{"total":27,"rows":[{"id":"2310.10773","title":"Gotta be SAFE: A New Framework for Molecular Design","created":"2023-10-16","cited_by_count":48,"area":null},{"id":"2310.02902","title":"Searching for High-Value Molecules Using Reinforcement Learning and Transformers","created":"2023-10-04","cited_by_count":18,"area":null},{"id":"2301.01829","title":"t-SMILES: A Scalable Fragment-based Molecular Representation Framework for De Novo Molecule Generation","created":"2023-01-04","cited_by_count":14,"area":null},{"id":"2310.03030","title":"GPT-MolBERTa: GPT Molecular Features Language Model for molecular property prediction","created":"2023-09-20","cited_by_count":14,"area":null},{"id":"2307.11694","title":"SynerGPT: In-Context Learning for Personalized Drug Synergy Prediction and Drug Design","created":"2023-06-19","cited_by_count":13,"area":null},{"id":"2405.04912","title":"GP-MoLFormer: A Foundation Model For Molecular Generation","created":"2024-04-04","cited_by_count":11,"area":null},{"id":"2406.17295","title":"Less can be more for predicting properties with large language models","created":"2024-06-25","cited_by_count":11,"area":null},{"id":"2302.03620","title":"Recent advances in the Self-Referencing Embedding Strings (SELFIES) library","created":"2023-02-07","cited_by_count":8,"area":null},{"id":"2310.03253","title":"Molecule Design by Latent Prompt Transformer","created":"2023-10-05","cited_by_count":8,"area":null},{"id":"2505.12565","title":"mCLM: A Modular Chemical Language Model that Generates Functional and Makeable Molecules","created":"2025-05-18","cited_by_count":8,"area":null},{"id":"2411.01667","title":"GraphXForm: Graph transformer for computer-aided molecular design","created":"2024-11-03","cited_by_count":6,"area":null},{"id":"2509.23099","title":"How to Make Large Language Models Generate 100% Valid Molecules?","created":"2025-09-27","cited_by_count":4,"area":null},{"id":"2405.16041","title":"Explainable Molecular Property Prediction: Aligning Chemical Concepts with Predictions via Language Models","created":"2024-05-25","cited_by_count":3,"area":null},{"id":"2304.06337","title":"Computational modeling of semantic change","created":"2023-04-13","cited_by_count":2,"area":null},{"id":"2402.02164","title":"Hierarchical Structure Enhances the Convergence and Generalizability of Linear Molecular Representation","created":"2024-02-03","cited_by_count":1,"area":null},{"id":"2409.15600","title":"Polyatomic Complexes: A topologically-informed learning representation for atomistic systems","created":"2024-09-23","cited_by_count":1,"area":null},{"id":"2604.16586","title":"A Systematic Survey and Benchmark of Deep Learning for Molecular Property Prediction in the Foundation Model Era","created":"2026-04-17","cited_by_count":1,"area":null},{"id":"2605.07693","title":"Toward Better Geometric Representations for Molecule Generative Models","created":"2026-05-08","cited_by_count":1,"area":null},{"id":"2402.17179","title":"Molecule Design by Latent Prompt Transformer","created":"2024-02-27","cited_by_count":0,"area":null},{"id":"2408.09106","title":"Fragment-Masked Diffusion for Molecular Optimization","created":"2024-08-17","cited_by_count":0,"area":null},{"id":"2410.08829","title":"Exploiting Latent Linearity in LLMs Improves Explainable Molecular Representation Learning","created":"2024-10-11","cited_by_count":0,"area":null},{"id":"2511.13758","title":"ChemFixer: Correcting Invalid Molecules to Unlock Previously Unseen Chemical Space","created":"2025-11-14","cited_by_count":0,"area":null},{"id":"2601.21964","title":"From Tokens to Blocks: A Block-Diffusion Perspective on Molecular Generation","created":"2026-01-29","cited_by_count":0,"area":null},{"id":"2604.03304","title":"Generative Chemical Language Models for Energetic Materials Discovery","created":"2026-03-30","cited_by_count":0,"area":null},{"id":"2606.30170","title":"Beyond Drug Discovery: The Nanotechnology Molecular Optimization (NMO) Benchmark","created":"2026-06-29","cited_by_count":0,"area":null},{"id":"2610.02186","title":"Higher-Order Molecular Grammars for Generative and Foundation Models in Chemistry","created":"2026-10-01","cited_by_count":0,"area":null},{"id":"2610.18438","title":"STAMP as a topology-aware molecular language for fragment-level learning and editing","created":"2026-10-13","cited_by_count":0,"area":null}],"next_cursor":null}