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LoFT: Enhancing Faithfulness and Diversity for Table-to-Text Generation via Logic Form Control., , , , and . EACL, page 554-561. Association for Computational Linguistics, (2023)ReasTAP: Injecting Table Reasoning Skills During Pre-training via Synthetic Reasoning Examples., , , , and . EMNLP, page 9006-9018. Association for Computational Linguistics, (2022)RobuT: A Systematic Study of Table QA Robustness Against Human-Annotated Adversarial Perturbations., , , , , , , and . ACL (1), page 6064-6081. Association for Computational Linguistics, (2023)MedAgents: Large Language Models as Collaborators for Zero-shot Medical Reasoning., , , , , , and . CoRR, (2023)Investigating Data Contamination in Modern Benchmarks for Large Language Models., , , , and . CoRR, (2023)ML-Bench: Large Language Models Leverage Open-source Libraries for Machine Learning Tasks., , , , , , , , , and 16 other author(s). CoRR, (2023)Q-GPU: A Recipe of Optimizations for Quantum Circuit Simulation Using GPUs., , , , , , , , , and . HPCA, page 726-740. IEEE, (2022)FOLIO: Natural Language Reasoning with First-Order Logic., , , , , , , , , and 16 other author(s). CoRR, (2022)QTSumm: Query-Focused Summarization over Tabular Data., , , , , , , , , and 2 other author(s). EMNLP, page 1157-1172. Association for Computational Linguistics, (2023)Towards Interpretable and Efficient Automatic Reference-Based Summarization Evaluation., , , , , , , and . EMNLP, page 16360-16368. Association for Computational Linguistics, (2023)