ICLR 2026 Past Large language modelsAI for science
ICLR 2026 Workshop on Foundation Models for Science: Real-World Impact and Science-First Design
ICLR 2026 Workshop FM4Science
- Submission deadline
- Feb 11, 2026, 11:59 UTC 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 (78)
Fetched from OpenReview (v2) on 2026-06-10.
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(Sparse) Attention to the Details: Preserving Spectral Fidelity in ML-based Weather Forecasting Models
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[Short] Real-Time Explanations for Tabular Foundation Models
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A Systematic Study of Behavioral Cloning for Scientific Data Annotation
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Accurate Tokenization of 3D Small Organic Molecules
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Agentic Discovery of Multi-Channel Bioacoustic Association Algorithms
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AI Driven Discovery of Bio Ecological Mediation in Cascading Heatwave Risks
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Augmenting representations with scientific papers
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Back to BERT in 2026: ModernGENA as a Strong, Efficient Baseline for DNA Foundation Models
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Benchmarking foundation models for unsupervised discovery in large multimodal astrophysical datasets
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Beyond Independent Frames: Latent Attention Masked Autoencoders for Multi-View Echocardiography
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Built-in Safeguards for Auto-regressive Protein Foundation Models through Self-play
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CausalEvolve: Towards Open-Ended Discovery with Causal Scratchpad
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CausalGame: Benchmarking Causal Thinking of LLM Agents in Games
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Constructing Machine-Precision Neural Networks with Quasi-Interpolants
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Darwin-7B: A Multi-Omic Foundation Model for the Human Gut Microbiome\\via Sparsified Quality-Aware Tokenization
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Deep Learning for BioImaging: What Are We Learning?
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Does Aurora Encode Atmospheric Structure? Latent Regime Analysis and Attribution
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ECLIPSE: A Composable Pipeline for Predicting ecDNA Formation, Evolution, and Therapeutic Vulnerabilities in Cancer
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Effective Biological Representation Learning by Masking Gene Expression
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Efficient Tail-Aware Generative Optimization via Flow Model Fine-Tuning
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Evaluating Expert Specialization in Mixture-of-Experts Antibody Language Models
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EVIDENCE-GATED SCIENTIFIC QA WITH EXPLICIT ABSTENTION AND PAGE-LEVEL PROVENANCE
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EvoFlows: Evolutionary Edit-Based Flow-Matching for Protein Engineering
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FINGERS-7B: A Multi-Omic Foundation Model for Precision Biomarker Discovery
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FIRE: Multi-fidelity Regression with Distribution-conditioned In-context Learning using Tabular Foundation Models
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FlowMS: Flow Matching for De Novo Structure Elucidation from Mass Spectra
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Foundation Model for Cardiac Time Series via Masked Latent Attention
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Foundation Models as Physical Priors: Decoupling Geometric Reasoning from Small-Molecule Solubility Prediction
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Foundation models for agricultural sciences - Challenges and opportunities
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FragmentFlow: Scalable Transition State Generation for Large Molecules
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From Weather to Weathering: Foundation Models for Carbon Removal via Rock Weathering
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Full-length mRNA Design with Reward-Guided Masked Diffusion Model Fine-Tuning
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GeoPT: Scaling Physics Simulation via Lifted Geometric Pre-Training
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Hierarchy-Guided Multimodal Representation Learning for Taxonomic Inference
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Higher-order grammar representations for molecular generation and learning
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Information-Theoretic Requirements for Gradient-Based Task Affinity Estimation in Multi-Task Learning
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Kraus Constrained Sequence Learning For Quantum Trajectories from Continuous Measurement
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Language-Enhanced Representation Learning for Single-Cell Transcriptomics
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Learning Enhanced Protein Representations from Molecular Dynamics Trajectories via Temporal GNNs
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Learning What's Real: Disentangling Signal and Measurement Artifacts in Multi-Sensor Data, with Applications to Astrophysics
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LUMINA: Foundation Models for Topology Transferable ACOPF
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LunarFM: a multimodal representation of the Moon's surface
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MEG-XL: Data-Efficient Brain-to-Text via Long-Context Pre-Training
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MMAI Gym for Science: Training Liquid Foundation Models for Drug Discovery
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MOOSE: Targeted Small Molecule Generation via Multi-Objective-Guided Discrete Diffusion
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Multimodal Datasets with Controllable Mutual Information
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Neural Scaling Laws for Boosted Jet Tagging
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NeuroLoom: Modeling Cortical Microcircuits with Spiking Neural Networks
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On Neural Scaling Laws for Weather Emulation through Continual Training
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Optimizing Materials With CliqueFlowmer
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PepRePs: Peptide-Retargeted Phosphatases via Generative Language Models
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Position: Science is Collaborative—LLM for Science Should Be Too
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Predicting New Concept--Object Associations in Astronomy by Mining the Literature
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Rethinking Perturbation Prediction Baselines
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SaDiT: Efficient Protein Backbone Design via Latent Structural Tokenization and Diffusion Transformers
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SciPredict: Can LLMs Predict the Outcomes of Scientific Experiments in Natural Sciences?
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Self-Attention for Quantum Entanglement Prediction
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SENDAI: A Hierarchical Sparse-measurement, EfficieNt Data AssImilation Framework
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Single-Position Intervention Fails: Distributed Output Templates Drive In-Context Learning
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SNOOPPI: Sequence-Normalized Database of On- and Off-Target Protein-Protein Interactions
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Sparse Probes, Murky Physics: Interpretability Challenges in a Foundation Model for Continuum Dynamics
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ST-Align: Multi-Scale Image-Gene Foundation Modeling for Spatial Transcriptomics via Spot-Niche Alignment
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Surrogate-Assisted Pedestrian Protection Design via a Foundation Model–Orchestrated Workflow
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Symmetry-Aware Entropy Reinforcement Learning for Chaos Accurate Holographic Duals in NISQ Hardware
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Test-Time Tuned Language Models Enable End-to-end De Novo Molecular Structure Generation from MS/MS Spectra
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The Reliability Gap in Agentic Evidence Verification for Materials Science
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The Right Inductive Bias for the Job: Dependency-Aware Masking for Scientific Foundation Models
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Towards Foundation Models for Quantum Unitary Synthesis via Zero-Shot MDL
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Towards Understanding Hybrid Protein Language Model Design: A Systematic Ablation and Interpretability Study
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Two-Stage Ligand-Protein Complex Sequence Design with L-Caliby
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Understanding The Limits Of Text-Only Molecular Reasoning: A Case Study In Synthetic Chain-Of-Thought Supervision
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Unified Cross-Scale 3D Generation and Understanding via Autoregressive Modeling
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Vehicle Surface Pressure Prediction from 2D Sketches via a Pre-Trained Diffusion Model
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Want to train KANS at scale? Now UKAN!
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When Does Context Help? A Systematic Study of Target-Conditional Molecular Property Prediction
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When Protein Dynamics Matter: Integrating Molecular Dynamics into Protein Foundation Models
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WIND: Weather Inverse Diffusion for Zero-Shot Atmospheric Modeling
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Zatom-1: A Multimodal Flow Foundation Model for 3D Molecules and Materials