A comprehensive index of artificial intelligence and machine-learning research with AI-generated summaries, citation metrics, and direct links to papers and code.
Bowei Tian, Xuntao Lyu, Meng Liu, et al.
This paper provides a theoretical and empirical analysis of why representation engineering works in vision-language models, offering a unified framework and practical insights.
Zhengqing Yuan, Weixiang Sun, Yixin Liu, et al.
EfficientLLM is a comprehensive benchmark and empirical study of efficiency techniques for LLMs, evaluating over 100 model-technique pairs across architecture, fine-tuning, and inference axes.
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This paper empirically studies the design of vision Mixture-of-Experts (MoE) models, providing insights into routing strategies and expert architectures for improved scalability.
Xixi Wu, Qianguo Sun, Ruiyang Zhang, et al.
A systematic empirical study demystifying the RL design space for long-horizon, tool-using agents using TravelPlanner as a testbed.