2 citations · 7 across the 10 of their papers we have counts for
3 papers · 1 filter
Answer Candidate Type Selection: Text-to-Text Language Model for Closed Book Question Answering Meets Knowledge Graphs
Mikhail Salnikov, Maria Lysyuk, Pavel Braslavski +3
Pre-trained Text-to-Text Language Models (LMs), such as T5 or BART yield promising results in the Knowledge Graph Question Answering (KGQA) task. However, the capacity of the model…
Kandinsky: an Improved Text-to-Image Synthesis with Image Prior and Latent Diffusion
Anton Razzhigaev, Arseniy Shakhmatov, Anastasia Maltseva +7
Text-to-image generation is a significant domain in modern computer vision and has achieved substantial improvements through the evolution of generative architectures. Among these,…
Large Language Models Meet Knowledge Graphs to Answer Factoid Questions
Mikhail Salnikov, Hai Le, Prateek Rajput +4
Recently, it has been shown that the incorporation of structured knowledge into Large Language Models significantly improves the results for a variety of NLP tasks. In this paper,…