Molecule Captioning

Description from the archive archive 2025-07-28.

Benchmarks archive 2025-07-28

2 leaderboard tables shown for this task, 2 with rows (a “benchmark” on this site is a table with at least one row, as on /sota), ordered by row count. “Best model” is the first row in the archive's own order at snapshot; nothing is re-ranked here and metric direction is not recorded in the archive. PwC's Trend sparklines are not in the archive, so that column is omitted.

Syntology column: samples harvested from the paper's repositories and executed on synthesized fixtures; “ran” is not a correctness claim and does not order the table. A dash means no Syntology record for that paper, not a recorded non-run. Read from the graph 2026-09-24.

Libraries

Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.

Datasets archive 2025-07-28

2 datasets whose archive record lists this task, ordered by the archive's paper count.

Subtasks archive 2025-07-28

No subtask under this task in the archive's task tree.

Most implemented papers archive 2025-07-28

23 shown of 23 papers with code (25 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• A Molecular Multimodal Foundation Model Associating Molecule Graphs with Natural Language
  12 Sep 2022 4 repositories listed Syntology ran 2 of 8 samples · 6 unverified · 2 pointer-only (licence)
  Although artificial intelligence (AI) has made significant progress in understanding molecules in a wide range of fields, existing models generally acquire the single cognitive ability from the single molecular modality.
• MolFM: A Multimodal Molecular Foundation Model
  6 Jun 2023 2 repositories listed
  In this study, we introduce MolFM, a multimodal molecular foundation model designed to facilitate joint representation learning from molecular structures, biomedical texts, and knowledge graphs.
• XMolCap: Advancing Molecular Captioning through Multimodal Fusion and Explainable Graph Neural Networks
  23 May 2025 1 repository listed
  Large language models (LLMs) have significantly advanced computational biology by enabling the integration of molecular, protein, and natural language data to accelerate drug discovery.
• Automatic Annotation Augmentation Boosts Translation between Molecules and Natural Language
  10 Feb 2025 1 repository listed
  Recent advancements in AI for biological research focus on integrating molecular data with natural language to accelerate drug discovery.
• Property Enhanced Instruction Tuning for Multi-task Molecule Generation with Large Language Models
  24 Dec 2024 1 repository listed
  In the first step, we use textual descriptions, SMILES, and biochemical properties as multimodal inputs to pre-train a model called PEIT-GEN, by aligning multi-modal representations to synthesize instruction data.
• GeomCLIP: Contrastive Geometry-Text Pre-training for Molecules
  16 Nov 2024 1 repository listed
  Based on this dataset, we propose the GeomCLIP framework to enhance for multi-modal representation learning from molecular structures and biomedical text.
• Vector-ICL: In-context Learning with Continuous Vector Representations
  8 Oct 2024 1 repository listed
  Large language models (LLMs) have shown remarkable in-context learning (ICL) capabilities on textual data.
• Mol2Lang-VLM: Vision- and Text-Guided Generative Pre-trained Language Models for Advancing Molecule Captioning through Multimodal Fusion
  15 Aug 2024 1 repository listed
  This paper introduces Mol2Lang-VLM, an enhanced method for refining generative pre-trained language models for molecule captioning using multimodal features to achieve more accurate caption generation.
• 3D-MolT5: Leveraging Discrete Structural Information for Molecule-Text Modeling
  9 Jun 2024 1 repository listed Syntology ran 10 of 16 samples · 6 unverified
  To address the limitations, we propose \textbf{3D-MolT5}, a unified framework designed to model molecule in both sequence and 3D structure spaces.
• ReactXT: Understanding Molecular "Reaction-ship" via Reaction-Contextualized Molecule-Text Pretraining
  23 May 2024 1 repository listed Syntology ran 7 of 10 samples · 3 unverified
  To resolve the challenges above, we propose a new pretraining method, ReactXT, for reaction-text modeling, and a new dataset, OpenExp, for experimental procedure prediction.
• Atomas: Hierarchical Alignment on Molecule-Text for Unified Molecule Understanding and Generation
  23 Apr 2024 1 repository listed
  However, most approaches employ a global alignment approach to learn the knowledge from different modalities that may fail to capture fine-grained information, such as molecule-and-text fragments and stereoisomeric…
• BioT5+: Towards Generalized Biological Understanding with IUPAC Integration and Multi-task Tuning
  27 Feb 2024 1 repository listed
  However, previous efforts like BioT5 faced challenges in generalizing across diverse tasks and lacked a nuanced understanding of molecular structures, particularly in their textual representations (e.
• Towards 3D Molecule-Text Interpretation in Language Models
  25 Jan 2024 1 repository listed Syntology ran 7 of 9 samples · 2 unverified · 9 pointer-only (licence)
  Through 3D molecule-text alignment and 3D molecule-centric instruction tuning, 3D-MoLM establishes an integration of 3D molecular encoder and LM.
• InstructMol: Multi-Modal Integration for Building a Versatile and Reliable Molecular Assistant in Drug Discovery
  27 Nov 2023 1 repository listed Syntology ran 3 of 3 samples · 0 unverified
  The rapid evolution of artificial intelligence in drug discovery encounters challenges with generalization and extensive training, yet Large Language Models (LLMs) offer promise in reshaping interactions with complex…
• MolCA: Molecular Graph-Language Modeling with Cross-Modal Projector and Uni-Modal Adapter
  19 Oct 2023 1 repository listed Syntology ran 8 of 16 samples · 8 unverified · 16 pointer-only (licence)
  MolCA enables an LM (e.
• BioT5: Enriching Cross-modal Integration in Biology with Chemical Knowledge and Natural Language Associations
  11 Oct 2023 1 repository listed Syntology ran 1 of 1 samples · 0 unverified
  Recent advancements in biological research leverage the integration of molecules, proteins, and natural language to enhance drug discovery.
• From Artificially Real to Real: Leveraging Pseudo Data from Large Language Models for Low-Resource Molecule Discovery
  11 Sep 2023 1 repository listed
  Furthermore, our method shows a sustained improvement as the volume of pseudo data increases, revealing the great potential of pseudo data in advancing low-resource cross-modal molecule discovery.
• GIT-Mol: A Multi-modal Large Language Model for Molecular Science with Graph, Image, and Text
  14 Aug 2023 1 repository listed Syntology ran 1 of 1 samples · 0 unverified
  Large language models have made significant strides in natural language processing, enabling innovative applications in molecular science by processing textual representations of molecules.
• Empowering Molecule Discovery for Molecule-Caption Translation with Large Language Models: A ChatGPT Perspective
  11 Jun 2023 1 repository listed
  In this work, we propose a novel LLM-based framework (MolReGPT) for molecule-caption translation, where an In-Context Few-Shot Molecule Learning paradigm is introduced to empower molecule discovery with LLMs like…
• MolXPT: Wrapping Molecules with Text for Generative Pre-training
  18 May 2023 1 repository listed
  Considering that text is the most important record for scientific discovery, in this paper, we propose MolXPT, a unified language model of text and molecules pre-trained on SMILES (a sequence representation of…
• Unifying Molecular and Textual Representations via Multi-task Language Modelling
  29 Jan 2023 1 repository listed
  Here, we propose the first multi-domain, multi-task language model that can solve a wide range of tasks in both the chemical and natural language domains.
• Graph-based Molecular Representation Learning
  8 Jul 2022 1 repository listed
  Recently, MRL has achieved considerable progress, especially in methods based on deep molecular graph learning.
• Translation between Molecules and Natural Language
  25 Apr 2022 1 repository listed Syntology ran 0 of 5 samples · 5 unverified
  We present MolT5 - a self-supervised learning framework for pretraining models on a vast amount of unlabeled natural language text and molecule strings.

Syntology lines on 9 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.