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Are Hard Examples also Harder to Explain? A Study with Human and Model-Generated Explanations.

, , , and . EMNLP, page 2121-2131. Association for Computational Linguistics, (2022)

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MURMUR: Modular Multi-Step Reasoning for Semi-Structured Data-to-Text Generation., , , , and . ACL (Findings), page 11069-11090. Association for Computational Linguistics, (2023)Bootstrapping for Numerical Open IE., , and . ACL (2), page 317-323. Association for Computational Linguistics, (2017)Creating Scoring Rubric from Representative Student Answers for Improved Short Answer Grading., , , , , and . CIKM, page 993-1002. ACM, (2018)PRover: Proof Generation for Interpretable Reasoning over Rules., , , and . EMNLP (1), page 122-136. Association for Computational Linguistics, (2020)MAGDi: Structured Distillation of Multi-Agent Interaction Graphs Improves Reasoning in Smaller Language Models., , , and . ICML, OpenReview.net, (2024)Open Information Extraction from Conjunctive Sentences., and . COLING, page 2288-2299. Association for Computational Linguistics, (2018)System-1.x: Learning to Balance Fast and Slow Planning with Language Models., , , , , and . CoRR, (2024)Balancing Human Efforts and Performance of Student Response Analyzer in Dialog-Based Tutors., , , , and . AIED (1), volume 10947 of Lecture Notes in Computer Science, page 70-85. Springer, (2018)Branch-Solve-Merge Improves Large Language Model Evaluation and Generation., , , , , and . CoRR, (2023)Pre-Training BERT on Domain Resources for Short Answer Grading., , , , , and . EMNLP/IJCNLP (1), page 6070-6074. Association for Computational Linguistics, (2019)