Intern-Atlas constructs a methodological evolution graph with 9.4 million edges from 1.03 million AI papers to capture how methods emerge, adapt, and transition, enabling better idea evaluation and generation for AI-driven research.
Bandit based monte-carlo planning
3 Pith papers cite this work. Polarity classification is still indexing.
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2026 3verdicts
UNVERDICTED 3roles
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use method 1representative citing papers
Framework uses LLMs to map natural-language questions about MCTS to explanations based on tree statistics like visit counts and values, without hand-crafted formal logic.
A new method decomposes property differences between weakly related molecules into minimal chemical edits to train a directional evaluator that guides multi-step optimization with less oracle querying.
citing papers explorer
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Intern-Atlas: A Methodological Evolution Graph as Research Infrastructure for AI Scientists
Intern-Atlas constructs a methodological evolution graph with 9.4 million edges from 1.03 million AI papers to capture how methods emerge, adapt, and transition, enabling better idea evaluation and generation for AI-driven research.
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Toward Template-Free Explainability for Monte Carlo Tree Search
Framework uses LLMs to map natural-language questions about MCTS to explanations based on tree statistics like visit counts and values, without hand-crafted formal logic.
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From Single-Step Edit Response to Multi-Step Molecular Optimization
A new method decomposes property differences between weakly related molecules into minimal chemical edits to train a directional evaluator that guides multi-step optimization with less oracle querying.