28 citations · 72 across the 55 of their papers we have counts for
4 papers · 2 filters
Why Summaries Turn Neutral: Policy Attribution for Sentiment Drift in Reinforcement Learning from Human Feedback
Mikhail Krasitskii, Alexander Gelbukh, Olga Kolesnikova +1
Reinforcement learning with human feedback (RLHF) aligns LLMs with human preferences, improving summarization fluency and safety, but causes sentiment drift: overly neutral summari…
Multiclass Sentiment Analysis for Identifying Political Viewpoints
Girma Yohannis Bade, Olga Kolesnikova, Jose Luis Oropeza +1
The rapid growth of social media has created vast amounts of political discourse, which provides valuable opportunities to analyze public opinions and identify different political…
Multilingual Sentiment Aware Text Summarization A Reinforcement Learning Approach for Consistency Maintenance
Mikhail Krasitskii, Alexander Gelbukh, Olga Kolesnikova +1
Reinforcement Learning from Human Feedback (RLHF) has significantly improved the quality and fluency of large language models in text summarization. However, its impact on affectiv…
How Psychological Learning Paradigms Shaped and Constrained Artificial Intelligence
Alex Anvi Eponon, Ildar Batyrshin, Christian E. Maldonado-Sifuentes +1
Current artificial intelligence systems struggle with systematic compositional reasoning: the capacity to recombine known components in novel configurations. This paper argues that…