activity
20192026
most citedExplainable Natural Language Processing for Corporate Sustainability Analysis

25 citations · 100 across the 18 of their papers we have counts for

collaborators
Showing 2025Show all

5 papers · 1 filter

cs.CL2025

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.CR2025

Mitigating Jailbreaks with Intent-Aware LLMs

Wei Jie Yeo, Ranjan Satapathy, Erik Cambria

Despite extensive safety-tuning, large language models (LLMs) remain vulnerable to jailbreak attacks via adversarially crafted instructions, reflecting a persistent trade-off betwe…

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.CV2025

Debiasing CLIP: Interpreting and Correcting Bias in Attention Heads

Wei Jie Yeo, Rui Mao, Moloud Abdar +2

Multimodal models like CLIP have gained significant attention due to their remarkable zero-shot performance across various tasks. However, studies have revealed that CLIP can inadv…

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…