24 citations · 26 across the 4 of their papers we have counts for
4 papers
Beyond I'm Sorry, I Can't: Dissecting Large Language Model Refusal
Nirmalendu Prakash, Yeo Wei Jie, Amir Abdullah +3
Refusal on harmful prompts is a key safety behaviour in instruction-tuned large language models (LLMs), yet the internal causes of this behaviour remain poorly understood. We study…
SusGen-GPT: A Data-Centric LLM for Financial NLP and Sustainability Report Generation
Qilong Wu, Xiaoneng Xiang, Hejia Huang +5
The rapid growth of the financial sector and the rising focus on Environmental, Social, and Governance (ESG) considerations highlight the need for advanced NLP tools. However, open…
How Interpretable are Reasoning Explanations from Prompting Large Language Models?
Wei Jie Yeo, Ranjan Satapathy, Rick Siow Mong Goh +1
Prompt Engineering has garnered significant attention for enhancing the performance of large language models across a multitude of tasks. Techniques such as the Chain-of-Thought no…
Plausible Extractive Rationalization through Semi-Supervised Entailment Signal
Wei Jie Yeo, Ranjan Satapathy, Erik Cambria
The increasing use of complex and opaque black box models requires the adoption of interpretable measures, one such option is extractive rationalizing models, which serve as a more…