A comprehensive index of artificial intelligence and machine-learning research with AI-generated summaries, citation metrics, and direct links to papers and code.
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Selective Self-to-Supervised Fine-Tuning (S3FT) improves LLM fine-tuning by selectively using the model's own correct predictions or gold responses to reduce overfitting and boost generalization.
Matthew R. Masters, Amr H. Mahmoud, Markus A. Lill
This paper reveals that deep learning co-folding models for protein-ligand structure prediction often violate fundamental physical principles, indicating overfitting rather than learning true physics.