Drug Discovery papers, 2023–2026

Key findings

• Drug Discovery went from 79 papers in 2023 to 211 in 2026, roughly 2.7x in three years.
• NeurIPS publishes the most Drug Discovery work: 234 papers from 2023 to 2026, 40% of the four-venue total.
• The fastest-growing overlap is with Applications · chemistry physics and earth sciences: papers tagged with both rose from 1 in 2023 to 42 in 2026.
• Among the 5 topics under Health and Life Sciences, it ranks #2 by 2026 paper count; the fastest grower in the group, Clinical NLP, is up 3.2x versus 2.7x here.

Representative papers

Spread across years and venues so every edition shows up

• NeurIPS 2026ACER: Towards Generalizable Protein-ligand Co-folding
• ICML 2026Adaptive Symmetry Discovery for Dynamical System Identification
• ICLR 2026Bures Generalized Category Discovery
• CVPR 2026Learning Like Humans Analogical Concept Learning for Generalized Category Discovery
• NeurIPS 2025AANet: Virtual Screening under Structural Uncertainty via Alignment and Aggregation
• ICML 2025Explicit Discovery of Nonlinear Symmetries from Dynamic Data
• ICLR 2025CBGBench: Fill in the Blank of Protein-Molecule Complex Binding Graph
• CVPR 2025Adaptive Part Learning for Fine-Grained Generalized Category Discovery: A Plug-and-Play Enhancement
• NeurIPS 2024A SARS-CoV-2 Interaction Dataset and VHH Sequence Corpus for Antibody Language Models
• ICML 2024Amortized Equation Discovery in Hybrid Dynamical Systems
• ICLR 2024Self-supervised Pocket Pretraining via Protein Fragment-Surroundings Alignment
• CVPR 2024Federated Generalized Category Discovery
• NeurIPS 2023An Optimization-based Approach To Node Role Discovery in Networks: Approximating Equitable Partitions
• ICML 2023A Group Symmetric Stochastic Differential Equation Model for Molecule Multi-modal Pretraining
• ICLR 2023Context-enriched molecule representations improve few-shot drug discovery
• CVPR 2023Bootstrap Your Own Prior: Towards Distribution-Agnostic Novel Class Discovery
• NeurIPS 2026Active Flow Expansion for Out-of-Distribution Discovery: from Theory to Molecules
• ICML 2026CURE: Consistency-under-Unified Semantic Regularization for Generalized Category Discovery
• ICLR 2026Exploring Synthesizable Chemical Space with Iterative Pathway Refinements
• CVPR 2026TAR Token-Aware Refinement for Fine-grained Generalized Category Discovery

All Drug Discovery papers

125 papers, page 2 of 3

51. ICML 2024Foundations of Testing for Finite-Sample Causal Discovery
52. ICML 2024Full-Atom Peptide Design based on Multi-modal Flow Matching
53. ICML 2024Generalist Equivariant Transformer Towards 3D Molecular Interaction Learning
54. ICML 2024Generative Enzyme Design Guided by Functionally Important Sites and Small-Molecule Substrates
55. ICML 2024Harmonic Self-Conditioned Flow Matching for joint Multi-Ligand Docking and Binding Site Design
56. ICML 2024Interaction-based Retrieval-augmented Diffusion Models for Protein-specific 3D Molecule Generation
57. ICML 2024Intersectional Unfairness Discovery
58. ICML 2024KernelWarehouse: Rethinking the Design of Dynamic Convolution
59. ICML 2024Latent Space Symmetry Discovery
60. ICML 2024Learning to Predict Mutational Effects of Protein-Protein Interactions by Microenvironment-aware Hierarchical Prompt Learning
61. ICML 2024LLM and Simulation as Bilevel Optimizers: A New Paradigm to Advance Physical Scientific Discovery
62. ICML 2024MolCRAFT: Structure-Based Drug Design in Continuous Parameter Space
63. ICML 2024On the sample complexity of conditional independence testing with Von Mises estimator with application to causal discovery
64. ICML 2024Optimal Kernel Choice for Score Function-based Causal Discovery
65. ICML 2024Position: Data-driven Discovery with Large Generative Models
66. ICML 2024PPFLOW: Target-Aware Peptide Design with Torsional Flow Matching
67. ICML 2024Predicting Dose-Response Curves with Deep Neural Networks
68. ICML 2024Projecting Molecules into Synthesizable Chemical Spaces
69. ICML 2024Representing Molecules as Random Walks Over Interpretable Grammars
70. ICML 2024Scalable and Flexible Causal Discovery with an Efficient Test for Adjacency
71. ICML 2024Score-Based Causal Discovery of Latent Variable Causal Models
72. ICML 2024Stable Differentiable Causal Discovery
73. ICML 2024Structure-based drug design by denoising voxel grids
74. ICML 2024SurfPro: Functional Protein Design Based on Continuous Surface
75. ICML 2024Unsupervised Concept Discovery Mitigates Spurious Correlations
76. ICML 2024WISER: Weak Supervision and Supervised Representation Learning to Improve Drug Response Prediction in Cancer
77. NeurIPS 2024$\nabla^2$DFT: A Universal Quantum Chemistry Dataset of Drug-Like Molecules and a Benchmark for Neural Network Potentials
78. NeurIPS 2024A benchmark for prediction of transcriptomic responses to chemical perturbations across cell types
79. NeurIPS 2024A SARS-CoV-2 Interaction Dataset and VHH Sequence Corpus for Antibody Language Models
80. NeurIPS 2024Bridge-IF: Learning Inverse Protein Folding with Markov Bridges
81. NeurIPS 2024Causal Discovery from Event Sequences by Local Cause-Effect Attribution
82. NeurIPS 2024Causal discovery with endogenous context variables
83. NeurIPS 2024Causal-learn: Causal Discovery in Python
84. NeurIPS 2024CausalStock: Deep End-to-end Causal Discovery for News-driven Multi-stock Movement Prediction
85. NeurIPS 2024Contrastive losses as generalized models of global epistasis
86. NeurIPS 2024Customized Subgraph Selection and Encoding for Drug-drug Interaction Prediction
87. NeurIPS 2024Data-Driven Discovery of Dynamical Systems in Pharmacology using Large Language Models
88. NeurIPS 2024Discovery of the Hidden World with Large Language Models
89. NeurIPS 2024Disentangled Unsupervised Skill Discovery for Efficient Hierarchical Reinforcement Learning
90. NeurIPS 2024Do's and Don'ts: Learning Desirable Skills with Instruction Videos
91. NeurIPS 2024FlexMol: A Flexible Toolkit for Benchmarking Molecular Relational Learning
92. NeurIPS 2024FlexSBDD: Structure-Based Drug Design with Flexible Protein Modeling
93. NeurIPS 2024Flipped Classroom: Aligning Teacher Attention with Student in Generalized Category Discovery
94. NeurIPS 2024Generalized Protein Pocket Generation with Prior-Informed Flow Matching
95. NeurIPS 2024Happy: A Debiased Learning Framework for Continual Generalized Category Discovery
96. NeurIPS 2024Hybrid Top-Down Global Causal Discovery with Local Search for Linear and Nonlinear Additive Noise Models
97. NeurIPS 2024Identifying Selections for Unsupervised Subtask Discovery
98. NeurIPS 2024Interventional Causal Discovery in a Mixture of DAGs
99. NeurIPS 2024Learning Infinitesimal Generators of Continuous Symmetries from Data
100. NeurIPS 2024Learning symmetries via weight-sharing with doubly stochastic tensors

FAQ

How many Drug Discovery papers were published at NeurIPS, ICLR, ICML and CVPR from 2023 to 2026?

578 in total: 79 in 2023, 125 in 2024, 163 in 2025, 211 in 2026.

How many Drug Discovery papers are at NeurIPS 2026?

NeurIPS 2026 has 100 Drug Discovery papers, versus 64 the year before.

How many Drug Discovery papers are at ICLR 2026?

ICLR 2026 has 37 Drug Discovery papers, versus 48 the year before.

How many Drug Discovery papers are at ICML 2026?

ICML 2026 has 63 Drug Discovery papers, versus 39 the year before.

How many Drug Discovery papers are at CVPR 2026?

CVPR 2026 has 11 Drug Discovery papers, versus 12 the year before.

Which conference publishes the most Drug Discovery papers?

NeurIPS, with 234 papers from 2023 to 2026.