Better Retrieval, Worse Robustness: How Multi-hop RAG Amplifies Upstream ASR Errors

arXiv:2608.22872 · cs.CL, cs.IR, eess.AS · Submitted 2026-08-24 · Read on arXiv

cs.CL, cs.IR, eess.AS

Submitted: 2026-08-24

Updated: 2026-08-25

Code: https://github.com/Continuum-AI-Corp/spoken-multihop-rag

Terminology

• RAG — 81× in this paper · explained in 3 episodes
• Benchmark — 25× in this paper · explained in 2 episodes
• Robustness — 4× in this paper · explained in 5 episodes
• Decode — 3× in this paper · explained in 2 episodes
• F1 Score — 3× in this paper · explained in 3 episodes
• Accuracy — 2× in this paper · explained in 1 episode
• Core — 2× in this paper · explained in 2 episodes
• Knowledge Graph — 2× in this paper · explained in 7 episodes
• Retrieval-Augmented Generation (RAG) — 2× in this paper · explained in 16 episodes
• Tokenization — 2× in this paper · explained in 2 episodes
• Word Error Rate — 2× in this paper
• Accountability — 1× in this paper · explained in 2 episodes
• Algorithmic Bias — 1× in this paper · explained in 1 episode
• Alignment — 1× in this paper · explained in 1 episode
• Automatic Speech Recognition (ASR) — 1× in this paper · explained in 2 episodes
• Benchmarking — 1× in this paper · explained in 3 episodes
• Continual Learning — 1× in this paper · explained in 2 episodes
• Cosine Similarity — 1× in this paper · explained in 3 episodes
• Distillation — 1× in this paper · explained in 2 episodes
• F1 and Exact Match — 1× in this paper
• Generalizability — 1× in this paper · explained in 6 episodes
• Multi-hop Reasoning — 1× in this paper · explained in 3 episodes

Sources

• Global Performance Disparities Between English-Language Accents in Automatic Speech Recognition
• From RAG to Memory: Non-Parametric Continual Learning for Large Language Models
• Spoken SQuAD: A Study of Mitigating the Impact of Speech Recognition Errors on Listening Comprehension
• Can Generative Large Language Models Perform ASR Error Correction?
• Seamless: Multilingual Expressive and Streaming Speech Translation
• Towards Data Distillation for End-to-end Spoken Conversational Question Answering

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