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20242026
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cs.CL2026

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…

cs.CL2025

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…

cs.CL2025

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…

cs.CL2024

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…

cs.CL2024

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…

cs.CL2024

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…