ICML 2025PastOther
ICML 2025 Workshop on Scaling Up Intervention Models
ICML 2025 Workshop SIM
- Submission deadline
- May 26, 2025, 11:59 UTCimported from OpenReview — check the website for extensions
- Submission portal
- OpenReview
- Notes
- Topics were auto-suggested and may be imprecise — edits welcome.
Accepted papers (41)
Fetched from OpenReview (v2) on 2026-06-10.
A Meta-Learning Approach to Causal Inference
Amortized Active Generation of Pareto Sets
An Object-Attribute Decoupled Approach for Learning Disentangled Representation for Image and Video Analysis
Bidding for Influence: Auction-Driven Diffusion Image Generation
Can Large Language Models Help Experimental Design for Causal Discovery?
CausalPFN: Amortized Causal Effect Estimation via In-Context Learning
Competing Event Models: Next Event Prediction Under Interventions
Deep RL Inventory Management with Supply and Capacity Risk Awareness
Discovering Hierarchical Latent Capabilities of Language Models via Causal Representation Learning
Do-PFN: In-Context Learning for Causal Effect Estimation
Enhancing Math Reasoning in Small-sized LLMs via Preview Difficulty-Aware Intervention
Equipping Graphical Models with Interventions and Interactions Simultaneously
Estimating Causal Effects in Gaussian Linear SCMs with Finite Data
Estimating Interventional Distributions with Uncertain Causal Graphs through Meta-Learning
Estimating treatment effects in networks using domain adversarial learning
Failure Modes of LLMs for Causal Reasoning on Narratives
Faithfulness and Intervention-Only Causal Discovery
Keep the Alignment, Skip the Overhead: Lightweight Instruction Alignment for Continually Trained LLMs
Learning to Adapt: Self-Supervised Representations for Robust Contextual Bandits
Learning Treatment Representations for Downstream Instrumental Variable Regression
LLMs Struggle to Perform Counterfactual Reasoning with Parametric Knowledge
Markov-Boundary Consistent Feature Attribution
MorphGen: Controllable and Morphologically Plausible Generative Cell-Imaging
Multi-Objective-Guided Discrete Flow Matching for Controllable Biological Sequence Design
Multi-Objective-Guided Generative Design of mRNA with Therapeutic Properties
Network System Forecasting Despite Topology Perturbation
Noise Tolerance of Distributionally Robust Learning
Off-Policy Learning for Diversity-aware Candidate Retrieval in Two-stage Decisions
OOD Detection with Relative Angles
Prompt Optimization with Logged Bandit Data
Quantized Disentanglement: A Practical Approach
Robust estimation of heterogeneous treatment effects in randomized trials leveraging external data
scDataset: Scalable Data Loading for Deep Learning on Large-Scale Single-Cell Omics
SOAPIA: Siamese-Guided Generation of Off Target-Avoiding Protein Interactions with High Target Affinity
Solo Connection: A Parameter Efficient Fine-Tuning Technique for Transformers
Steering LLM Reasoning Through Bias-Only Adaptation
The Third Pillar of Causal Analysis? A Measurement Perspective on Causal Representations
Thompson Sampling in Function Spaces via Neural Operators
Towards Causal Representation Learning with Observable Sources as Auxiliaries
Towards Robust Causal Effect Identification beyond Markov Equivalence
TrialCalibre: A Fully Automated Causal Engine for RCT Benchmarking and Observational Trial Calibration