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How I Study AI - Learn AI Papers & Lectures the Easy Way

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All SourcesarXiv
#execution feedback

CLI-Gym: Scalable CLI Task Generation via Agentic Environment Inversion

Intermediate
Yusong Lin, Haiyang Wang et al.Feb 11arXiv

CLI-Gym is a new way to create lots of realistic computer-fixing tasks for AI by safely breaking and then repairing software environments inside containers.

#agentic coding#command line interface#Dockerfile

daVinci-Dev: Agent-native Mid-training for Software Engineering

Intermediate
Ji Zeng, Dayuan Fu et al.Jan 26arXiv

This paper teaches code AIs to work more like real software engineers by training them in the middle of their learning using real development workflows.

#agentic mid-training#agent-native data#contextually-native trajectories

SAGE: Steerable Agentic Data Generation for Deep Search with Execution Feedback

Intermediate
Fangyuan Xu, Rujun Han et al.Jan 26arXiv

SAGE is a two-agent system that automatically writes tough, multi-step search questions and checks them by actually trying to solve them.

#deep search#agentic data generation#execution feedback

UCoder: Unsupervised Code Generation by Internal Probing of Large Language Models

Intermediate
Jiajun Wu, Jian Yang et al.Dec 19arXiv

The paper introduces UCoder, a way to teach a code-generating AI to get better without using any outside datasets, not even unlabeled code.

#unsupervised code generation#self-training#internal probing