Papers with human quality control
ReportGPT: Human-in-the-loop Verifiable Table-to-Text Generation (2024.emnlp-industry)
Copied to clipboard
| Challenge: | Recent advances in the quality and accessibility of large language models have precipitated a surge in user-facing tools for content generation. |
| Approach: | They propose a pipeline framework for verifiable human-in-the-loop table-to-text generation that is based on a domain specific language and a set of modules that use it as a representation for generating verifierable commentary. |
| Outcome: | The proposed framework learns from human feedback in real-time, needing only a few samples to improve performance. |