πŸŽ“How I Study AIHISA
πŸ“–Read
πŸ“„PapersπŸ“°Blogs🎬Courses
πŸ’‘Learn
πŸ›€οΈPathsπŸ“šTopicsπŸ’‘Concepts🎴Shorts
🎯Practice
🧩Problems🎯Prompts🧠Review
Search
How I Study AI - Learn AI Papers & Lectures the Easy Way

Papers4

AllBeginnerIntermediateAdvanced
All SourcesarXiv
#tool-integrated reasoning

Pushing the Boundaries of Natural Reasoning: Interleaved Bonus from Formal-Logic Verification

Intermediate
Chuxue Cao, Jinluan Yang et al.Jan 30arXiv

Large language models sometimes reach the right answer for the wrong reasons, which is risky and confusing.

#formal logic verification#interleaved verification#neuro-symbolic reasoning

BAPO: Boundary-Aware Policy Optimization for Reliable Agentic Search

Intermediate
Shiyu Liu, Yongjing Yin et al.Jan 16arXiv

RL-trained search agents often sound confident even when they don’t know, which can mislead people.

#agentic search#reinforcement learning#boundary awareness

Nested Browser-Use Learning for Agentic Information Seeking

Beginner
Baixuan Li, Jialong Wu et al.Dec 29arXiv

This paper teaches AI helpers to browse the web more like people do, not just by grabbing static snippets.

#information-seeking agents#browser-use#ReAct function-calling

Nemotron-Math: Efficient Long-Context Distillation of Mathematical Reasoning from Multi-Mode Supervision

Intermediate
Wei Du, Shubham Toshniwal et al.Dec 17arXiv

Nemotron-Math is a giant math dataset with 7.5 million step-by-step solutions created in three thinking styles and with or without Python help.

#mathematical reasoning#long-context fine-tuning#multi-mode supervision