Search Results for author: Lorenzo Jaime Yu Flores

Found 6 papers, 6 papers with code

On the Benefits of Fine-Grained Loss Truncation: A Case Study on Factuality in Summarization

1 code implementation9 Mar 2024 Lorenzo Jaime Yu Flores, Arman Cohan

We study the behavior of the underlying losses between factual and non-factual examples, to understand and refine the performance of LT. We demonstrate that LT's performance is limited when the underlying assumption that noisy targets have higher NLL loss is not satisfied, and find that word-level NLL among entities provides better signal for distinguishing factuality.

Hallucination Text Summarization

Medical Text Simplification: Optimizing for Readability with Unlikelihood Training and Reranked Beam Search Decoding

1 code implementation17 Oct 2023 Lorenzo Jaime Yu Flores, Heyuan Huang, Kejian Shi, Sophie Chheang, Arman Cohan

Text simplification has emerged as an increasingly useful application of AI for bridging the communication gap in specialized fields such as medicine, where the lexicon is often dominated by technical jargon and complex constructs.

Text Simplification

Look Ma, Only 400 Samples! Revisiting the Effectiveness of Automatic N-Gram Rule Generation for Spelling Normalization in Filipino

1 code implementation6 Oct 2022 Lorenzo Jaime Yu Flores, Dragomir Radev

With 84. 75 million Filipinos online, the ability for models to process online text is crucial for developing Filipino NLP applications.

Spelling Correction

An Adversarial Benchmark for Fake News Detection Models

1 code implementation AAAI Workshop AdvML 2022 Lorenzo Jaime Yu Flores, Yiding Hao

With the proliferation of online misinformation, fake news detection has gained importance in the artificial intelligence community.

Fact Checking Fake News Detection +1

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