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Erik Cambria

18 papers hereh-index 6213 citations20 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author10
  • last author5

Across the 15 of 18 papers where every author was matched, so the position is known.

fields
  • cs.CL12
  • cs.AI2
  • cs.CR1
  • cs.CV1
  • cs.IR1
  • cs.LG1
same name
  • Erik Cambria — 26 papers, h 20
  • Erik Cambria — 11 papers, h 3
  • Erik Cambria — 7 papers, h 5
  • Erik Cambria — 6 papers, h 6
  • Erik Cambria — 6 papers, h 15
  • Erik Cambria — 5 papers, h 3

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20232026
most citedHow Interpretable are Reasoning Explanations from Prompting Large Language Models?

24 citations · 40 across the 17 of their papers we have counts for

collaborators
Showing 2025Show all

4 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…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.