Hugging Face Trending Papers
Molecular LLM Agents: From Architectural Design to Scientific Autonomy
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arXiv AI
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Molecular LLM Agents: From Architectural Design to Scientific Autonomy
arXiv:2608.23104v1 Announce Type: cross Abstract: Molecular science represents an important frontier for LLM-based agents. Unlike general agents that mainly operate over natural language, code, or we...
arXiv AI
Jun 16
Protein Design with Agent Rosetta: A Case Study for Specialized Scientific Agents
arXiv:2603. 15952v2 Announce Type: replace Abstract: Large language models (LLMs) are capable of emulating reasoning and using tools, creating opportunities for autonomous agents that execute complex scientific tasks.
arXiv AI
Jun 12
MDForge: Agentic Molecular Dynamics Pipeline Design under Sparse Simulator Feedback
arXiv:2606. 12916v1 Announce Type: new Abstract: Molecular dynamics (MD) is the canonical in-silico method for atomistic molecular science, simulating molecular behavior from first-principle physics.
arXiv AI
Sep 24
MolDesignBench: Evaluating LLM-based Agent for Scenario-grounded Molecular Design
MolDesignBench is a new benchmark for evaluating large language model (LLM)-based agents in scenario‑grounded molecular design. It contains 2,000 generation and optimization tasks that blend implicit narrative requirements with explicit property and functional‑group constraints, including infeasible cases, and require the use of 17 specialized chemistry tools. Experiments with leading LLMs show low success rates (best ~43%) and highlight failures in implicit‑constraint reasoning, infeasibility detection, and tool usage, underscoring the benchmark’s role in identifying key bottlenecks for future research.
arXiv Machine Learning
Jun 11
My Chemical Harness: Evolutionary Molecular Design over Synthetic Pathways with Large Language Model Agents
arXiv:2606. 11256v1 Announce Type: cross Abstract: Designing molecules with target properties is most useful when candidate structures are accompanied by feasible synthetic routes.
arXiv AI
Aug 10
CAi Copilot: Reducing Operational Workload in Molecular Design through Intent-Driven Agentic Workflows
arXiv:2608. 06961v1 Announce Type: new Abstract: Early-stage molecular design is an iterative process, not just a task of generating molecules.