From the 2 of 42 linked papers with an AI index.
18 citations · 25 across the 14 of their papers we have counts for
15 papers · 1 filter
Bi-semantic Chemical Embedder for Joint Representation Learning of SMILES and Natural Language
David Ming Segura, Jeremy Goumaz, Joshua W. Sin +3
Transformer models have revolutionized natural language processing (NLP), and text-based molecular representations like SMILES have successfully extended these architectures to che…
Sample Efficient Generative Optimization for Molecular Design
Sarina Kopf, Cristina Nevado, Philippe Schwaller
The paper proposes SEGO, a Bayesian optimization framework that steers a generative model to propose molecules, achieving strong molecular design performance with far fewer expensi…
Teaching Language Models Mechanistic Explainability Through MechSMILES
Théo A. Neukomm, Zlatko JonÄev, Philippe Schwaller
Chemical reaction mechanisms are the foundation of how chemists evaluate reactivity and feasibility, yet current Computer-Assisted Synthesis Planning (CASP) systems operate without…
Humanity's Last Exam
Long Phan, Alice Gatti, Ziwen Han +1144
Benchmarks are important tools for tracking the rapid advancements in large language model (LLM) capabilities. However, benchmarks are not keeping pace in difficulty: LLMs now achi…
MiST: Understanding the Role of Mid-Stage Scientific Training in Developing Chemical Reasoning Models
Andres M Bran, Tong Xie, Shai Pranesh +9
Large Language Models can develop reasoning capabilities through online fine-tuning with rule-based rewards. However, recent studies reveal a critical constraint: reinforcement lea…
Large language models as uncertainty-calibrated optimizers for experimental discovery
Bojana RankoviÄ, Ryan-Rhys Griffiths, Philippe Schwaller
Scientific discovery increasingly depends on efficient experimental optimization to navigate vast design spaces under time and resource constraints. Traditional approaches often re…