Paper Citation Record · LEDGER

ChemBERTa-2: Towards Chemical Foundation Models

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 26 inbound Pith citation observations for arXiv:2209.01712.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2209.01712 v1

Coverage vector

measured 0 of 0 reference resolution

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measured 26 of 26 standing notices

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Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 26 of 26 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:27:37.612240Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-07-04T09:49:44.745385Z

Reference resolution

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External citation measurements

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Outbound references

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Pith citing papers

Observation 7f89c938-8373-4467-a5a5-164aa30c0864 · inbound

Leveraging neural network interatomic potentials for a foundation model of chemistry cites this paper.

Leveraging neural network interatomic potentials for a foundation model of chemistry ChemBERTa-2: Towards Chemical Foundation Models

Reference 36

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Observation c72b6e0a-b85d-4366-8db6-83fb7460264b · inbound

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

DeepRetro: Retrosynthetic Pathway Discovery using Iterative LLM Reasoning ChemBERTa-2: Towards Chemical Foundation Models

Reference 36

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Observation 08f9e5f0-6499-432f-8696-0f7bc5fe12fe · inbound

Predicting and generating antibiotics against future pathogens with ApexOracle cites this paper.

Predicting and generating antibiotics against future pathogens with ApexOracle ChemBERTa-2: Towards Chemical Foundation Models

Reference 25

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Observation 1be64774-e5fb-435e-86ce-d0ad41f86d23 · inbound

A Foundation Model for Material Fracture Prediction cites this paper.

A Foundation Model for Material Fracture Prediction ChemBERTa-2: Towards Chemical Foundation Models

Reference 20

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Observation 9313b98b-3299-4ffe-99be-7907c61dcbcb · inbound

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-2: Towards Chemical Foundation Models

Reference 78

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Observation f7b8f989-c8cb-40eb-88de-ae98e5b12fe6 · inbound

Thermodynamically consistent machine learning model for excess Gibbs energy cites this paper.

Thermodynamically consistent machine learning model for excess Gibbs energy ChemBERTa-2: Towards Chemical Foundation Models

Reference 30

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Observation b9b315c4-46a2-4608-95db-dc32937b4214 · inbound

MHA-RAG: Improving Efficiency, Accuracy, and Consistency by Encoding Exemplars as Soft Prompts cites this paper.

MHA-RAG: Improving Efficiency, Accuracy, and Consistency by Encoding Exemplars as Soft Prompts ChemBERTa-2: Towards Chemical Foundation Models

Reference 1

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Observation 4ca02074-b492-4a8a-b194-d9879d4ae7f9 · inbound

oMeBench: Towards Robust Benchmarking of LLMs in Organic Mechanism Elucidation and Reasoning cites this paper.

oMeBench: Towards Robust Benchmarking of LLMs in Organic Mechanism Elucidation and Reasoning ChemBERTa-2: Towards Chemical Foundation Models

Reference 4

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Observation 2102a122-471e-4bcf-8c73-ff2131b7b2cf · inbound

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

Foundation Models for Discovery and Exploration in Chemical Space ChemBERTa-2: Towards Chemical Foundation Models

Reference 144

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Observation aebeb27c-7c00-4a9e-b624-2e5f22277b6f · inbound

The Ray Tracing Sampler: Bayesian Sampling of Neural Networks for Everyone cites this paper.

The Ray Tracing Sampler: Bayesian Sampling of Neural Networks for Everyone ChemBERTa-2: Towards Chemical Foundation Models

Reference 3

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Observation 35202730-720f-4e91-86fb-7699ca87525b · inbound

Machine learning for smell: Ordinal odor strength prediction of molecular perfumery components cites this paper.

Machine learning for smell: Ordinal odor strength prediction of molecular perfumery components ChemBERTa-2: Towards Chemical Foundation Models

Reference 49

Resolution: verified exact; arxiv_id, observed 2026-05-21T18:34:17.981696Z

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

Observation f5a8756e-dccf-4ea1-86d9-8317e2c1db5f · inbound

Structure-Preserving Learning Improves Geometry Generalization in Neural PDEs cites this paper.

Structure-Preserving Learning Improves Geometry Generalization in Neural PDEs ChemBERTa-2: Towards Chemical Foundation Models

Reference 2019

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MultiPUFFIN: A Multimodal Domain-Constrained Foundation Model for Molecular Property Prediction of Small Molecules cites this paper.

MultiPUFFIN: A Multimodal Domain-Constrained Foundation Model for Molecular Property Prediction of Small Molecules ChemBERTa-2: Towards Chemical Foundation Models

Reference 16

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CVT Archives and Chemical Embedding Measures for Multi-Objective Quality Diversity in Molecular Design cites this paper.

CVT Archives and Chemical Embedding Measures for Multi-Objective Quality Diversity in Molecular Design ChemBERTa-2: Towards Chemical Foundation Models

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-05-10T23:15:50.467015Z

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Observation 9c715081-ebd3-4134-90a3-4b03bf2897f3 · inbound

A Systematic Survey and Benchmark of Deep Learning for Molecular Property Prediction in the Foundation Model Era cites this paper.

A Systematic Survey and Benchmark of Deep Learning for Molecular Property Prediction in the Foundation Model Era ChemBERTa-2: Towards Chemical Foundation Models

Reference 27

Resolution: verified exact; arxiv_id, observed 2026-05-10T08:43:01.460387Z

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Observation 0122a0d4-3632-4a4d-8a7e-444590592c7d · 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-2: Towards Chemical Foundation Models

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-05-12T09:16:27.737196Z

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Observation 1a4cb876-2f94-4209-be74-7c78f6c27e2e · 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-2: Towards Chemical Foundation Models

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-05-19T17:42:42.030611Z

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 472a3698-e2d0-41df-9a03-da14380620ce · inbound

Bolek: A Multimodal Language Model for Molecular Reasoning cites this paper.

Bolek: A Multimodal Language Model for Molecular Reasoning ChemBERTa-2: Towards Chemical Foundation Models

Reference 38

Resolution: verified exact; arxiv_id, observed 2026-05-11T16:36:10.051375Z

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Observation 1d15f216-6ea7-4bed-ba79-637fe6be94ad · 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-2: Towards Chemical Foundation Models

Reference 7

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Observation 48aa5b3b-ea3e-4e9f-9615-5157b03ae0dc · inbound

MSAlign: Aligning Molecule and Mass Spectra Foundation Models for Metabolite Identification cites this paper.

MSAlign: Aligning Molecule and Mass Spectra Foundation Models for Metabolite Identification ChemBERTa-2: Towards Chemical Foundation Models

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-05-20T07:48:07.423446Z

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

Observation ac3a9c4d-eaa0-4672-b327-bbb44c4fb73a · inbound

SciCore-Mol: Augmenting Large Language Models with Pluggable Molecular Cognition Modules cites this paper.

SciCore-Mol: Augmenting Large Language Models with Pluggable Molecular Cognition Modules ChemBERTa-2: Towards Chemical Foundation Models

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-05-22T05:31:07.765507Z

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Observation 18572fef-412c-45da-b9e9-656ea5490d05 · inbound

One Mask to Rule Them All: On Hidden Facts after Editing and How to Find Them cites this paper.

One Mask to Rule Them All: On Hidden Facts after Editing and How to Find Them ChemBERTa-2: Towards Chemical Foundation Models

Reference 1

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Observation 77051319-ad9e-4e45-b1c9-aa32669bf7a1 · inbound

The Biosecurity Blind Spot: Systematic Dual-use Detection in Open Science Infrastructure cites this paper.

The Biosecurity Blind Spot: Systematic Dual-use Detection in Open Science Infrastructure ChemBERTa-2: Towards Chemical Foundation Models

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-07-01T13:45:46.499320Z

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

Observation c97e9aa0-c335-41c7-bc1a-5a15ccde1653 · inbound

The Metric Picks the Winner: Evaluation Choice Flips Model Rankings for Drug-Response Prediction in Unseen Chemistry cites this paper.

The Metric Picks the Winner: Evaluation Choice Flips Model Rankings for Drug-Response Prediction in Unseen Chemistry ChemBERTa-2: Towards Chemical Foundation Models

Reference 2

Resolution: verified exact; arxiv_id, observed 2026-07-03T09:17:48.698863Z

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

Observation dcadaf46-44d6-44d5-b205-2ab44ef9e6b5 · inbound

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

What Does a Chemical Language Model Know About Molecules? ChemBERTa-2: Towards Chemical Foundation Models

Reference 2

Resolution: verified exact; arxiv_id, observed 2026-07-04T09:49:44.746691Z

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

Observation 4b5d9181-8d56-44b7-b2d9-0c1b5977336e · inbound

MetaboLLM: a metabolomics-specialized large language model for biochemical knowledge integration and predictive metabolite graph construction cites this paper.

MetaboLLM: a metabolomics-specialized large language model for biochemical knowledge integration and predictive metabolite graph construction ChemBERTa-2: Towards Chemical Foundation Models

Reference 69

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