Hugging Face Trending Papers
Latent JEPA: Abstract Future Prediction for Latent Reasoning in Chemistry
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arXiv Machine Learning
1d ago
Latent JEPA: Abstract Future Prediction for Latent Reasoning in Chemistry
Latent JEPA is a new framework that trains continuous latent thoughts to anticipate informative aspects of future solutions in chemical reasoning, without verbalizing every intermediate step. It combines autoregressive learning with joint-embedding prediction of one or more future views, using textual and molecular prediction objectives that link latent thoughts to subsequent reasoning and molecular outcomes. Experiments on ChemCoTBench demonstrate improvements in molecular optimization, editing, and reaction metrics, and representation analyses show that future prediction makes latent thoughts more informative about molecular outcomes and better aligned with chemical structure.
arXiv AI
Jun 3
LatentChem: From Textual CoT to Latent Thinking in Chemical Reasoning
arXiv:2602. 07075v5 Announce Type: replace-cross Abstract: Current chemical large language models (LLMs) predominantly rely on explicit Chain-of-Thought (CoT) to solve complex reasoning problems.
arXiv Machine Learning
Sep 17
A Multitask Large Reasoning Model for Molecular Science
The paper introduces a multitask large reasoning model for molecular science that incorporates chemical knowledge via a multispecialist architecture, chain-of-thought supervision, and molecule-informed reinforcement learning. It coordinates prediction and inference specialists across ten molecular tasks—including description, generation, nomenclature translation, property prediction, and reaction prediction—using task-conditioned routing. The model surpasses more than 20 general-purpose and molecular large language models, improving aggregate performance by 50.3% and outperforming leading multitask baselines on most tasks, while maintaining interpretable chemical inference and demonstrating a workflow for CNS candidate generation and retrosynthetic planning.
arXiv AI
Jun 16
Retro-Expert: Collaborative Reasoning for Interpretable Retrosynthesis
arXiv:2508. 10967v3 Announce Type: replace-cross Abstract: Retrosynthesis prediction aims to infer the reactant molecules based on a given product molecule, which is a fundamental task in chemical synthesis.
Hugging Face Trending Papers
Aug 13
Localize, Then Reason: Visual Latent Structural Reasoning for Molecular Properties and Edits
Local chemical perception and property reasoning are both essential for understanding how molecular structure determines properties. Current LLM-based chemical reasoning methods either receive SMILES/molecular images together with descriptions of local motifs, or reason directly from molecular images.
arXiv Machine Learning
Jul 27
LatentFlow: Visual Analytics for Latent Space Analysis in Molecular Graph Neural Networks
arXiv:2607. 21941v1 Announce Type: new Abstract: Chemists and materials scientists increasingly use machine learning models, such as graph neural networks (GNNs), to predict properties of molecules and the outcomes of their reactions.