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InternAgent-1.5: A Unified Agentic Framework for Long-Horizon Autonomous Scientific Discovery
This is the official repository for HypoGeniC (Hypothesis Generation in Context) and HypoRefine, which are automated, data-driven tools that leverage large language models to generate hypothesis for open-domain research. For more details, please see the original paper using the link below.
Systematically learn and evaluate the latent geometry of high-dimensional data, with a focus on scRNAseq analysis
Official implementation of the ACL 2024: Scientific Inspiration Machines Optimized for Novelty
AI research assistant for researchers: turns ideas into evidence-grounded outcomes with live paper retrieval, full-text reasoning, citation tracing, and proposal workflow planning.
AGATHA: Automatic Graph-mining And Transformer based Hypothesis generation Approach
Locally hosted AI Agent Python Tool To Generate Novel Research Hypothesis + Titles + Abstracts
A platform for Interactive AI-assisted Hypothesis Generation [ACL 2025]
Deep Critical Research Agent : The first AI-driven Critical Analysis to turn the huge amount of preclinical biology data and information into knowledge and hence disease cures.
Symbolic XAI explainable machine learning & non-linear regression platform for MATLAB
AstroAgents: Multi-Agent AI for Hypothesis Generation from Mass Spectrometry Data
Workflow to generate interactive feature selection report for cross-sectional or longitudinal studies
A open source Literature Based Discovery system, using Groovy & Grails, including a re-implementation of the Arrowsmith algorithm(s)
A Python library for creating and exploring structured review articles.
How do you train retrievers to find inspirations? [ACL 2025]
AI-powered positioning, competitive research, and CRO skills for Claude Code. Autonomous web research, analytics audits, experiment planning, and landing page generation.
Official code for the paper: "Simple LLM Baselines are Competitive for Model Diffing"
IRIS Gate Protocol: Cross-architecture phenomenological convergence research (RFC v0.2)
Case Studies & Problems based on Data Science Lifecycle Framework - Problem Formulation, Hypothesis Building, Data Extraction and Cleaning, Data Modeling and Post Modeling
A verifiers RL environment that trains models to propose novel, evidence-grounded, falsifiable hypotheses. Rewards novelty with accountability.
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