ICLR 2026PastGenomicsGenerative models
Generative AI in Genomics (Gen²): Barriers and Frontiers
Gen² 2026
- Submission deadline
- Feb 12, 2026, 11:59 UTCOpenReview-synced 2026-02-12 11:59 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 (57)
Fetched from OpenReview (v2) on 2026-06-10.
A Standardized Framework For Evaluating Gene Expression Generative Models
Accelerating Scientific Discovery with Autonomous Goal-evolving Agents
Attractome: From Theory to Generative Models for Cancer Dynamics and Control
Back to BERT in 2026: ModernGENA as a Strong, Efficient Baseline for DNA Foundation Models
Benchmarking COX1 Embeddings across Genomic Foundation Models, kmers, and Imbalance-Aware Losses
Beyond Edge Prediction: Residual Set Modeling for Combinatorial Gene Regulation
BiomedSQL: Text-to-SQL for Scientific Reasoning on Biomedical Knowledge Bases
CausalOmics-10T: An Evolving Foundational Dataset to Enable Causal Modeling of Microbial Ecosystems
CellTarNet: Single-Cell Perturbation Prediction using Transformer based Normalizing Flow
CONSTRAINED LANGUAGE-GUIDED REFINEMENT FOR ZERO-SHOT SPATIAL ANNOTATION
Contact-Guided 3D Genome Structure Generation of E. coli via Diffusion Transformers
Continuous Diffusion Transformers for Designing Synthetic Regulatory Elements
D3LM: A Discrete DNA Diffusion Language Model for Bidirectional DNA Understanding and Generation
DALI Learns Rules Generating Spatiotemporal Transcriptomics
Deep Learning-Based Prediction of Variant Effects on Chromatin Accessibility During Dynamic Neuronal Activation
DISCRETE FLOW MATCHING FOR REGULATORY DNA SEQUENCE DESIGN
Dissecting and Steering Cell Identity in a Single-Cell Foundation Model Using Sparse Autoencoders
Distilling Genomic Models for Efficient mRNA Representation Learning via Embedding Matching
DREAM-DNA: Controlled Design via Reasoning and Matched-flows for DNA
Effects of Distance Metrics and Scaling on the Perturbation Discrimination Score
ELISA: A Generative AI Agent for Expression Grounded Discovery in Single-Cell Genomics
Enigma: An Efficient Model for Deciphering Regulatory Genomics
From sequence to strength: prediction and design of intrinsic transcription terminators
Generating and decoding methylated DNA with a Human Epigenetic Foundation Model
Generative Modeling of Spatial Transcriptomics via Gaussian Mixture Flow Matching
Generative modeling reveals the connection between cellular morphology and gene expression
Genes Are Not Words: Dependency-Aware Masking for Single-Cell Foundation Models
Genomic heterogeneity inflates the performance of variant pathogenicity predictions
GPC: Deep generative model of genetic variation data improves imputation accuracy in private populations
Graph Attention Network generates Super-resolution Spatial Transcriptomic data
Hierarchical Disease-State Generators for Neurodegenerative Genomics: A Benchmark Proposal for Intervention-Conditioned Multi-omic Generation
Identifying Donor-Robust Perturbation Targets via Sparse Manifold Control
Large-Scale Benchmarking of Gene and Expression Encoding Strategies for Single-Cell Foundation Models
LLM-Guided Retrieval for Prediction of Molecular Perturbation Responses
MapPFN: Learning Causal Perturbation Maps in Context
MechPert: Mechanistic Consensus as an Inductive Bias for Unseen Perturbation Prediction
Mimyr: Generative Modeling of Missing Tissue in Spatial Transcriptomics
Modern Gene Finders: ab initio gene discovery benchmark with DNA language models
Motif-Gen: Learning the Compositional Logic of Gene Regulation for De Novo DNA Design
mRNABench: A curated benchmark for mature mRNA property and function prediction
ON THE IMPACT OF EMBEDDING ANISOTROPY IN GENOMIC LANGUAGE MODELS FOR BACTERIAL TAXONOMY
On the role of drug representations in single-cell perturbation modeling
Optimizing Genomic Language Models for Efficient Training, Fine-Tuning, and Inference
PD-scWorld: Pathway-Guided Disentanglement for Single-Cell Perturbation World Models
Protein Counterfactuals via Diffusion-Guided Latent Optimization
Rethinking Perturbation Prediction Baselines
Retrieval-Augmented Generation for Predicting Cellular Responses to Gene Perturbation
Reward-Guided Discrete Diffusion via Clean-Sample Markov Chain for Molecule and Biological Sequence Design
Scaling Laws and Architectural Frontiers in Metagenomic Foundation Models
Sequence Generation and Phylogenetic Inference with Generative Flow Networks
Sparse Autoencoders Reveal Interpretable Features in Single-Cell Foundation Models
SplicedVAE: Learning Splicing Ratios from scRNA-seq to Enhance RNA Velocity and Cellular Trajectories
Structured and interpretable patient embeddings from Single-Cell Foundation Models
Tensorised Modular Architectures for Multi-Omics Generation
Toward Generative Virtual Cells: Co-Evolving World Models and Perturbation Planners
Trajectory-conditioned reconstruction of single-cell expression suggests regulatory programs
TRUST-REGION SALIENCY-GUIDED LOCAL SEARCH FOR INTERPRETABLE SEQUENCE DESIGN AT FIXED EDIT BUDGETS