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[COLING 2025]A curated paper list about LLMs for chemistry
AI agents running research on single-GPU nanochat training automatically
Autoresearch for GPU kernels. Give it any PyTorch model, go to sleep, wake up to optimized Triton kernels.
Review automated kernel generation in the era of LLMs
Universal machine-learning models for advanced atomistic simulations
BioNeMo Framework: For building and adapting AI models in drug discovery at scale
Home for cuQuantum Python & NVIDIA cuQuantum SDK C++ samples
Open-source deep-learning framework for building, training, and fine-tuning deep learning models using state-of-the-art Physics-ML methods
ALCHEMI Toolkit-Ops is a collection of optimized batch kernels to accelerate computational chemistry and material science workflows.
The agent harness performance optimization system. Skills, instincts, memory, security, and research-first development for Claude Code, Codex, Opencode, Cursor and beyond.
Persistent file-based planning for AI coding agents and long-running agentic tasks. Crash-proof markdown plans that survive context loss and /clear, plus a deterministic completion gate and multi-a…
nablaDFT: Large-Scale Conformational Energy and Hamiltonian Prediction benchmark and dataset
cuEquivariance is a math library that is a collective of low-level primitives and tensor ops to accelerate widely-used models, like DiffDock, MACE, Allegro and NEQUIP, based on equivariant neural n…
🌟 [NeurIPS '25 Spotlight] Official implement of QHFlow for DFT Hamiltonian prediction
An Open-source RL System from ByteDance Seed and Tsinghua AIR
Fully open reproduction of DeepSeek-R1
800,000 step-level correctness labels on LLM solutions to MATH problems
verl/HybridFlow: A Flexible and Efficient RL Post-Training Framework
Analyzing chemical databases and predicting reaction conditions with cheminformatics
[ICLR 2026] Code, benchmark and environment for "ScienceBoard: Evaluating Multimodal Autonomous Agents in Realistic Scientific Workflows"
overview of datasets for ML in chemistry
Robust recipes to align language models with human and AI preferences
[EMNLP 2024] mDPO: Conditional Preference Optimization for Multimodal Large Language Models.
LucaProt: A novel deep learning framework that incorporates protein amino acid sequence and structural information to predict protein function.
Chat language model that can use tools and interpret the results
Official code repo for the paper "LlaSMol: Advancing Large Language Models for Chemistry with a Large-Scale, Comprehensive, High-Quality Instruction Tuning Dataset"