CliffSplit exposes at least 15% higher errors in cliff-heavy regions of QM9 while CliffLoss narrows the cliff-to-smooth error gap by up to 30% and improves overall MAE by 9.7% across several molecular tasks and backbones.
Collaborative expert llms guided multi-objective molecular optimization
4 Pith papers cite this work. Polarity classification is still indexing.
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background 2representative citing papers
MolDeTox is a new benchmark that shows fragment-level stepwise editing by LLMs and VLMs improves structural validity and detoxification quality over prior toxicity-focused evaluations.
Mol-Debate applies multi-agent debate in an iterative loop with perspective orchestration to achieve state-of-the-art text-guided molecular design, scoring 59.82% exact match on ChEBI-20 and 50.52% weighted success on S2-Bench.
A new method decomposes property differences between weakly related molecules into minimal chemical edits to train a directional evaluator that guides multi-step optimization with less oracle querying.
citing papers explorer
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When Molecular Similarity Works: Property Cliffs Reveal Hidden Errors
CliffSplit exposes at least 15% higher errors in cliff-heavy regions of QM9 while CliffLoss narrows the cliff-to-smooth error gap by up to 30% and improves overall MAE by 9.7% across several molecular tasks and backbones.
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MolDeTox: Evaluating Language Model's Stepwise Fragment Editing for Molecular Detoxification
MolDeTox is a new benchmark that shows fragment-level stepwise editing by LLMs and VLMs improves structural validity and detoxification quality over prior toxicity-focused evaluations.
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Mol-Debate: Multi-Agent Debate Improves Structural Reasoning in Molecular Design
Mol-Debate applies multi-agent debate in an iterative loop with perspective orchestration to achieve state-of-the-art text-guided molecular design, scoring 59.82% exact match on ChEBI-20 and 50.52% weighted success on S2-Bench.
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From Single-Step Edit Response to Multi-Step Molecular Optimization
A new method decomposes property differences between weakly related molecules into minimal chemical edits to train a directional evaluator that guides multi-step optimization with less oracle querying.