Papers with PARENT metric
uFACT: Unfaithful Alien-Corpora Training for Semantically Consistent Data-to-Text Generation (2022.findings-acl)
Copied to clipboard
| Challenge: | uFACT (Un-Faithful Alien Corpora Training) is a training corpus construction method for data-to-text generation models. |
| Approach: | They propose a training corpus construction method for data-to-text (d2t) generation models which augments a target corpus with alien corpora which have different semantic representations. |
| Outcome: | The proposed method generates utterances which represent the semantic content of the data sources more accurately compared to models trained on the target corpus alone. |
ReTAG: Reasoning Aware Table to Analytic Text Generation (2023.emnlp-main)
Copied to clipboard
| Challenge: | Table to text models generate descriptive summaries that repeat information contained within a table in sentences. |
| Approach: | They propose a table-aware table-to-text model that uses vector-quantization to infuse different types of analytical reasoning into the output. |
| Outcome: | The proposed model achieves 2.2%, 2.9% improvement on PARENT metric over state-of-the-art models. |