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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FragmentNet: Adaptive Graph Fragmentation for Graph-to-Sequence Molecular Representation Learning cites this paper.

FragmentNet: Adaptive Graph Fragmentation for Graph-to-Sequence Molecular Representation Learning ChemBERTa: Large-Scale Self-Supervised Pretraining for Molecular Property Prediction

Reference 1

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Docking-Aware Attention: Dynamic Protein Representations through Molecular Context Integration cites this paper.

Docking-Aware Attention: Dynamic Protein Representations through Molecular Context Integration ChemBERTa: Large-Scale Self-Supervised Pretraining for Molecular Property Prediction

Reference 5

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Graph-based Molecular In-context Learning Grounded on Morgan Fingerprints cites this paper.

Graph-based Molecular In-context Learning Grounded on Morgan Fingerprints ChemBERTa: Large-Scale Self-Supervised Pretraining for Molecular Property Prediction

Reference 2020

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Automatic Annotation Augmentation Boosts Translation between Molecules and Natural Language cites this paper.

Automatic Annotation Augmentation Boosts Translation between Molecules and Natural Language ChemBERTa: Large-Scale Self-Supervised Pretraining for Molecular Property Prediction

Reference 2020

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Transformers in Protein: A Survey cites this paper.

Transformers in Protein: A Survey ChemBERTa: Large-Scale Self-Supervised Pretraining for Molecular Property Prediction

Reference 65

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Uncovering Bottlenecks and Optimizing Scientific Lab Workflows with Cycle Time Reduction Agents cites this paper.

Uncovering Bottlenecks and Optimizing Scientific Lab Workflows with Cycle Time Reduction Agents ChemBERTa: Large-Scale Self-Supervised Pretraining for Molecular Property Prediction

Reference 2

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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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Chunk Twice, Embed Once: A Systematic Study of Segmentation and Representation Trade-offs in Chemistry-Aware Retrieval-Augmented Generation cites this paper.

Chunk Twice, Embed Once: A Systematic Study of Segmentation and Representation Trade-offs in Chemistry-Aware Retrieval-Augmented Generation ChemBERTa: Large-Scale Self-Supervised Pretraining for Molecular Property Prediction

Reference 69

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OmniESI: A unified framework for enzyme-substrate interaction prediction with progressive conditional deep learning cites this paper.

OmniESI: A unified framework for enzyme-substrate interaction prediction with progressive conditional deep learning ChemBERTa: Large-Scale Self-Supervised Pretraining for Molecular Property Prediction

Reference 28

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A Survey of AI for Materials Science: Foundation Models, LLM Agents, Datasets, and Tools cites this paper.

A Survey of AI for Materials Science: Foundation Models, LLM Agents, Datasets, and Tools ChemBERTa: Large-Scale Self-Supervised Pretraining for Molecular Property Prediction

Reference 100

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DeepRetro: Retrosynthetic Pathway Discovery using Iterative LLM Reasoning cites this paper.

DeepRetro: Retrosynthetic Pathway Discovery using Iterative LLM Reasoning ChemBERTa: Large-Scale Self-Supervised Pretraining for Molecular Property Prediction

Reference 35

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MODA: A Unified 3D Diffusion Framework for Multi-Task Target-Aware Molecular Generation cites this paper.

MODA: A Unified 3D Diffusion Framework for Multi-Task Target-Aware Molecular Generation ChemBERTa: Large-Scale Self-Supervised Pretraining for Molecular Property Prediction

Reference 29

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A Foundation Model for Material Fracture Prediction cites this paper.

A Foundation Model for Material Fracture Prediction ChemBERTa: Large-Scale Self-Supervised Pretraining for Molecular Property Prediction

Reference 27

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Large Language Models Transform Organic Synthesis From Reaction Prediction to Automation cites this paper.

Large Language Models Transform Organic Synthesis From Reaction Prediction to Automation ChemBERTa: Large-Scale Self-Supervised Pretraining for Molecular Property Prediction

Reference 39

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Predicting Drug-Drug Interactions Using Heterogeneous Graph Neural Networks: HGNN-DDI cites this paper.

Predicting Drug-Drug Interactions Using Heterogeneous Graph Neural Networks: HGNN-DDI ChemBERTa: Large-Scale Self-Supervised Pretraining for Molecular Property Prediction

Reference 14

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Valid Property-Enhanced Contrastive Learning for Targeted Optimization & Resampling for Novel Drug Design cites this paper.

Valid Property-Enhanced Contrastive Learning for Targeted Optimization & Resampling for Novel Drug Design ChemBERTa: Large-Scale Self-Supervised Pretraining for Molecular Property Prediction

Reference 62

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Towards a Physics Foundation Model cites this paper.

Towards a Physics Foundation Model ChemBERTa: Large-Scale Self-Supervised Pretraining for Molecular Property Prediction

Reference 9

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Adaptive Minds: Empowering Agents with LoRA-as-Tools cites this paper.

Adaptive Minds: Empowering Agents with LoRA-as-Tools 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

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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

Resolution: verified exact; arxiv_id, observed 2026-05-10T14:15:29.087701Z

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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

Resolution: verified exact; arxiv_id, observed 2026-05-11T12:21:05.161131Z

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Observation f62a042d-4922-495c-8415-e4b30f946f23 · inbound

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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Observation 9b677c4e-9e30-487a-8078-f58ae6f491fb · inbound

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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Observation 31d01993-c84b-47cc-8cf9-6a965b8a6070 · inbound

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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Observation a1de2f68-0848-4e69-b942-f4bbe8c18cda · inbound

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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Observation 0b92ab7b-f96c-4b69-a3db-c17c4a57ecb8 · inbound

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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Observation 55a342f0-90ab-47e7-a779-b197298d73e7 · inbound

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

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Observation 5e00b309-9d2e-4aef-a264-6113d8a61947 · inbound

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

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Observation ed5ac803-a367-4057-8373-a005e03408e5 · inbound

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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Observation 746ab109-a125-4391-b33b-7e55c46899eb · inbound

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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Observation 465d15f9-a395-4df9-b2c8-68d24adc6130 · inbound

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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Observation d37fc5af-fe83-4e85-a6f5-856e787487b1 · inbound

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

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Observation d7d08f91-834c-4184-89ef-c1a32f4a359f · inbound

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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Observation cb5f82c4-c20d-40af-80a4-0eae626966c0 · inbound

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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Observation 27fc41f3-28b9-4722-88dc-9dd0b730bba5 · inbound

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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Observation d30a2ed4-9474-48ad-aff4-25a8b67da997 · inbound

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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Observation a8aab07c-0ebe-49ab-97c0-3af518ac75cf · inbound

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

Resolution: verified exact; arxiv_id, observed 2026-07-04T00:09:14.031671Z

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Observation 0beb2121-f24c-402a-8c45-348c1e5453a1 · inbound

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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Observation 98e78bc2-1d88-4b81-863d-16a9dd7ab1d1 · inbound

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

Resolution: verified exact; arxiv_id, observed 2026-07-04T09:59:45.791091Z

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Observation 144364f9-2c4f-4758-b2fc-cd373d4f4e31 · inbound

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

Resolution: verified exact; arxiv_id, observed 2026-07-04T09:49:44.741796Z

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Observation d9c14e0c-1be4-4b19-a8ff-f69296b700ca · inbound

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

Resolution: verified exact; arxiv_id, observed 2026-06-30T07:34:21.547540Z

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Observation 9614f837-fb01-4273-8333-eb380e47ac58 · inbound

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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Observation 06ba9ae0-a941-4787-8afb-cf44a0369c13 · inbound

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

Resolution: verified exact; arxiv_id, observed 2026-07-03T17:18:43.065942Z

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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

Resolution: verified exact; local_arxiv, observed 2026-07-11T02:57:47.351709Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 4e3c232d-2942-44ef-8295-1b43c68ef264 · inbound

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

Resolution: verified exact; local_arxiv, observed 2026-07-11T02:07:43.444303Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 429126b3-9497-4c5c-b132-890d30dab33d · inbound

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

Resolution: unresolved; no resolver link, observed 2026-08-02T06:23:58.264750Z

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Observation 6a9bf859-3c94-42c2-9418-349d795a6edc · inbound

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

Resolution: unresolved; no resolver link, observed 2026-08-01T17:38:00.865291Z

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Observation d502ff06-32b3-4bb3-9bc2-f8334b22f5a5 · inbound

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

Resolution: unresolved; no resolver link, observed 2026-08-01T18:39:13.925232Z

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Observation 593dc983-43f6-4cd3-9796-e58ce5e7ab2c · inbound

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

Resolution: unresolved; no resolver link, observed 2026-08-01T10:35:20.125749Z

Source-reported events for the cited work

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Observation bd2119b4-b168-4e51-86f9-04b225e04c06 · inbound

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

Reference 7

Resolution: unresolved; no resolver link, observed 2026-07-30T17:47:26.800296Z

Source-reported events for the cited work

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Observation 052a68bc-b7ab-4127-a2b1-6086d5d31119 · inbound

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

Resolution: unresolved; no resolver link, observed 2026-08-01T03:57:15.634404Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9cbf7b27-3dd6-414c-ae4d-cc9a5aa7f654 · inbound

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

Resolution: unresolved; no resolver link, observed 2026-07-31T00:54:10.974480Z

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Observation f9098571-9831-4786-bcd7-626cf802d883 · inbound

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

Resolution: unresolved; no resolver link, observed 2026-07-31T18:32:14.122104Z

Source-reported events for the cited work

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Observation 2fa0c340-1ba6-4b0a-bc97-eaa4484bedbd · inbound

ED-DiT: Physics-Guided Diffusion Pretraining for Transferable Molecular Representations from Electron Density cites this paper.

ED-DiT: Physics-Guided Diffusion Pretraining for Transferable Molecular Representations from Electron Density ChemBERTa: Large-Scale Self-Supervised Pretraining for Molecular Property Prediction

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-05T22:26:38.418381Z

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