ICLR 2026 Past GenomicsGenerative models
Generative AI in Genomics (Gen²): Barriers and Frontiers
Gen² 2026
- Submission deadline
- Feb 11, 2026, 23:59 AoE (UTC−12) imported from OpenReview — check the website for extensions
- Submission portal
- OpenReview
- Notes
- Auto-imported from the OpenReview venue record on 2026-06-10 — please verify and enrich (topics are keyword-guessed).
Accepted papers (57)
Fetched from OpenReview (v2) on 2026-06-10.
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A Standardized Framework For Evaluating Gene Expression Generative Models
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Accelerating Scientific Discovery with Autonomous Goal-evolving Agents
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Attractome: From Theory to Generative Models for Cancer Dynamics and Control
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Back to BERT in 2026: ModernGENA as a Strong, Efficient Baseline for DNA Foundation Models
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Benchmarking COX1 Embeddings across Genomic Foundation Models, kmers, and Imbalance-Aware Losses
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Beyond Edge Prediction: Residual Set Modeling for Combinatorial Gene Regulation
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BiomedSQL: Text-to-SQL for Scientific Reasoning on Biomedical Knowledge Bases
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CausalOmics-10T: An Evolving Foundational Dataset to Enable Causal Modeling of Microbial Ecosystems
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CellTarNet: Single-Cell Perturbation Prediction using Transformer based Normalizing Flow
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CONSTRAINED LANGUAGE-GUIDED REFINEMENT FOR ZERO-SHOT SPATIAL ANNOTATION
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Contact-Guided 3D Genome Structure Generation of E. coli via Diffusion Transformers
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Continuous Diffusion Transformers for Designing Synthetic Regulatory Elements
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D3LM: A Discrete DNA Diffusion Language Model for Bidirectional DNA Understanding and Generation
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DALI Learns Rules Generating Spatiotemporal Transcriptomics
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Deep Learning-Based Prediction of Variant Effects on Chromatin Accessibility During Dynamic Neuronal Activation
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DISCRETE FLOW MATCHING FOR REGULATORY DNA SEQUENCE DESIGN
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Dissecting and Steering Cell Identity in a Single-Cell Foundation Model Using Sparse Autoencoders
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Distilling Genomic Models for Efficient mRNA Representation Learning via Embedding Matching
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DREAM-DNA: Controlled Design via Reasoning and Matched-flows for DNA
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Effects of Distance Metrics and Scaling on the Perturbation Discrimination Score
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ELISA: A Generative AI Agent for Expression Grounded Discovery in Single-Cell Genomics
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Enigma: An Efficient Model for Deciphering Regulatory Genomics
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From sequence to strength: prediction and design of intrinsic transcription terminators
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Generating and decoding methylated DNA with a Human Epigenetic Foundation Model
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Generative Modeling of Spatial Transcriptomics via Gaussian Mixture Flow Matching
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Generative modeling reveals the connection between cellular morphology and gene expression
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Genes Are Not Words: Dependency-Aware Masking for Single-Cell Foundation Models
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Genomic heterogeneity inflates the performance of variant pathogenicity predictions
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GPC: Deep generative model of genetic variation data improves imputation accuracy in private populations
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Graph Attention Network generates Super-resolution Spatial Transcriptomic data
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Hierarchical Disease-State Generators for Neurodegenerative Genomics: A Benchmark Proposal for Intervention-Conditioned Multi-omic Generation
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Identifying Donor-Robust Perturbation Targets via Sparse Manifold Control
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Large-Scale Benchmarking of Gene and Expression Encoding Strategies for Single-Cell Foundation Models
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LLM-Guided Retrieval for Prediction of Molecular Perturbation Responses
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MapPFN: Learning Causal Perturbation Maps in Context
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MechPert: Mechanistic Consensus as an Inductive Bias for Unseen Perturbation Prediction
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Mimyr: Generative Modeling of Missing Tissue in Spatial Transcriptomics
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Modern Gene Finders: ab initio gene discovery benchmark with DNA language models
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Motif-Gen: Learning the Compositional Logic of Gene Regulation for De Novo DNA Design
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mRNABench: A curated benchmark for mature mRNA property and function prediction
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ON THE IMPACT OF EMBEDDING ANISOTROPY IN GENOMIC LANGUAGE MODELS FOR BACTERIAL TAXONOMY
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On the role of drug representations in single-cell perturbation modeling
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Optimizing Genomic Language Models for Efficient Training, Fine-Tuning, and Inference
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PD-scWorld: Pathway-Guided Disentanglement for Single-Cell Perturbation World Models
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Protein Counterfactuals via Diffusion-Guided Latent Optimization
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Rethinking Perturbation Prediction Baselines
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Retrieval-Augmented Generation for Predicting Cellular Responses to Gene Perturbation
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Reward-Guided Discrete Diffusion via Clean-Sample Markov Chain for Molecule and Biological Sequence Design
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Scaling Laws and Architectural Frontiers in Metagenomic Foundation Models
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Sequence Generation and Phylogenetic Inference with Generative Flow Networks
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Sparse Autoencoders Reveal Interpretable Features in Single-Cell Foundation Models
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SplicedVAE: Learning Splicing Ratios from scRNA-seq to Enhance RNA Velocity and Cellular Trajectories
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Structured and interpretable patient embeddings from Single-Cell Foundation Models
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Tensorised Modular Architectures for Multi-Omics Generation
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Toward Generative Virtual Cells: Co-Evolving World Models and Perturbation Planners
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Trajectory-conditioned reconstruction of single-cell expression suggests regulatory programs
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TRUST-REGION SALIENCY-GUIDED LOCAL SEARCH FOR INTERPRETABLE SEQUENCE DESIGN AT FIXED EDIT BUDGETS