ChemBERTa: Large-Scale Self-Supervised Pretraining for Molecular Property Prediction | Paper Citation Record

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ChemCrow: Augmenting large-language models with chemistry tools cites this paper.

ChemCrow: Augmenting large-language models with chemistry tools ChemBERTa: Large-Scale Self-Supervised Pretraining for Molecular Property Prediction

Reference 30

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Machine Learning Based Prediction of Proton Conductivity in Metal-Organic Frameworks cites this paper.

Machine Learning Based Prediction of Proton Conductivity in Metal-Organic Frameworks ChemBERTa: Large-Scale Self-Supervised Pretraining for Molecular Property Prediction

Reference 4

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Regression with Large Language Models for Materials and Molecular Property Prediction cites this paper.

Regression with Large Language Models for Materials and Molecular Property Prediction ChemBERTa: Large-Scale Self-Supervised Pretraining for Molecular Property Prediction

Reference 1

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SmellNet: A Large-scale Dataset for Real-world Smell Recognition cites this paper.

SmellNet: A Large-scale Dataset for Real-world Smell Recognition ChemBERTa: Large-Scale Self-Supervised Pretraining for Molecular Property Prediction

Reference 9

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Foundation Models for Discovery and Exploration in Chemical Space cites this paper.

Foundation Models for Discovery and Exploration in Chemical Space ChemBERTa: Large-Scale Self-Supervised Pretraining for Molecular Property Prediction

Reference 107

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FlexMS is a flexible framework for benchmarking deep learning-based mass spectrum prediction tools in metabolomics cites this paper.

FlexMS is a flexible framework for benchmarking deep learning-based mass spectrum prediction tools in metabolomics ChemBERTa: Large-Scale Self-Supervised Pretraining for Molecular Property Prediction

Reference 9

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SIGMA: Semantic Identifier Grouping for Molecular Autoregression cites this paper.

SIGMA: Semantic Identifier Grouping for Molecular Autoregression ChemBERTa: Large-Scale Self-Supervised Pretraining for Molecular Property Prediction

Reference 2023

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NOSE: Neural Olfactory-Semantic Embedding with Tri-Modal Orthogonal Contrastive Learning cites this paper.

NOSE: Neural Olfactory-Semantic Embedding with Tri-Modal Orthogonal Contrastive Learning ChemBERTa: Large-Scale Self-Supervised Pretraining for Molecular Property Prediction

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-05-11T09:16:00.936912Z

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Lit2Vec: A Reproducible Workflow for Building a Legally Screened Chemistry Corpus from S2ORC for Downstream Retrieval and Text Mining cites this paper.

Lit2Vec: A Reproducible Workflow for Building a Legally Screened Chemistry Corpus from S2ORC for Downstream Retrieval and Text Mining ChemBERTa: Large-Scale Self-Supervised Pretraining for Molecular Property Prediction

Reference 12

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When Active Learning Falls Short: An Empirical Study on Chemical Reaction Extraction cites this paper.

When Active Learning Falls Short: An Empirical Study on Chemical Reaction Extraction ChemBERTa: Large-Scale Self-Supervised Pretraining for Molecular Property Prediction

Reference 38

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Do Larger Models Really Win in Drug Discovery? A Benchmark Assessment of Model Scaling in AI-Driven Molecular Property and Activity Prediction cites this paper.

Do Larger Models Really Win in Drug Discovery? A Benchmark Assessment of Model Scaling in AI-Driven Molecular Property and Activity Prediction ChemBERTa: Large-Scale Self-Supervised Pretraining for Molecular Property Prediction

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-05-12T09:16:27.780711Z

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Do Larger Models Really Win in Drug Discovery? A Benchmark Assessment of Model Scaling in AI-Driven Molecular Property and Activity Prediction cites this paper.

Do Larger Models Really Win in Drug Discovery? A Benchmark Assessment of Model Scaling in AI-Driven Molecular Property and Activity Prediction ChemBERTa: Large-Scale Self-Supervised Pretraining for Molecular Property Prediction

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-05-19T17:42:42.024902Z

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SPADE: Faster Drug Discovery by Learning from Sparse Data cites this paper.

SPADE: Faster Drug Discovery by Learning from Sparse Data ChemBERTa: Large-Scale Self-Supervised Pretraining for Molecular Property Prediction

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-05-09T06:50:41.839056Z

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Molecules Meet Language: Confound-Aware Representation Learning and Chemical Property Steering in Transformer-VAE Latent Spaces cites this paper.

Molecules Meet Language: Confound-Aware Representation Learning and Chemical Property Steering in Transformer-VAE Latent Spaces ChemBERTa: Large-Scale Self-Supervised Pretraining for Molecular Property Prediction

Reference 12

Resolution: verified exact; arxiv_id, observed 2026-05-11T19:01:13.212028Z

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Molecules Meet Language: Confound-Aware Representation Learning and Chemical Property Steering in Transformer-VAE Latent Spaces cites this paper.

Molecules Meet Language: Confound-Aware Representation Learning and Chemical Property Steering in Transformer-VAE Latent Spaces ChemBERTa: Large-Scale Self-Supervised Pretraining for Molecular Property Prediction

Reference 13

Resolution: verified exact; arxiv_id, observed 2026-05-08T21:34:12.726846Z

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Can LLMs Predict Polymer Physics Just by Reading Synthesis and Processing Prose? cites this paper.

Can LLMs Predict Polymer Physics Just by Reading Synthesis and Processing Prose? ChemBERTa: Large-Scale Self-Supervised Pretraining for Molecular Property Prediction

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-05-12T01:46:13.534345Z

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From Syntax to Semantics: Unveiling the Emergence of Chirality in SMILES Translation Models cites this paper.

From Syntax to Semantics: Unveiling the Emergence of Chirality in SMILES Translation Models ChemBERTa: Large-Scale Self-Supervised Pretraining for Molecular Property Prediction

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-05-12T04:06:24.643095Z

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FORGE: Fragment-Oriented Ranking and Generation for Context-Aware Molecular Optimization cites this paper.

FORGE: Fragment-Oriented Ranking and Generation for Context-Aware Molecular Optimization ChemBERTa: Large-Scale Self-Supervised Pretraining for Molecular Property Prediction

Reference 22

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Chem-GMNet: A Sphere-Native Geometric Transformer for Molecular Property Prediction cites this paper.

Chem-GMNet: A Sphere-Native Geometric Transformer for Molecular Property Prediction ChemBERTa: Large-Scale Self-Supervised Pretraining for Molecular Property Prediction

Reference 6

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Training distribution determines the ceiling of drug-blind cancer sensitivity prediction cites this paper.

Training distribution determines the ceiling of drug-blind cancer sensitivity prediction ChemBERTa: Large-Scale Self-Supervised Pretraining for Molecular Property Prediction

Reference 8

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AutoScientists: Self-Organizing Agent Teams for Long-Running Scientific Experimentation cites this paper.

AutoScientists: Self-Organizing Agent Teams for Long-Running Scientific Experimentation ChemBERTa: Large-Scale Self-Supervised Pretraining for Molecular Property Prediction

Reference 65

Resolution: verified exact; arxiv_id, observed 2026-06-29T12:43:25.676179Z

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When Tabular Foundation Models Transfer Across Modalities: A Systematic Evaluation Across 95 Datasets, 7 Modalities, and Two Regimes cites this paper.

When Tabular Foundation Models Transfer Across Modalities: A Systematic Evaluation Across 95 Datasets, 7 Modalities, and Two Regimes ChemBERTa: Large-Scale Self-Supervised Pretraining for Molecular Property Prediction

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-07-01T22:16:16.771174Z

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MolE-RAG: Molecular Structure-Enhanced Retrieval-Augmented Generation for Chemistry cites this paper.

MolE-RAG: Molecular Structure-Enhanced Retrieval-Augmented Generation for Chemistry ChemBERTa: Large-Scale Self-Supervised Pretraining for Molecular Property Prediction

Reference 46

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GLACIER: A Multimodal Student-Teacher Foundation Model for Molecular Property Prediction cites this paper.

GLACIER: A Multimodal Student-Teacher Foundation Model for Molecular Property Prediction ChemBERTa: Large-Scale Self-Supervised Pretraining for Molecular Property Prediction

Reference 12

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Augmenting Molecular Language Models with Local $n$-gram Memory cites this paper.

Augmenting Molecular Language Models with Local $n$-gram Memory ChemBERTa: Large-Scale Self-Supervised Pretraining for Molecular Property Prediction

Reference 50

Resolution: verified exact; arxiv_id, observed 2026-07-03T10:37:56.670213Z

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Contextualizing Biological Language Models across Modalities via Logit-Space Contrastive Alignment cites this paper.

Contextualizing Biological Language Models across Modalities via Logit-Space Contrastive Alignment ChemBERTa: Large-Scale Self-Supervised Pretraining for Molecular Property Prediction

Reference 43

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Contextualizing Biological Language Models across Modalities via Logit-Space Contrastive Alignment cites this paper.

Contextualizing Biological Language Models across Modalities via Logit-Space Contrastive Alignment ChemBERTa: Large-Scale Self-Supervised Pretraining for Molecular Property Prediction

Reference 44

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A large-scale foundation model enables simulation-to-real adaptation for nuclear magnetic resonance-based molecular structure analysis cites this paper.

A large-scale foundation model enables simulation-to-real adaptation for nuclear magnetic resonance-based molecular structure analysis ChemBERTa: Large-Scale Self-Supervised Pretraining for Molecular Property Prediction

Reference 58

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Observation 5a4e5e17-b837-40b4-9312-193e9f024126 · inbound

Closed-loop Auto Research for Molecular Property Prediction: Discovering and Certifying Generalizable Improvements cites this paper.

Closed-loop Auto Research for Molecular Property Prediction: Discovering and Certifying Generalizable Improvements ChemBERTa: Large-Scale Self-Supervised Pretraining for Molecular Property Prediction

Reference 8

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What Does a Chemical Language Model Know About Molecules? cites this paper.

What Does a Chemical Language Model Know About Molecules? ChemBERTa: Large-Scale Self-Supervised Pretraining for Molecular Property Prediction

Reference 6

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Towards Generalizable and Evidential Nuclear Magnetic Resonance-Based Molecular Structure Elucidation via Large Language Model Agent cites this paper.

Towards Generalizable and Evidential Nuclear Magnetic Resonance-Based Molecular Structure Elucidation via Large Language Model Agent ChemBERTa: Large-Scale Self-Supervised Pretraining for Molecular Property Prediction

Reference 4

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Modeling Cell-Cycle-Aware Single-Cell Drug Perturbation Responses cites this paper.

Modeling Cell-Cycle-Aware Single-Cell Drug Perturbation Responses ChemBERTa: Large-Scale Self-Supervised Pretraining for Molecular Property Prediction

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-07-01T12:35:44.093689Z

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Probing Chemical Language Models: Effects of Pre-training and Fine-tuning cites this paper.

Probing Chemical Language Models: Effects of Pre-training and Fine-tuning ChemBERTa: Large-Scale Self-Supervised Pretraining for Molecular Property Prediction

Reference 1

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Observation ff31abc1-a090-47b4-8f6c-20553f5e6792 · inbound

Multimodal Molecular Representation Learning with Graph Neural Networks, Deep & Cross Networks, and SMILES Embeddings cites this paper.

Multimodal Molecular Representation Learning with Graph Neural Networks, Deep & Cross Networks, and SMILES Embeddings ChemBERTa: Large-Scale Self-Supervised Pretraining for Molecular Property Prediction

Reference 15

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A Quiet Failure in Calibrated Virtual Screening: Marginal Conformal Prediction Under-Covers the Minority Class, and a Class-Conditional Fix Recovers It cites this paper.

A Quiet Failure in Calibrated Virtual Screening: Marginal Conformal Prediction Under-Covers the Minority Class, and a Class-Conditional Fix Recovers It ChemBERTa: Large-Scale Self-Supervised Pretraining for Molecular Property Prediction

Reference 11

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Improving Molecular Property Prediction in Small Language Models Using Graph-based Tools cites this paper.

Improving Molecular Property Prediction in Small Language Models Using Graph-based Tools ChemBERTa: Large-Scale Self-Supervised Pretraining for Molecular Property Prediction

Reference 24

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Trustworthy Protein-Ligand Binding Affinity Prediction via Reliability-Aware Multi-Engine Fusion cites this paper.

Trustworthy Protein-Ligand Binding Affinity Prediction via Reliability-Aware Multi-Engine Fusion ChemBERTa: Large-Scale Self-Supervised Pretraining for Molecular Property Prediction

Reference 8

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ChemHyperMag: Physics-informed magnetic hypergraph learning improves molecular ADMET prediction cites this paper.

ChemHyperMag: Physics-informed magnetic hypergraph learning improves molecular ADMET prediction ChemBERTa: Large-Scale Self-Supervised Pretraining for Molecular Property Prediction

Reference 66

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OLEDLM: A Unified Language Model for OLED Molecular Design cites this paper.

OLEDLM: A Unified Language Model for OLED Molecular Design ChemBERTa: Large-Scale Self-Supervised Pretraining for Molecular Property Prediction

Reference 13

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MS-GPT: Rethinking MS/MS De Novo Structure Elucidation as Spectrum-Induced Posterior Querying of a Molecule-Language Model cites this paper.

MS-GPT: Rethinking MS/MS De Novo Structure Elucidation as Spectrum-Induced Posterior Querying of a Molecule-Language Model ChemBERTa: Large-Scale Self-Supervised Pretraining for Molecular Property Prediction

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Beyond Predictive Accuracy: A Reliability-Aware Audit of Molecular Representations for Human Olfaction cites this paper.

Beyond Predictive Accuracy: A Reliability-Aware Audit of Molecular Representations for Human Olfaction ChemBERTa: Large-Scale Self-Supervised Pretraining for Molecular Property Prediction

Reference 7

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Persistent Manifold Learning of Protein Properties cites this paper.

Persistent Manifold Learning of Protein Properties ChemBERTa: Large-Scale Self-Supervised Pretraining for Molecular Property Prediction

Reference 8

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Chem World: A Large-Scale Benchmark and Physics-Informed Framework for Trustworthy Chemical Property Prediction cites this paper.

Chem World: A Large-Scale Benchmark and Physics-Informed Framework for Trustworthy Chemical Property Prediction ChemBERTa: Large-Scale Self-Supervised Pretraining for Molecular Property Prediction

Reference 9

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