arXiv (OAI Expanded)
open access
Exploiting Speech LLM Representations for Multilingual and Cross-Lingual Parkinson's Disease Detection
Speech Large Language Models (Speech LLMs) have shown strong performance across diverse tasks, yet their utility for pathological speech analysis remains underexplored. In this work, we investigate the effectiveness of internal representations from encoder and decoder components of Speech LLMs for P
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Where Does the Signal Live? A Web Data Recipe for Medical Encoder Pretraining#985143
- Uncovering Ordinal-Matching Bias in Audio-Visual LLMs#1119296
- Resolution as a First-Class Decision: Task-Conditioned Routing for Efficient Multimodal Large Language Models#1129550
- MAD: Modality-Adaptive Decoding for Mitigating Cross-Modal Hallucinations in Multimodal Large Language Models#999725
- Universal Defenses for Tool-Integrated LLM Agents Against Adversarial Attacks#1110485
Record · ID 1083865
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive