arXiv Machine Learning
Machine Unlearning for Speech Question Answering in Large Audio-Language Models
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Confess What You Know: Forget-Set Misalignment with Model Knowledge in LLM Unlearning
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HEAR: Real Voices, Real Bias: A Large-Scale Human-Recorded, Demographically Diverse Benchmark for Audio Language Models
arXiv:2609.35952v1 Announce Type: cross Abstract: We introduce HEAR (Human-recorded Evaluation of Audio-LLM bias by Real speakers), a large-scale, ecologically valid benchmark comprising 87k real hum...