25 citations · 100 across the 18 of their papers we have counts for
11 papers · 1 filter
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…
Understanding Refusal in Language Models with Sparse Autoencoders
Wei Jie Yeo, Nirmalendu Prakash, Clement Neo +3
Refusal is a key safety behavior in aligned language models, yet the internal mechanisms driving refusals remain opaque. In this work, we conduct a mechanistic study of refusal in…
ESGSenticNet: A Neurosymbolic Knowledge Base for Corporate Sustainability Analysis
Keane Ong, Rui Mao, Deeksha Varshney +5
Evaluating corporate sustainability performance is essential to drive sustainable business practices, amid the need for a more sustainable economy. However, this is hindered by the…
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…
Towards Faithful Natural Language Explanations: A Study Using Activation Patching in Large Language Models
Wei Jie Yeo, Ranjan Satapathy, Erik Cambria
Large Language Models (LLMs) are capable of generating persuasive Natural Language Explanations (NLEs) to justify their answers. However, the faithfulness of these explanations sho…
Self-training Large Language Models through Knowledge Detection
Wei Jie Yeo, Teddy Ferdinan, Przemyslaw Kazienko +2
Large language models (LLMs) often necessitate extensive labeled datasets and training compute to achieve impressive performance across downstream tasks. This paper explores a self…
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…
FinXABSA: Explainable Finance through Aspect-Based Sentiment Analysis
Keane Ong, Wihan van der Heever, Ranjan Satapathy +2
This paper presents a novel approach for explainability in financial analysis by deriving financially-explainable statistical relationships through aspect-based sentiment analysis,…
Polarity and Subjectivity Detection with Multitask Learning and BERT Embedding
Ranjan Satapathy, Shweta Pardeshi, Erik Cambria
Multitask learning often helps improve the performance of related tasks as these often have inter-dependence on each other and perform better when solved in a joint framework. In t…
PhonSenticNet: A Cognitive Approach to Microtext Normalization for Concept-Level Sentiment Analysis
Ranjan Satapathy, Aalind Singh, Erik Cambria
With the current upsurge in the usage of social media platforms, the trend of using short text (microtext) in place of standard words has seen a significant rise. The usage of micr…