13 citations · 17 across the 7 of their papers we have counts for
3 papers · 1 filter
Adaptive Retrieval Without Self-Knowledge? Bringing Uncertainty Back Home
Viktor Moskvoretskii, Maria Lysyuk, Mikhail Salnikov +7
Retrieval Augmented Generation (RAG) improves correctness of Question Answering (QA) and addresses hallucinations in Large Language Models (LLMs), yet greatly increase computationa…
Argument-Based Comparative Question Answering Evaluation Benchmark
Irina Nikishina, Saba Anwar, Nikolay Dolgov +6
In this paper, we aim to solve the problems standing in the way of automatic comparative question answering. To this end, we propose an evaluation framework to assess the quality o…
Investigating the Impact of Quantization Methods on the Safety and Reliability of Large Language Models
Artyom Kharinaev, Viktor Moskvoretskii, Egor Shvetsov +3
Large Language Models (LLMs) are powerful tools for modern applications, but their computational demands limit accessibility. Quantization offers efficiency gains, yet its impact o…