5 citations · 5 across the 5 of their papers we have counts for
6 papers
Same Context, Different Agents: A Behavioral Study of Semantic Layers, Orchestration and Compaction in Data Agents
Zhivar Sourati, Marianne Menglin Liu, Zheng Wang +6
Answering questions over heterogeneous data means combining evidence from files, databases, documents and the web. Data agents automate this, but their success depends on context.…
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…
Speech Retrieval-Augmented Generation without Automatic Speech Recognition
Do June Min, Karel Mundnich, Andy Lapastora +3
One common approach for question answering over speech data is to first transcribe speech using automatic speech recognition (ASR) and then employ text-based retrieval-augmented ge…
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…
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…
SpeechVerse: A Large-scale Generalizable Audio Language Model
Nilaksh Das, Saket Dingliwal, Srikanth Ronanki +14
Large language models (LLMs) have shown incredible proficiency in performing tasks that require semantic understanding of natural language instructions. Recently, many works have f…