Interpreting Context Look-ups in Transformers: Investigating Attention-MLP Interactions. - Clement Neo; Shay B. Cohen; Fazl Barez (EMNLP, 2024)

Interpreting Learned Feedback Patterns in Large Language Models. - Luke Marks; Amir Abdullah; Clement Neo; Rauno Arike; David Krueger 001; Philip Torr 001; Fazl Barez (NeurIPS, 2024)

Increasing Trust in Language Models through the Reuse of Verified Circuits. - Philip Quirke; Clement Neo; Fazl Barez (CoRR, 2024)

Min P Sampling: Balancing Creativity and Coherence at High Temperature. - Minh Nguyen; Andrew Baker; Andreas Kirsch 004; Clement Neo (CoRR, 2024)

Benchmark Inflation: Revealing LLM Performance Gaps Using Retro-Holdouts. - Jacob Haimes; Cenny Wenner; Kunvar Thaman; Vassil Tashev; Clement Neo; Esben Kran; Jason Schreiber (CoRR, 2024)

Turning Up the Heat: Min-p Sampling for Creative and Coherent LLM Outputs. - Nguyen Nhat Minh; Andrew Baker; Clement Neo; Allen G. Roush; Andreas Kirsch 004; Ravid Shwartz-Ziv (ICLR, 2025)

Towards Interpreting Visual Information Processing in Vision-Language Models. - Clement Neo; Luke Ong; Philip Torr 001; Mor Geva; David Krueger 001; Fazl Barez (ICLR, 2025)

TinySQL: A Progressive Text-to-SQL Dataset for Mechanistic Interpretability Research. - Philip Quirke; Clement Neo; Abir Harrasse; Dhruv Nathawani; Amir Abdullah (CoRR, 2025)

Understanding Refusal in Language Models with Sparse Autoencoders. - Wei Jie Yeo; Nirmalendu Prakash; Clement Neo; Roy Ka-Wei Lee; Erik Cambria; Ranjan Satapathy (CoRR, 2025)

Beyond Monoliths: Expert Orchestration for More Capable, Democratic, and Safe Large Language Models. - Philip Quirke; Narmeen Oozeer; Chaithanya Bandi; Amir Abdullah; Jason Hoelscher-Obermaier; Jeff M. Phillips; Joshua Greaves; Clement Neo; Fazl Barez; Shriyash Upadhyay (CoRR, 2025)