1 citations · 1 across the 6 of their papers we have counts for
6 papers
Paved with True Intents: Intent-Aware Training Improves LLM Safety Classification Across Training Regimes
Jeremias Ferrao, Niclas Müller-Hof, Iustin Sîrbu +2
We argue that safety classifiers should model user intent as an explicit signal between the prompt and the final label. To study this, we introduce AIMS, a human-annotated dataset…
What Really Counts? Examining Step and Token Level Attribution in Multilingual CoT Reasoning
Jeremias Ferrao, Ezgi Basar, Khondoker Ittehadul Islam +1
This study investigates the attribution patterns underlying Chain-of-Thought (CoT) reasoning in multilingual LLMs. While prior works demonstrate the role of CoT prompting in improv…
The Anatomy of Alignment: Decomposing Preference Optimization by Steering Sparse Features
Jeremias Ferrao, Matthijs van der Lende, Ilija Lichkovski +1
Prevailing alignment methods induce opaque parameter changes, obscuring what models truly learn. To address this, we introduce Feature Steering with Reinforcement Learning (FSRL),…
Self-Ablating Transformers: More Interpretability, Less Sparsity
Jeremias Ferrao, Luhan Mikaelson, Keenan Pepper +1
A growing intuition in machine learning suggests a link between sparsity and interpretability. We introduce a novel self-ablation mechanism to investigate this connection ante-hoc…
Evaluating Uncertainty in Deep Gaussian Processes
Matthijs van der Lende, Jeremias Lino Ferrao, Niclas Müller-Hof
Reliable uncertainty estimates are crucial in modern machine learning. Deep Gaussian Processes (DGPs) and Deep Sigma Point Processes (DSPPs) extend GPs hierarchically, offering pro…
World Model Agents with Change-Based Intrinsic Motivation
Jeremias Ferrao, Rafael Cunha
Sparse reward environments pose a significant challenge for reinforcement learning due to the scarcity of feedback. Intrinsic motivation and transfer learning have emerged as promi…