ICML 2025 Past Other
ICML 2025 Workshop on Scaling Up Intervention Models
ICML 2025 Workshop SIM
- Submission deadline
- May 26, 2025, 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 (41)
Fetched from OpenReview (v2) on 2026-06-10.
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A Meta-Learning Approach to Causal Inference
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Amortized Active Generation of Pareto Sets
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An Object-Attribute Decoupled Approach for Learning Disentangled Representation for Image and Video Analysis
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Bidding for Influence: Auction-Driven Diffusion Image Generation
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Can Large Language Models Help Experimental Design for Causal Discovery?
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CausalPFN: Amortized Causal Effect Estimation via In-Context Learning
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Competing Event Models: Next Event Prediction Under Interventions
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Deep RL Inventory Management with Supply and Capacity Risk Awareness
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Discovering Hierarchical Latent Capabilities of Language Models via Causal Representation Learning
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Do-PFN: In-Context Learning for Causal Effect Estimation
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Enhancing Math Reasoning in Small-sized LLMs via Preview Difficulty-Aware Intervention
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Equipping Graphical Models with Interventions and Interactions Simultaneously
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Estimating Causal Effects in Gaussian Linear SCMs with Finite Data
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Estimating Interventional Distributions with Uncertain Causal Graphs through Meta-Learning
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Estimating treatment effects in networks using domain adversarial learning
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Failure Modes of LLMs for Causal Reasoning on Narratives
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Faithfulness and Intervention-Only Causal Discovery
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Keep the Alignment, Skip the Overhead: Lightweight Instruction Alignment for Continually Trained LLMs
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Learning to Adapt: Self-Supervised Representations for Robust Contextual Bandits
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Learning Treatment Representations for Downstream Instrumental Variable Regression
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LLMs Struggle to Perform Counterfactual Reasoning with Parametric Knowledge
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Markov-Boundary Consistent Feature Attribution
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MorphGen: Controllable and Morphologically Plausible Generative Cell-Imaging
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Multi-Objective-Guided Discrete Flow Matching for Controllable Biological Sequence Design
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Multi-Objective-Guided Generative Design of mRNA with Therapeutic Properties
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Network System Forecasting Despite Topology Perturbation
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Noise Tolerance of Distributionally Robust Learning
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Off-Policy Learning for Diversity-aware Candidate Retrieval in Two-stage Decisions
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OOD Detection with Relative Angles
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Prompt Optimization with Logged Bandit Data
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Quantized Disentanglement: A Practical Approach
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Robust estimation of heterogeneous treatment effects in randomized trials leveraging external data
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scDataset: Scalable Data Loading for Deep Learning on Large-Scale Single-Cell Omics
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SOAPIA: Siamese-Guided Generation of Off Target-Avoiding Protein Interactions with High Target Affinity
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Solo Connection: A Parameter Efficient Fine-Tuning Technique for Transformers
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Steering LLM Reasoning Through Bias-Only Adaptation
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The Third Pillar of Causal Analysis? A Measurement Perspective on Causal Representations
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Thompson Sampling in Function Spaces via Neural Operators
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Towards Causal Representation Learning with Observable Sources as Auxiliaries
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Towards Robust Causal Effect Identification beyond Markov Equivalence
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TrialCalibre: A Fully Automated Causal Engine for RCT Benchmarking and Observational Trial Calibration