Tag: AI fine-tuning
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Orak Benchmark: Train & Evaluate LLM Agents in Video Games
Discover Orak, a benchmark for training and evaluating LLM agents across diverse video games with fine-tuning datasets and versatile game coverage.
Emergent Attention Heads in Post-Training Reasoning Models
Discover how post-training sparks emergent attention heads that enhance reasoning models' performance and reveal key trade-offs in AI computation.
SOAR: Enhancing Diffusion Models with Self-Correction
Discover SOAR, a post-training method that boosts diffusion model performance via self-correction, improving alignment and refinement without reward models...
Why LLMs Struggle with Abstract Meaning Comprehension
Explore why large language models struggle with abstract meanings and how fine-tuning and new methods improve their comprehension abilities.
Polynomial Expansion Rank Adaptation for Efficient Fine-Tuning
Discover Polynomial Expansion Rank Adaptation (PERA) to enhance low-rank fine-tuning with high-order interactions for better large language model performan...