arXiv (All)
open access
FSA-GRPO: Teaching Auditory LLMs to Use Few-Shot Demonstrations
Few-shot prompting provides an effective way to adapt auditory large language models to low-resource tasks such as children's speech recognition. However, most auditory large language models are not explicitly trained to perform inference in this demonstration-conditioned format, limiting the extent
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
- FSA-GRPO: Teaching Auditory LLMs to Use Few-Shot Demonstrations#789702
- ProCAP: Probabilistic Cross-Attentive Prompt Learning for Vision-Language Models#1104633
- I-Perceive: A Foundation Model for Active Perception with Language Instructions#609880
- The Linear Representation Hypothesis for Vision-Language-Action Models#1105555
- On the Limits of Prompt-Conditioned Language Models as General-Purpose Learners#299920
Record · ID 793706
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