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cs.CL2024
Zero-resource Speech Translation and Recognition with LLMs
Karel Mundnich, Xing Niu, Prashant Mathur +10
Despite recent advancements in speech processing, zero-resource speech translation (ST) and automatic speech recognition (ASR) remain challenging problems. In this work, we propose…
cs.CL2024
SpeechGuard: Exploring the Adversarial Robustness of Multimodal Large Language Models
Raghuveer Peri, Sai Muralidhar Jayanthi, Srikanth Ronanki +11
Integrated Speech and Large Language Models (SLMs) that can follow speech instructions and generate relevant text responses have gained popularity lately. However, the safety and r…
cs.LG2024
AutoGluon-Multimodal (AutoMM): Supercharging Multimodal AutoML with Foundation Models
Zhiqiang Tang, Haoyang Fang, Su Zhou +5
AutoGluon-Multimodal (AutoMM) is introduced as an open-source AutoML library designed specifically for multimodal learning. Distinguished by its exceptional ease of use, AutoMM ena…