betweenmulti-signal query reformulation and faithfulextractive generation."
}