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

211 papers, page 4 of 5

151. NeurIPS 2026Fiedler-Regularized Causal Discovery for Sparse Connected DAGs
152. NeurIPS 2026Finite Resources False Discovery Rate Control on Structured Hypothesis Spaces
153. NeurIPS 2026Flexible Flows for Biological Sequence Design
154. NeurIPS 2026From I/O to Code with Discovery Agent
155. NeurIPS 2026Generating Physically Consistent Molecules with Energy-Based Models
156. NeurIPS 2026GenZ: Hybrid statistical–foundational models for knowledge discovery from real-valued multidimensional targets
157. NeurIPS 2026GraDE: A Graph Diffusion Estimator for Frequent Subgraph Discovery in Neural Architectures
158. NeurIPS 2026Hodge Laplacian Quasi-Harmonic Flows for Option Discovery
159. NeurIPS 2026HyperTree: Scalable Unsupervised Hierarchy Discovery in Hyperbolic Space
160. NeurIPS 2026Improving constraint-based discovery with robust propagation and LLM priors
161. NeurIPS 2026Integrating Background Knowledge for Scalable Causal Discovery
162. NeurIPS 2026Interpreting Latent Protein Language Model Features with Geometric Annotations
163. NeurIPS 2026Learning Generative Dynamics for 3D Molecule Generation via Sequential Neuro-Symbolic Constraints
164. NeurIPS 2026Lifting Biomolecular Data Acquisition
165. NeurIPS 2026LLM-AutoSciLab: Closed-Loop Scientific Law Discovery via Active Experimentation with LLMs
166. NeurIPS 2026LLMs Improving LLMs: Agentic Discovery for Test-Time Scaling
167. NeurIPS 2026Mapping Uncharted Symmetries: Machine Discovery in Combinatorics
168. NeurIPS 2026Mimicking the Physicist's Eye: A VLM-centric Approach for Physics Formula Discovery
169. NeurIPS 2026MIND-DDI: Multi-Omics Interpretable Drug-Drug Interaction Prediction with Joint Optimization of Graph Structure, Neural Architecture, and Symbolic Rules
170. NeurIPS 2026MolSpecFlow: Modality-Incomplete Molecular--Spectral Learning for MS/MS
171. NeurIPS 2026MOSAIC: Module Discovery via Sparse Additive Identifiable Causal Learning for Scientific Time Series
172. NeurIPS 2026Multi-Oracle Agreement Reveals the Limits of Self-Consistency Evaluation in RNA Design
173. NeurIPS 2026Multi-Part Object Representations via Graph Structures and Co-Part Discovery
174. NeurIPS 2026NORMA: Norm-Guided Explanation Subgraph Discovery
175. NeurIPS 2026On the Selectivity of Generative Models in Structure-Based Drug Design
176. NeurIPS 2026Open-Ended Scientific Discovery and the Social Dynamics of Evolving Agent Networks
177. NeurIPS 2026Optimizing Analytic Constants via AI-Guided Lean Proof Refinement
178. NeurIPS 2026PAIR-CI: Calibrated Conditional Independence Testing for Causal Discovery with Incomplete Data
179. NeurIPS 2026PIGRAM: An Interpretable Patch--Motif Interaction Grammar for Protein--Nucleic-Acid Recognition
180. NeurIPS 2026Position: Machine Learning Models for Reaction Transition States Deserve Better
181. NeurIPS 2026Preserving DEG Rankings for Gene Discovery in Histology-Based Spatial Gene Expression Prediction
182. NeurIPS 2026Probe Before You Edit: Probing-Guided Molecular Optimization for LLM Agents in Structure-Based Drug Design
183. NeurIPS 2026ProteinOPD: Towards Effective and Efficient Preference Alignment for Protein Design
184. NeurIPS 2026ProtGlycanDock: Towards Accurate Protein-Glycan Docking with Tailored Dataset, Benchmark and Model
185. NeurIPS 2026Pushing Biomolecular Utility-Diversity Frontiers with Supergroup Relative Policy Optimization
186. NeurIPS 2026QT-Net: Rethinking Evaluation of AI Models in Atomic Chemical Space
187. NeurIPS 2026Reusable Conditional Resampling via Flow Matching for Constraint-Based Causal Discovery
188. NeurIPS 2026RnR: a meta-solver for causal discovery in undersampled time series data
189. NeurIPS 2026Runtime Analysis of Cartesian Genetic Programming on MAX: A Proven Exponential Speedup
190. NeurIPS 2026SCDM: Scalable Causal Discovery in Nonlinear Temporal Systems with Meta-Learning
191. NeurIPS 2026SciResearchBench: Benchmarking AI Agents on Complex Scientific Literature Discovery
192. NeurIPS 2026ScopeSAE: Model-Scope Feature Discovery with Interpretable Layer Selection
193. NeurIPS 2026Screening Lipid Nanoparticles through Structure-Ratio Alignment
194. NeurIPS 2026ScreenShot: A Foundation Model for Few-Shot Combination Drug Screening
195. NeurIPS 2026Seen-Constrained Model-Order Selection for Unknown-$K$ Generalized Category Discovery
196. NeurIPS 2026Self-Improvement Imitation with Biologically Guided Search for Protein Design Under Oracle Budgets
197. NeurIPS 2026Self-Supervised Keyframe Discovery for Horizon-Invariant Behavior Cloning
198. NeurIPS 2026SLOT-IR: Learning Disentangled Slot Representations for Infrared Spectral Unmixing
199. NeurIPS 2026SNACK: A Sequential Notation Framework for Probabilistic Graph Generation
200. NeurIPS 2026Sparse Biological Features Reveal Early Functional Commitment in Diffusion Protein Language Models

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.