반응형 논문572 [2023-04-02] 오늘의 자연어처리 Hindi as a Second Language: Improving Visually Grounded Speech with Semantically Similar Samples The objective of this work is to explore the learning of visually grounded speech models (VGS) from multilingual perspective. Bilingual VGS models are generally trained with an equal number of spoken captions from both languages. However, in reality, there can be an imbalance among the languages for .. 2023. 4. 2. [2023-04-01] 오늘의 자연어처리 Language Models can Solve Computer Tasks Agents capable of carrying out general tasks on a computer can improve efficiency and productivity by automating repetitive tasks and assisting in complex problem-solving. Ideally, such agents should be able to solve new computer tasks presented to them through natural language commands. However, previous approaches to this problem require large amounts o.. 2023. 4. 1. [2023-03-31] 오늘의 자연어처리 LMExplainer: a Knowledge-Enhanced Explainer for Language Models Large language models (LMs) such as GPT-4 are very powerful and can process different kinds of natural language processing (NLP) tasks. However, it can be difficult to interpret the results due to the multi-layer nonlinear model structure and millions of parameters. Lack of understanding of how the model works can make the model unr.. 2023. 3. 31. [2023-03-30] 오늘의 자연어처리 Summarizing Indian Languages using Multilingual Transformers based Models With the advent of multilingual models like mBART, mT5, IndicBART etc., summarization in low resource Indian languages is getting a lot of attention now a days. But still the number of datasets is low in number. In this work, we (Team HakunaMatata) study how these multilingual models perform on the datasets which have Indi.. 2023. 3. 30. 이전 1 ··· 71 72 73 74 75 76 77 ··· 143 다음 반응형