Papers with acoustic grounding

2 papers
HalluAudio: A Comprehensive Benchmark for Hallucination Detection in Large Audio-Language Models (2026.acl-long)

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Challenge: Existing studies on hallucination focus on text or vision, while few audio-oriented studies are limited in scale, modality coverage, and diagnostic depth.
Approach: They propose a large-scale benchmark for evaluating hallucinations across speech, sound, and music.
Outcome: The proposed model improves hallucination rate, yes/no bias, error-type analysis, and refusal rate.
CliniCAST: Benchmarking Acoustic Grounding and Text Dominance in Medical Triage (2026.findings-acl)

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Challenge: Recent Large Audio-Language Models (LALMs) integrate acoustic capabilities into reasoning, yet whether they reliably ground clinical judgments in audible evidence remains unproven.
Approach: They propose a benchmark that disentangles clinically meaningful acoustic cues from lexical content and speaker demographics.
Outcome: Evaluating 5,856 synthetic samples across 12 disease conditions, the proposed model exhibits fragile acoustic grounding and pronounced "text dominance" failure mode.

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