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3 papers
Concepts' Information Bottleneck Models
Karim Galliamov, Syed M Ahsan Kazmi, Adil Khan +1
Concept Bottleneck Models (CBMs) aim to deliver interpretable predictions by routing decisions through a human-understandable concept layer, yet they often suffer reduced accuracy…
Enhancing RLHF with Human Gaze Modeling
Karim Galliamov, Ivan Titov, Ilya Pershin
Reinforcement Learning from Human Feedback (RLHF) aligns language models with human preferences but is computationally expensive. We explore two approaches that leverage human gaze…
Refining Joint Text and Source Code Embeddings for Retrieval Task with Parameter-Efficient Fine-Tuning
Karim Galliamov, Leila Khaertdinova, Karina Denisova
The latest developments in Natural Language Processing (NLP) have demonstrated remarkable progress in a code-text retrieval problem. As the Transformer-based models used in this ta…