4 papers · 1 filter
Pre-training interventions, ex post facto: Grafting model beliefs across checkpoints
Peter Nutter, Dani Roytburg, Clément Dumas +2
Pre-training interventions are critical to alignment research, since beliefs formed during pre-training shape how a model generalizes from later training. One recently popular tech…
Diff Mining: Logit Differences Reveal Finetuning Objectives
Greg Kocher, Robert West, Clément Dumas +1
Finetuning has become the gold standard for refining existing behaviors and inducing new ones in language models, yet it often remains unclear exactly which behaviors emerge during…
nnterp: A Standardized Interface for Mechanistic Interpretability of Transformers
Clément Dumas
Mechanistic interpretability research requires reliable tools for analyzing transformer internals across diverse architectures. Current approaches face a fundamental tradeoff: cust…
Overcoming Sparsity Artifacts in Crosscoders to Interpret Chat-Tuning
Julian Minder, Clément Dumas, Caden Juang +2
Model diffing is the study of how fine-tuning changes a model's representations and internal algorithms. Many behaviors of interest are introduced during fine-tuning, and model dif…