ChatGPT can produce synthetic system requirement specifications that 62 percent of experts rate as realistic, though the outputs contain contradictions and deficiencies.
Reasoning with large language models, a survey
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TableMaster improves LM table understanding by verbalizing tables with enriched semantics and using adaptive textual-symbolic reasoning, reaching 78.13% accuracy on WikiTQ with GPT-4o-mini.
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Can ChatGPT Generate Realistic Synthetic System Requirement Specifications? Results of a Case Study
ChatGPT can produce synthetic system requirement specifications that 62 percent of experts rate as realistic, though the outputs contain contradictions and deficiencies.
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TableMaster: A Recipe to Advance Table Understanding with Language Models
TableMaster improves LM table understanding by verbalizing tables with enriched semantics and using adaptive textual-symbolic reasoning, reaching 78.13% accuracy on WikiTQ with GPT-4o-mini.