ICLR 2026PastGenomicsGenerative models
ICLR 2026 Workshop on Generative and Experimental Perspectives for Biomolecular Design
GEM 2026
- Submission deadline
- Feb 6, 2026, 13:59 UTCOpenReview-synced 2026-02-06 13:59 UTC (as of 2026-06-23) — extensions on OpenReview are applied automatically; verify on the website.
- Submission portal
- OpenReview
- Notes
- Topics were auto-suggested and may be imprecise — edits welcome.
Accepted papers (76)
Fetched from OpenReview (v2) on 2026-06-10.
A novel combinatorial high-throughput assay of small molecules and their protein targets
A Prospective Experimental Assessment of Structure-Based Drug Design: Are We There Yet?
A Unified Computational Framework for the Integration of AI Models in Structure-Based Drug Design
AbDD: Experimentally Validated Antibody Developability Optimization via Discrete Diffusion
Accelerating Protein Molecular Dynamics Simulation with DeepJump
Accelerating Scientific Discovery with Autonomous Goal-evolving Agents
AF3Design: Selectivity–Aware Nanobody Design with AlphaFold3
AlphaFast: High-throughput AlphaFold 3 via GPU-accelerated MSA construction
An Integrated Computational-Experimental Platform for Holistic mRNA Sequence Design, Build, Test, and Learn
Antibody design with steerable discrete diffusion
Antigen-specific Antibody Multi-modal Foundation Model for Functional Antibody Design
AReUReDi: Annealed Rectified Updates for Refining Discrete Flows with Multi-Objective Guidance
Autoregressive Boltzmann Generators
Biologically-Grounded Multi-Encoder Architectures as Developability Oracles for Antibody Design
Boltz2ESI: Accurate Enzyme Specificity Prediction with Co-folding Foundation Model
Bonobo: Efficient Library-Scale Generation for De Novo Antibody Design
Branching Flows: Discrete, Continuous, and Manifold Flow Matching with Splits and Deletions
CausalBind: Causal Concept Alignment for Protein-Ligand Virtual Screening
CHIMERA-Bench: A Benchmark Dataset for Epitope-Specific Antibody Design
Comparing Selectivity-Aware Generative AI and Library Screening in a Virtual DMT Cycle
Conditional Monte Carlo Tree Diffusion for Designing Cell-Type-Specific and Biologically Faithful Regulatory DNA
Conditionally Site-Independent Neural Evolution of Antibody Sequences
Conditioning Protein Language Models Using High-Throughput Sequence-Fitness Data Collection
DeepPrime7: Predicting PE7 Prime Editing Efficiency Across PAM Variants
Design of phase-separating biosystem via joint diffusion and positive-unlabeled guidance
Discovery of Bioresorbable Polymer Suture Coatings for Controlled Tissue Regeneration with Multimodal Foundation Models
ECLIPSE: A Composable Pipeline for Predicting ecDNA Formation, Evolution, and Therapeutic Vulnerabilities in Cancer
Efficient, Few-shot Directed Evolution with Energy Rank Alignment
Folding scFv--Antigen Complexes at Scale
FoldSAE: Learning To Steer Protein Folding Through Sparse Representations
From Structure to Function: Preference Alignment for Function-Aware Protein Inverse Folding
Generalized Multi-State Protein Design with AlphaFold3
Generative inverse design of RNA structure and function with gRNAde
GNMCADS: Sampling For Protein Conformation Diversity With Gaussian Network Model Based Condition Annealed Diffusion Sampler
HallmarkAge: Binarized Hallmark-Aware Transcriptomic Clocks to Discover Aging Mechanisms
Hit Expansion via Localized Exploration of Synthesizable Chemical Space
How to make the most of your masked language model for protein engineering
Hybrid interpretable biophysical modeling of fluorescent protein biosensor function
IN SILICO GENERATIVE DESIGN OF CHEMICALLY MODIFIED RNA SEQUENCES FOR FUNCTIONAL PREDICTION
Inference-time optimization for experiment-grounded protein ensemble generation
Inference-Time Toxicity Mitigation in Protein Language Models via Logit-Diff Amplification
Information-Theoretic Requirements for Gradient-Based Task Affinity Estimation in Multi-Task Learning
JUST ADD STRUCTURE: PROTEIN LANGUAGE MODELS COMBINED WITH STRUCTURAL EQUIVARIANCE EXCEL AT PROTEIN TASKS
Learning Adaptive Perturbation-Conditioned Contexts for Robust Transcriptional Response Prediction
LieFlower: Controlling Protein Dynamics via Lie-Guided Discrete Flows
Lyrebird: Toward Robust and Generalizable 3D Molecular Conformer Generation via Equivariant Flows
Machine learning-guided design of biomolecular condensates in an automated laboratory
Mechanisms of AI Protein Folding in ESMFold
Mechanistic Interpretability of Antibody Language Models Using SAEs
ML-GUIDED MINING OF AN EXTENSIVELY VALIDATED SCFV LIBRARY FOR OPEN-SOURCE ENZYMES IN DIAGNOSTICS
Modeling Static and Dynamic Protein Structure from 2D Infrared Spectrum with Stochastic Interpolant
mRNA-GPT: End-to-end Generative Design and Optimization of Full-length mRNA
MutaGen: Implicitly Guided Protein Evolution from Ranked Feedback via Pair-Based Discrete Flow Matching
OmegAMP: Targeted AMP Discovery via Biologically Informed Generation
On improving experimental binding affinity predictions with synthetic data
Origin-1: Experimentally Validated Generative AI Platform for De Novo Antibody Design Against “Zero-Prior” Epitopes
pCoMole: Pareto-Constrained Molecule Editing with Discrete Flows
PeptiVerse: A Unified Platform for Therapeutic Peptide Property Prediction
PMO-Dock: Benchmarking Docking, Specificity and Generalization in Molecular Optimization
PRISM: A Hybrid Diffusion-Reinforcement Learning Framework for 3D Structure-based De Novo Design
Protein Autoregressive Modeling via Multiscale Structure Generation
Reading TEA leaves for de novo protein design
S2S2Fun: Decoding Protein Function From Latent Structural Representations
Sample Efficient Generative Molecular Optimization with Joint Self-Improvement
Scalable Inference-Time Annealing for Continuous Normalizing Flows
Search-Based Inference-Time Scaling for All-Atom Protein Binder Design
Sequence Design and Phylogenetic Inference with Generative Flow Networks
SNOOPPI: Sequence-Normalized Database of On- and Off-Target Protein-Protein Interactions
Structural plausibility without binding specificity: limits of AI-based antibody-antigen structure prediction scores
SynLaD: Latent Diffusion for Generating Synthesizable Molecules Conditioned on 3D Pharmacophore Profiles
Synthesis-constrained discrete diffusion for ionizable lipid generation
Synthetic RNA Evolution Enables Accurate Alignment-Free 3D Structure Prediction
TD3B: Transition-Directed Discrete Diffusion for Allosteric Binder Generation
The Mechanistic Invariance Test: Genomic Language Models Fail To Learn Positional Regulatory Logic
Towards A Generative Protein Evolution Machine with DPLM-Evo
TOWARDS UNDERSTANDING HYBRID PROTEIN LANGUAGE MODEL DESIGN: A SYSTEMATIC ABLATION AND INTERPRETABILITY STUDY