arXiv (All)
open access
On the Importance of Data Size in Probing Fine-tuned Models
Several studies have investigated the reasons behind the effectiveness of fine-tuning, usually through the lens of probing. However, these studies often neglect the role of the size of the dataset on which the model is fine-tuned. In this paper, we highlight the importance of this factor and its und
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
- ScAn-Bench: Evaluating Scaling Analysis Methodology#1130357
- ScAn-Bench: Evaluating Scaling Analysis Methodology#1108750
- On Assessing ML Model Robustness: A Methodological Framework (Academic Track)#6579
- Methods Used in Developing the Adaptive Design Extension of the DELTA² Checklist for Enhancing Sample Size Reporting in Trial Grant Applications and Protocols#629549
- Understanding LoRA Rank Trade-offs in Diffusion Model Fine-Tuning#997652
Record · ID 987347
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