2 papers
cs.AI2026
Agents Learn Their Runtime: Interpreter Persistence as Training-Time Semantics
Victor May, Aaditya Salgarkar, Yishan Wang +2
Tool-augmented LLMs are increasingly deployed as agents that interleave natural-language reasoning with executable Python actions, as in CodeAct-style frameworks. In deployment, th…
cs.CL2024
RedPajama: an Open Dataset for Training Large Language Models
Maurice Weber, Daniel Fu, Quentin Anthony +16
Large language models are increasingly becoming a cornerstone technology in artificial intelligence, the sciences, and society as a whole, yet the optimal strategies for dataset co…