Titlebook: Recent Trends in Analysis of Images, Social Networks and Texts; 11th International C Dmitry I. Ignatov,Michael Khachay,Sergey Zagoruyko Con

GRIEF

cumulative

Ophthalmoscope

Whether Large Language Models Learn at the Inference Stage? Effects of Active Learning and Labellingd recently, in connection with the discovered possibility of Large Language Models (LLMs) based on examples (and in particular demonstrations of instructions, some actions with examples, including demonstration of reasoning) to solve certain types of problems at the Inference stage, without the need

AGATE

Machine Translation for Russian-Khakas Language Pair: Translation Results in Low-Resource Settingws that using the Russian-Chuvash language pair for pre-training can significantly improve the model’s performance. The study describes the process of collecting and preprocessing the data, tokenization, training and evaluation of the results.

surrogate

委托

Negotiate

Tuning-Free Discriminative Nearest Neighbor Few-Shot Intent Detection via Consecutive Knowledge Tranenging because of limited data availability. In this study, we aim to develop a few-shot intent classification model capable of OOS detection that does not require fine-tuning on target data. We adopt the discriminative nearest neighbor classification architecture and replace the fine-tuning phase w

Jejune

Postulate

树胶