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cs.CL2025
ComposeRAG: A Modular and Composable RAG for Corpus-Grounded Multi-Hop Question Answering
Ruofan Wu, Youngwon Lee, Fan Shu +5
Retrieval-Augmented Generation (RAG) systems are increasingly diverse, yet many suffer from monolithic designs that tightly couple core functions like query reformulation, retrieva…
cs.SE2025
ConvCodeWorld: Benchmarking Conversational Code Generation in Reproducible Feedback Environments
Hojae Han, Seung-won Hwang, Rajhans Samdani +1
Large language models (LLMs) have proven invaluable for code generation, particularly in interactive settings. However, existing code generation benchmarks fail to capture the dive…
cs.CL2025
Agentic Verification for Ambiguous Query Disambiguation
Youngwon Lee, Seung-won Hwang, Ruofan Wu +5
In this work, we tackle the challenge of disambiguating queries in retrieval-augmented generation (RAG) to diverse yet answerable interpretations. State-of-the-arts follow a Divers…