14 citations · 19 across the 7 of their papers we have counts for
6 papers · 1 filter
Can Confidence Estimates Decide When Chain-of-Thought Is Necessary for LLMs?
Samuel Lewis-Lim, Xingwei Tan, Zhixue Zhao +1
Chain-of-thought (CoT) prompting is a common technique for improving the reasoning abilities of large language models (LLMs). However, extended reasoning is often unnecessary and s…
Comparing Explanation Faithfulness between Multilingual and Monolingual Fine-tuned Language Models
Zhixue Zhao, Nikolaos Aletras
In many real natural language processing application scenarios, practitioners not only aim to maximize predictive performance but also seek faithful explanations for the model pred…
Investigating Hallucinations in Pruned Large Language Models for Abstractive Summarization
George Chrysostomou, Zhixue Zhao, Miles Williams +1
Despite the remarkable performance of generative large language models (LLMs) on abstractive summarization, they face two significant challenges: their considerable size and tenden…
Incorporating Attribution Importance for Improving Faithfulness Metrics
Zhixue Zhao, Nikolaos Aletras
Feature attribution methods (FAs) are popular approaches for providing insights into the model reasoning process of making predictions. The more faithful a FA is, the more accurate…
On the Impact of Temporal Concept Drift on Model Explanations
Zhixue Zhao, George Chrysostomou, Kalina Bontcheva +1
Explanation faithfulness of model predictions in natural language processing is typically evaluated on held-out data from the same temporal distribution as the training data (i.e.…
SS-BERT: Mitigating Identity Terms Bias in Toxic Comment Classification by Utilising the Notion of "Subjectivity" and "Identity Terms"
Zhixue Zhao, Ziqi Zhang, Frank Hopfgartner
Toxic comment classification models are often found biased toward identity terms which are terms characterizing a specific group of people such as "Muslim" and "black". Such bias i…