Text Revision By On-the-Fly Representation Optimization
Authors: Jingjing Li, Zichao Li, Tao Ge, Irwin King, Michael R. Lyu10956-10964
AAAI 2022 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | The empirical experiments on two typical and important text revision tasks, text formalization and text simplification, show the effectiveness of our approach. |
| Researcher Affiliation | Collaboration | Jingjing Li1, Zichao Li2, Tao Ge3, Irwin King1, Michael R. Lyu1 1The Chinese University of Hong Kong 2Mila/Mc Gill University 3Microsoft Research Asia |
| Pseudocode | Yes | Algorithm 1: Text revision with OREO |
| Open Source Code | Yes | Our code and model are released at https://github.com/jingjingli01/OREO. |
| Open Datasets | Yes | Based on the widely used corpora Newsela (Xu, Callison-Burch, and Napoles 2015), Jiang et al. (2020) constructs a reliable corpus consisting of 666K complex-simple sentence pairs1. 1Dataset available at https://github.com/chaojiang06/wiki-auto. ... We experimented with the domain of Family & Relationships in Grammarly s Yahoo Answers Formality Corpus (GYAFC-fr) (Rao and Tetreault 2018). |
| Dataset Splits | Yes | The final dataset consists of 269K train, 28K development and 29K test sentences. ... There are 100K, 5K and 2.5K informal-formal2 pairs in GYAFC. |
| Hardware Specification | Yes | It takes 8-GPU hours to fine-tune Ro BERTa on one Tesla V100 for both tasks. |
| Software Dependencies | No | The paper states, 'We implement Ro BERTa based on Huggingface transformers (Wolf et al. 2020).' While it names a library and cites a paper for it, it does not provide specific version numbers for the software dependencies needed for replication. |
| Experiment Setup | Yes | We primarily adopted the default hyperparameters with a fixed learning rate of 5e-5. The numbers of fine-tuning epochs are 6 and 2 for text simplification and formalization, respectively. ... The maximum iteration I was set to 4... λ was selected from {0.8, 1.2, 1.6, 2.0} and set to 1.6. ... The attribute threshold δ is task-dependent. It was selected from from {0.1, 0.2, . . . , 0.5} and set to 0.5 for text simplification and 0.3 for text formalization. K = 1 for both tasks. |