4 papers
Monitor-Generate-Verify (MGV): Formalising Metacognitive Theory for Language Model Reasoning
Nick Oh, Fernand Gobet
Test-time reasoning architectures such as those following the Generate-Verify paradigm, where a model iteratively refines or verifies its own generated outputs, prioritise generati…
Before you <think>, monitor: Implementing Flavell's metacognitive framework in LLMs
Nick Oh
Current approaches to enhancing LLM reasoning follows two isolated paradigms: Monitor-Generate methods like Plan-and-Solve (Wang et al., 2023) and SELF-DISCOVER (Zhou et al., 2024)…
PETLP: A Privacy-by-Design Pipeline for Social Media Data in AI Research
Nick Oh, Giorgos D. Vrakas, Siân J. M. Brooke +2
Social media data presents AI researchers with overlapping obligations under the GDPR, copyright law, and platform terms -- yet existing frameworks fail to integrate these regulato…
In Defence of Post-hoc Explainability
Nick Oh
This position paper defends post-hoc explainability methods as legitimate tools for scientific knowledge production in machine learning. Addressing criticism of these methods' reli…