A comprehensive index of artificial intelligence and machine-learning research with AI-generated summaries, citation metrics, and direct links to papers and code.
Yu Wang, Shiwan Zhao, Zhihu Wang, et al.
SCoT improves LLM reasoning by first eliciting a problem-solving strategy before generating Chain-of-Thought steps, achieving significant gains on reasoning benchmarks.
Léonard Boussioux, Jacqueline N. Lane, Miaomiao Zhang, et al.
Human-AI collaborative solutions for creative problem-solving show superior strategic viability and quality over human-only ideas, though human ideas are more novel.
Xinyi Li, S. Wang, Siqi Zeng, et al.
A comprehensive survey of LLM-based multi-agent systems, proposing a unified five-component workflow framework and reviewing applications in problem-solving and world simulation.
Unknown
ReST^EM iteratively self-trains language models via EM-like steps, using binary feedback to filter model-generated samples and fine-tune the base model, improving problem-solving without human data.
Unknown
MAmmoTH introduces a series of LLMs trained on MathInstruct, a dataset combining chain-of-thought and program-of-thought rationales for general math problem-solving.