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Journal of Didactic Mathematics, 2023 Matematika dan ...
Cover And Table of Content
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Table Meets LLM: Can Large Language Models Understand Structured Table Data? A Benchmark and Empirical Study [PDF]
Web Search and Data Mining, 2023 Large language models (LLMs) are becoming attractive as few-shot reasoners to solve Natural Language (NL)-related tasks. However, there is still much to learn about how well LLMs understand structured data, such as tables.
Yuan Sui +4 more
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RobuT: A Systematic Study of Table QA Robustness Against Human-Annotated Adversarial Perturbations [PDF]
Annual Meeting of the Association for Computational Linguistics, 2023 Despite significant progress having been made in question answering on tabular data (Table QA), it’s unclear whether, and to what extent existing Table QA models are robust to task-specific perturbations, e.g., replacing key question entities or ...
Yilun Zhao +7 more
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LoFT: Enhancing Faithfulness and Diversity for Table-to-Text Generation via Logic Form Control [PDF]
Conference of the European Chapter of the Association for Computational Linguistics, 2023 Logical Table-to-Text (LT2T) generation is tasked with generating logically faithful sentences from tables. There currently exists two challenges in the field: 1) Faithfulness: how to generate sentences that are factually correct given the table content;
Yilun Zhao +4 more
semanticscholar +1 more source
Front Cover, Publication Information [PDF]
, 1974 Front Cover, Publication Information, Table of ...
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