4 papers · 1 filter
Understanding and Mitigating Dataset Corruption in LLM Steering
Cullen Anderson, Narmeen Oozeer, Foad Namjoo +3
Contrastive steering has been shown as a simple and effective method to adjust the generative behavior of LLMs at inference time. It uses examples of prompt responses with and with…
DreamReader: An Interpretability Toolkit for Text-to-Image Models
Nirmalendu Prakash, Narmeen Oozeer, Michael Lan +6
Despite the rapid adoption of text-to-image (T2I) diffusion models, causal and representation-level analysis remains fragmented and largely limited to isolated probing techniques.…
TinySQL: A Progressive Text-to-SQL Dataset for Mechanistic Interpretability Research
Abir Harrasse, Philip Quirke, Clement Neo +3
Mechanistic interpretability research faces a gap between analyzing simple circuits in toy tasks and discovering features in large models. To bridge this gap, we propose text-to-SQ…
Distribution-Aware Feature Selection for SAEs
Narmeen Oozeer, Nirmalendu Prakash, Michael Lan +2
Sparse autoencoders (SAEs) decompose neural activations into interpretable features. A widely adopted variant, the TopK SAE, reconstructs each token from its K most active latents.…