AQUA-Bench: Beyond Finding Answers to Knowing When There Are None in Audio Question Answering

arXiv:2601.12248v2 Announce Type: replace-cross Abstract: Recent advances in audio-aware large language models have shown strong performance on audio question answering. However, existing benchmarks mainly cover answerable questions and overlook the challenge of unanswerable ones, where no reliable answer can be inferred from the audio. Such cases are common in real-world settings, where questions may be misleading, ill-posed, or incompatible with the information. To address this gap, we present