Idea Search: Guiding Tree Search with Ideas to Explore Diverse Scientific Methods
Xuefei Julie Wang, Hao Cui, Michael P. Brenner, Subhashini Venugopalan
cs.LG, cs.AI, q-bio.GN, q-bio.QM
Submitted: 2026-08-09
Updated: 2026-08-11
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Terminology
Sources
- SWE-Search: Enhancing Software Agents with Monte Carlo Tree Search and Iterative Refinement
- ResearchAgent: Iterative Research Idea Generation over Scientific Literature with Large Language Models
- AdaEvolve: Adaptive LLM Driven Zeroth-Order Optimization
- Frontier-Eng: Benchmarking Self-Evolving Agents on Real-World Engineering Tasks with Generative Optimization
- The Station: An Open-World Environment for AI-Driven Discovery
- Nova: An Iterative Planning and Search Approach to Enhance Novelty and Diversity of LLM Generated Ideas
- AIDE: AI-Driven Exploration in the Space of Code
- Chain of Ideas: Revolutionizing Research Via Novel Idea Development with LLM Agents
- EvoX: Meta-Evolution for Automated Discovery
- ML-Master: Towards AI-for-AI via Integration of Exploration and Reasoning
- AlphaEvolve: A coding agent for scientific and algorithmic discovery
- Can LLMs Generate Novel Research Ideas? A Large-Scale Human Study with 100+ NLP Researchers
- The Ideation-Execution Gap: Execution Outcomes of LLM-Generated versus Human Research Ideas
- AI Research Agents for Machine Learning: Search, Exploration, and Generalization in MLE-bench
- Planning In Natural Language Improves LLM Search For Code Generation
- Self-Consistency Improves Chain of Thought Reasoning in Language Models
- ThetaEvolve: Test-time Learning on Open Problems
- Learning to Discover at Test Time
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