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

Interactive Benchmarks

Beginner

Baoqing Yue, Zihan Zhu et al.Mar 5arXiv

This paper says we should test AI the way real life works: by letting it ask questions, gather clues, and make smart moves step by step under a limited budget.

#interactive benchmarks#information acquisition#budgeted reasoning

Calibrate-Then-Act: Cost-Aware Exploration in LLM Agents

Intermediate

Wenxuan Ding, Nicholas Tomlin et al.Feb 18arXiv

This paper teaches AI agents to make smart choices about when to explore for more information and when to act right away.

#Calibrate-Then-Act#cost-aware exploration#LLM agents

Neural Predictor-Corrector: Solving Homotopy Problems with Reinforcement Learning

Intermediate

Jiayao Mai, Bangyan Liao et al.Feb 3arXiv

This paper shows that many hard math and AI problems can be solved with one shared idea called homotopy, where we move from an easy version of a problem to the real one step by step.

#homotopy continuation#predictor-corrector#reinforcement learning

Papers3

Interactive Benchmarks

Calibrate-Then-Act: Cost-Aware Exploration in LLM Agents

Neural Predictor-Corrector: Solving Homotopy Problems with Reinforcement Learning