{"total":16,"rows":[{"id":"2107.09846","title":"Guided Generation of Cause and Effect","created":"2021-07-21","cited_by_count":33,"area":null},{"id":"2101.06426","title":"A Survey on Extraction of Causal Relations from Natural Language Text","created":"2021-01-16","cited_by_count":25,"area":null},{"id":"2204.11714","title":"The Causal News Corpus: Annotating Causal Relations in Event Sentences from News","created":"2022-04-25","cited_by_count":25,"area":null},{"id":"2208.09163","title":"UniCausal: Unified Benchmark and Repository for Causal Text Mining","created":"2022-08-19","cited_by_count":10,"area":null},{"id":"2411.10371","title":"A Survey of Event Causality Identification: Taxonomy, Challenges, Assessment, and Prospects","created":"2024-11-15","cited_by_count":6,"area":null},{"id":"2108.12626","title":"HeadlineCause: A Dataset of News Headlines for Detecting Causalities","created":"2021-08-28","cited_by_count":5,"area":null},{"id":"2406.19307","title":"The Odyssey of Commonsense Causality: From Foundational Benchmarks to Cutting-Edge Reasoning","created":"2024-06-27","cited_by_count":5,"area":null},{"id":"2209.06367","title":"A Review and Roadmap of Deep Learning Causal Discovery in Different Variable Paradigms","created":"2022-09-14","cited_by_count":4,"area":null},{"id":"2211.12154","title":"Event Causality Identification with Causal News Corpus -- Shared Task 3, CASE 2022","created":"2022-11-22","cited_by_count":4,"area":null},{"id":"2104.00814","title":"CURIE: An Iterative Querying Approach for Reasoning About Situations","created":"2021-04-01","cited_by_count":3,"area":null},{"id":"2108.03087","title":"Detecting Requirements Smells With Deep Learning: Experiences, Challenges and Future Work","created":"2021-08-06","cited_by_count":2,"area":null},{"id":"2107.09980","title":"Fine-Grained Causality Extraction From Natural Language Requirements Using Recursive Neural Tensor Networks","created":"2021-07-21","cited_by_count":1,"area":null},{"id":"2102.09923","title":"Back to Prior Knowledge: Joint Event Causality Extraction via Convolutional Semantic Infusion","created":"2021-02-19","cited_by_count":0,"area":null},{"id":"2409.04934","title":"Maximizing Relation Extraction Potential: A Data-Centric Study to Unveil Challenges and Opportunities","created":"2024-09-07","cited_by_count":0,"area":null},{"id":"2512.11108","title":"Explanation Bias is a Product: Revealing the Hidden Lexical and Position Preferences in Post-Hoc Feature Attribution","created":"2025-12-11","cited_by_count":0,"area":null},{"id":"2604.06902","title":"iTAG: Inverse Design for Natural Text Generation with Accurate Causal Graph Annotations","created":"2026-04-08","cited_by_count":0,"area":null}],"next_cursor":null}