Summary of Nl2formula: Generating Spreadsheet Formulas From Natural Language Queries, by Wei Zhao et al.
NL2Formula: Generating Spreadsheet Formulas from Natural Language Queries
by Wei Zhao, Zhitao Hou, Siyuan Wu, Yan Gao, Haoyu Dong, Yao Wan, Hongyu Zhang, Yulei Sui, Haidong Zhang
First submitted to arxiv on: 20 Feb 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This paper proposes a novel benchmark task called NL2Formula to generate executable spreadsheet formulas from natural language queries. The authors introduce a comprehensive dataset of 70,799 paired NL queries and corresponding spreadsheet formulas, covering various table structures and formula functions. They provide a sequence-to-sequence baseline implementation called fCoder, which outperforms other models in experimental results. The study also compares fCoder with an initial GPT-3.5 model, highlighting the potential challenges in the NL2Formula task. This paper contributes to improving the automation of spreadsheet formula writing and reducing the error-prone process. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper helps computers write formulas on spreadsheets better. People often have a hard time creating formulas by hand because it can be tricky and prone to mistakes. To solve this problem, the researchers created a special task called NL2Formula that translates natural language queries into spreadsheet formulas. They made a big dataset with lots of examples and tested different models to see which one worked best. The results showed that their model was better at writing formulas than others. This study can help make it easier for people to use spreadsheets without getting frustrated. |
Keywords
» Artificial intelligence » Gpt
