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cs.SD2026

Spectro-Temporal Interference Confounds Phase Encoding in Spatial Audio Foundation Models

Yuxuan Chen, Haoyuan Yu, Peize He

Recent spatial self supervised audio models achieve high performance on localization tasks, raising questions about their encoding of microsecond interaural phase fine structures.…

cs.SD2026

Inside the Latent Flow: Causal Deciphering of Attention Dynamics in Audio Separation Foundation Models

Yuxuan Chen, Haoyuan Yu, Peize He

Flow-matching transformers achieve strong audio separation, yet their attention dynamics are opaque. We adapt established causal-intervention principles into a deterministic, infer…

cs.SD2026

HeadRouter: Dynamic Head-Weight Routing for Task-Adaptive Audio Token Pruning in Large Audio Language Models

Peize He, Yaodi Luo, Xiaoqian Liu +7

Recent large audio language models (LALMs) demonstrate remarkable capabilities in processing extended multi-modal sequences, yet incur high inference costs. Token compression is an…

cs.SD2026

AudioKV: KV Cache Eviction in Efficient Large Audio Language Models

Yuxuan Wang, Peize He, Xiyan Gui +6

Large Audio-Language Models (LALMs) have set new benchmarks in speech processing, yet their deployment is hindered by the memory footprint of the Key-Value (KV) cache during long-c…

cs.SD2026

UniWhisper: Efficient Continual Multi-task Training for Robust Universal Audio Representation

Yuxuan Chen, Peize He, Haoyuan Yu +1

A universal audio representation should capture fine-grained speech cues and high-level semantics for environmental sounds and music in a single encoder. Existing encoders often ex…

cs.SD2025

AudioMarathon: A Comprehensive Benchmark for Long-Context Audio Understanding and Efficiency in Audio LLMs

Peize He, Zichen Wen, Yubo Wang +13

Processing long-form audio is a major challenge for Large Audio Language models (LALMs). These models struggle with the quadratic cost of attention () and with modeling lon…