Reasoning

Nonlinear Causal Discovery with Latent Confounders ICML 2023 Nonparametric Identifiability of Causal Representations from Unknown Interventions NeurIPS 2023 Normalizing Flows for Interventional Density Estimation ICML 2023 Nothing but Regrets — Privacy-Preserving Federated Causal Discovery AISTATS 2023 Novel Relation Detection: Discovering Unknown Relation Types via Multi-Strategy Self-Supervised Learning EMNLP 2023 NQE: N-ary Query Embedding for Complex Query Answering over Hyper-Relational Knowledge Graphs AAAI 2023 On Building a Semi-Automated Framework for Generating Causal Bayesian Networks from Raw Text IJCAI 2023 On Data Manifolds Entailed by Structural Causal Models ICML 2023 On Grounded Planning for Embodied Tasks with Language Models AAAI 2023 On Identifiability of Conditional Causal Effects UAI 2023 On Learning Necessary and Sufficient Causal Graphs NeurIPS 2023 On the Complexity of Counterfactual Reasoning IJCAI 2023 On the Relationship Between Explanation and Prediction: A Causal View ICML 2023 On Undisputed Sets in Abstract Argumentation AAAI 2023 Open-Domain Hierarchical Event Schema Induction by Incremental Prompting and Verification ACL 2023 Optimal Treatment Regimes for Proximal Causal Learning NeurIPS 2023 Optimizing the Computation of Overriding in DLN (Extended Abstract) IJCAI 2023 Out-of-Distribution Generalization by Neural-Symbolic Joint Training AAAI 2023 Pairwise Causality Guided Transformers for Event Sequences NeurIPS 2023 Partial identification of dose responses with hidden confounders UAI 2023 Penguins Don’t Fly: Reasoning about Generics through Instantiations and Exceptions EACL 2023 Pipeline for modeling causal beliefs from natural language ACL 2023 PlanBench: An Extensible Benchmark for Evaluating Large Language Models on Planning and Reasoning about Change NeurIPS 2023 Polynomial-Time Algorithms for Counting and Sampling Markov Equivalent DAGs with Applications JMLR 2023 PPAT: Progressive Graph Pairwise Attention Network for Event Causality Identification IJCAI 2023