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cs.CL2026
Robust Audio-Text Retrieval via Cross-Modal Attention and Hybrid Loss
Meizhu Liu, Matthew Rowe, Amit Agarwal +8
Audio-text retrieval enables semantic alignment between audio content and natural language queries, supporting applications in multimedia search, accessibility, and surveillance. H…
cs.CL2026
Au-M-ol: A Unified Model for Medical Audio and Language Understanding
Meizhu Liu, Nistha Mitra, Paul Li +3
In this work, we present Au-M-ol, a novel multimodal architecture that extends Large Language Models (LLMs) with audio processing. It is designed to improve performance on clinical…
cs.CL2026
Think Twice Before You Write -- an Entropy-based Decoding Strategy to Enhance LLM Reasoning
Jiashu He, Meizhu Liu, Olaitan P Olaleye +9
Decoding strategies play a central role in shaping the reasoning ability of large language models (LLMs). Traditional methods such as greedy decoding and beam search often suffer f…