Large language models (eg, GPT-4) are uniquely capable of producing highly rated text
simplification, yet current human evaluation methods fail to provide a clear understanding of …

Factuality is important to dialogue summarization. Factual error correction (FEC) of model-
generated summaries is one way to improve factuality. Current FEC evaluation that relies on …

Factual error correction (FEC) aims to revise factual errors in false claims with minimal
editing, making them faithful to the provided evidence. This task is crucial for alleviating the …

Due to the prohibitively high cost of creating error correction datasets, most Factual Claim
Correction methods rely on a powerful verification model to guide the correction process …

Due to the prohibitively high cost of creating error correction datasets, most Factual Claim
Correction methods rely on a powerful verification model to guide the correction process …

Due to the prohibitively high cost of creating error correction datasets, most Factual Claim
Correction methods rely on a powerful verification model to guide the correction process …