30 citations · 96 across the 31 of their papers we have counts for
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cs.LG2026
Understanding Helpfulness and Harmless Tension in Reward Models
Eshaan Tanwar, Pepa Atanasova
Reward models (RMs) are a key component of reinforcement learning from human feedback, enabling the alignment of large language models with human values such as helpfulness and har…
cs.LG2022★ 2 cited
Accountable and Explainable Methods for Complex Reasoning over Text
Pepa Atanasova
A major concern of Machine Learning (ML) models is their opacity. They are deployed in an increasing number of applications where they often operate as black boxes that do not prov…
cs.LG2021
Diagnostics-Guided Explanation Generation
Pepa Atanasova, Jakob Grue Simonsen, Christina Lioma +1
Explanations shed light on a machine learning model's rationales and can aid in identifying deficiencies in its reasoning process. Explanation generation models are typically train…