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

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All SourcesarXiv
#multi-turn reasoning

Agent-Omit: Training Efficient LLM Agents for Adaptive Thought and Observation Omission via Agentic Reinforcement Learning

Intermediate
Yansong Ning, Jun Fang et al.Feb 4arXiv

Agent-Omit teaches AI agents to skip unneeded thinking and old observations, cutting tokens while keeping accuracy high.

#LLM agents#reinforcement learning#agentic RL

D-CORE: Incentivizing Task Decomposition in Large Reasoning Models for Complex Tool Use

Intermediate
Bowen Xu, Shaoyu Wu et al.Feb 2arXiv

This paper fixes a common problem in reasoning AIs called Lazy Reasoning, where the model rambles instead of making a good plan.

#task decomposition#tool use#large reasoning models

Figure It Out: Improve the Frontier of Reasoning with Executable Visual States

Intermediate
Meiqi Chen, Fandong Meng et al.Dec 30arXiv

FIGR is a new way for AI to β€˜think by drawing,’ using code to build clean, editable diagrams while it reasons.

#executable visual states#diagrammatic reasoning#reinforcement learning for reasoning