Smiles
PulseAugur coverage of Smiles — every cluster mentioning Smiles across labs, papers, and developer communities, ranked by signal.
4 day(s) with sentiment data
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GraphNOSE: New Graph Transformer Predicts Olfactory Qualities
Researchers have developed GraphNOSE, an open-source graph transformer framework designed to predict olfactory qualities from molecular structures. This new model demonstrates superior performance compared to existing l…
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Frontier LLMs show widespread verbatim retrieval of molecular data, study finds
A new study published on arXiv investigates the phenomenon of "molecular déjà vu" in frontier language models, where models appear to retrieve published molecular property values verbatim rather than predicting them. Th…
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New method uses probabilistic model checking for AI sequence models
Researchers have developed a new pipeline that uses probabilistic model checking to analyze autoregressive neural sequence models, addressing limitations of traditional test-set accuracy. This method quantifies the prob…
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AI uses language to guide crystal and molecular structure generation
Two new research papers introduce novel methods for structure generation using language-informed flow matching. The first, TFMat, uses structured text to guide crystal structure generation, improving match rates and ali…
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New agentic LLM S3C-LLM enhances molecular structure elucidation
Researchers have developed S3C-LLM, a novel agentic language model designed for spectrum-to-structure elucidation in molecular analysis. Unlike previous methods that directly convert spectra to SMILES, S3C-LLM mimics th…
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LLM-powered framework enhances molecular inverse design
Researchers have developed a closed-loop framework called \"method\" for molecular inverse design, which uses a large language model (LLM) to reason over task instructions, optimization history, and oracle feedback. Thi…
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VERDICT system enhances chemical structure recognition accuracy
Researchers have developed a new system called VERDICT that improves the accuracy of Optical Chemical Structure Recognition (OCSR). VERDICT utilizes agreement among multiple recognizers, outperforming pixel-space verifi…
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New VLSR Framework Enhances LLM Molecular Reasoning with Localization
Researchers have developed Visual Latent Structural Reasoning (VLSR), a new framework designed to improve how large language models (LLMs) understand molecular structures and predict their properties. Unlike previous me…
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New molecular LLM uses substructure rationale for improved property prediction
Researchers have developed MR-MoL, a novel molecular large language model (LLM) designed for property prediction in drug discovery. Unlike existing models that represent molecules implicitly, MR-MoL explicitly incorpora…
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MolBioKG system grounds unregistered molecules in biomedical knowledge graphs
Researchers have developed MolBioKG, a novel two-layer system designed to connect unregistered molecules to biomedical knowledge graphs. This system addresses the challenge of 'out-of-graph molecules' by using multi-res…
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MinerU.Chem system achieves 93% accuracy in chemical structure recognition
A new system called MinerU.Chem has been developed to extract chemical structures and reactions from organic chemistry documents, converting them into machine-readable data. This system, integrated into the MinerU platf…
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New model CheMatE unifies chemical structures and natural language
Researchers have developed CheMatE, a new embedding model designed to jointly represent chemical structures (SMILES) and natural language within a unified space. Built on a ModernBERT backbone, CheMatE employs a two-sta…
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New SIGMA objective improves molecular autoregressive models
Researchers have developed SIGMA, a novel objective for autoregressive molecular models that improves their ability to assign probabilities to molecules regardless of their serialization format. This method uses a dense…
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New generative model InVirtuoGen advances fragment-based drug discovery
Researchers have developed InVirtuoGen, a novel discrete flow generative model designed for fragment-based drug discovery. This model shifts the generation paradigm from completion to refinement, allowing for more effec…
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New Python library bridges molecular ML and scikit-learn
A new Python library called scikit-fingerprints has been released, designed to integrate molecular machine learning functionalities with the scikit-learn ecosystem. This library, built upon RDKit, provides a unified int…
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New Q-Steer method boosts molecular optimization for AI language models
Researchers have introduced Q-Steer, a novel method designed to enhance molecular policy optimization for language models. This technique addresses the challenge of delayed feedback in molecular generation by estimating…
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OLEDLM: New Language Model for OLED Molecular Design
Researchers have developed OLEDLM, a novel language model specifically designed for the design of organic light-emitting diode (OLED) molecules. This model utilizes a LLaMA-style transformer architecture as a foundation…
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S1-Omni model unifies scientific AI tasks, outperforms GPT-5.5 and Gemini-3.1 Pro
Researchers have introduced S1-Omni, a novel unified multimodal reasoning model designed to advance AI for Science (AI4S). This model addresses the fragmentation in current AI4S approaches by integrating the joint model…
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New framework MolBasic enhances LLMs' molecular understanding via SMILES-Graph translation
Researchers have introduced MolBasic, a new framework designed to enhance the molecular understanding capabilities of large language models (LLMs). This approach addresses the issue of LLMs failing to reliably capture m…
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New neural network fuses 3D geometry, topology, and physics for molecular prediction
Researchers have developed a novel Tri-Branch Modular Fusion Neural Network designed to improve molecular property prediction. This framework integrates three distinct data modalities: 3D spatial geometry using SchNet, …