AI-Scientist-v2
The AI Scientist-v2: Workshop-Level Automated Scientific Discovery via Agentic Tree Search
Discover agentic tree search benefits in AI Scientist v2. Explore a parallel, self-correcting system for efficient AI research and automated pruning.
How AI Scientist v2 Uses Semantic Scholar for Literature Search and Automated CitationsDiscover how AI Scientist v2 leverages Semantic Scholar for literature search and automated citations. Explore autonomous discovery and effortless manuscript generation.
AI Scientist v1 vs v2: How the Template-Driven System Evolved into an Agentic Research EngineExplore the evolution from AI Scientist v1's rigid templates to v2's agentic research engine. Discover how the Experiment Manager dynamically drives scientific discovery.
How to Perform Ideation with AI Scientist v2: Automated Research Generation GuideLearn how to perform ideation with AI Scientist v2 for automated research generation Create proposals using LLMs literature search and multi-round reflection Get structured JSON outputs from this powerful tool
Default Timeout for Experiments in AI Scientist v2: Complete Configuration GuideDiscover the default experiment timeout in AI Scientist v2. Learn how to configure this setting using bfts_config.yaml for optimal experiment management.
How AI-Scientist-v2 Ensures Experiment Workspace Isolation: A Complete Technical GuideAI-Scientist-v2 ensures experiment isolation with unique directories and process subfolders, preventing file system collisions for concurrent runs. Learn how.
Understanding the Purpose of ai_scientist/llm.py in AI-Scientist-v2Discover the central role of ai_scientist/llm.py in AI-Scientist-v2. This module unifies LLM interactions, manages client creation, routing, retries, and output parsing for seamless AI development.
How to Specify Different LLMs for Different Tasks in AI Scientist v2Learn how to specify different LLMs for different tasks in AI Scientist v2. Easily assign LLMs to code generation, feedback, write-ups & more using YAML config and command-line flags.
How to Run the Full AI Scientist v2 Pipeline: A Complete End-to-End GuideRun the full AI Scientist v2 pipeline end-to-end. Execute ideation with perform_ideation_temp_free.py and launch the autonomous workflow via launch_scientist_bfts.py for research, experimentation, and review.
What LLM Models Are Supported by AI Scientist v2: Complete Model CatalogDiscover which LLM models AI Scientist v2 supports. Explore the full catalog featuring models from Anthropic, OpenAI, Meta, Google, and more. Access the complete list now.
How AI Scientist v2 Gathers Citations for Research Papers: A Deep Dive into Semantic Scholar IntegrationDiscover how AI Scientist v2 gathers research paper citations using Semantic Scholar integration. Learn about metadata retrieval, citation sorting, and reference formatting for LLM ideation.
Difference Between perform_writeup.py and perform_icbinb_writeup.py in AI-Scientist-v2Understand the differences between perform_writeup.py and perform_icbinb_writeup.py in AI-Scientist-v2. Generate LaTeX papers for ML conferences and ICBINB workshops with specific optimizations.
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