5 papers
AV-SyncBench: Decoupled Benchmarking of Temporal and Semantic Audio-Visual Synchronization
Tianhong Zhou, Mingyang Han, Boyu Li +8
Audio-visual feature extraction is a fundamental component of multimodal understanding and generation tasks. However, existing evaluation protocols for feature extraction models ex…
VoiceGiraffe: A Benchmark for Extreme Long-Context Audio-Language Understanding
Jashin Ye, Dongxiao Wang, Yixuan Ye +10
While large audio language models (LALMs) have achieved remarkable progress in audio processing at the second- or minute-level scale, understanding hour-level audio remains a funda…
EchoDistill:Alignment Noisy-to-Clean Self-Distillation for Robust Audio LLMs
Liang Lin, Chunxi Luo, Kaiwen Luo +9
Audio Large Language Models (ALLMs) are highly vulnerable to real-world noise, which often induces severe semantic drift and hallucinations. Existing robustness methods primarily r…
RSA-Bench: Benchmarking Audio Large Models in Real-World Acoustic Scenarios
Yibo Zhang, Liang Lin, Kaiwen Luo +8
While Audio Large Models (ALMs) have achieved remarkable proficiency, their robustness remains brittle in real-world deployment. Existing evaluations largely rely on synthetic Gaus…
CSSBench: Evaluating the Safety of Lightweight LLMs against Chinese-Specific Adversarial Patterns
Zhenhong Zhou, Shilinlu Yan, Chuanpu Liu +3
Large language models (LLMs) are increasingly deployed in cost-sensitive and on-device scenarios, and safety guardrails have advanced mainly in English. However, real-world Chinese…