Artificial Intelligence Research
Artificial intelligence (AI) research aims to create intelligent agents capable of complex tasks, currently focusing on improving reasoning, planning, and multimodal capabilities. This involves developing and refining model architectures like Large Language Models (LLMs) and Large Reasoning Models (LRMs), often employing techniques such as instruction tuning and reinforcement learning. The field's significance lies in its potential to revolutionize various sectors, from healthcare and gaming to autonomous systems and scientific discovery, while simultaneously raising crucial ethical and societal considerations regarding safety, fairness, and reproducibility.
Papers
Concept Alignment
Sunayana Rane, Polyphony J. Bruna, Ilia Sucholutsky, Christopher Kello, Thomas L. Griffiths
MERA: A Comprehensive LLM Evaluation in Russian
Alena Fenogenova, Artem Chervyakov, Nikita Martynov, Anastasia Kozlova, Maria Tikhonova, Albina Akhmetgareeva, Anton Emelyanov, Denis Shevelev, Pavel Lebedev, Leonid Sinev, Ulyana Isaeva, Katerina Kolomeytseva, Daniil Moskovskiy, Elizaveta Goncharova, Nikita Savushkin, Polina Mikhailova, Denis Dimitrov, Alexander Panchenko, Sergei Markov
Big Tech influence over AI research revisited: memetic analysis of attribution of ideas to affiliation
Stanisław Giziński, Paulina Kaczyńska, Hubert Ruczyński, Emilia Wiśnios, Bartosz Pieliński, Przemysław Biecek, Julian Sienkiewicz
Mini-GPTs: Efficient Large Language Models through Contextual Pruning
Tim Valicenti, Justice Vidal, Ritik Patnaik