The Inception Team at NSURL-2019 Task 8: Semantic Question Similarity in Arabic

NSURL-2019 Shared Task 8: Semantic Question Similarity in Arabic

Question semantic similarity (Q2Q) is a challenging task that is very useful in many NLP applications, such as detecting duplicate questions and question answering systems. In this paper, we present the results and findings of the shared task (Semantic Question Similarity in Arabic). The task was organized as part of the first workshop on NLP Solutions for Under Resourced Languages (NSURL 2019) The goal of the task is to predict whether two questions are semantically similar or not, even if they are phrased differently. A total of 9 teams participated in the task. The datasets created for this…

Tha3aroon at NSURL-2019 Task 8: Semantic Question Similarity in Arabic

In this paper, we describe our team's effort on the semantic text question similarity task of NSURL 2019. Our top performing system utilizes several innovative data augmentation techniques to enlarge the training data. Then, it takes ELMo pre-trained contextual embeddings of the data and feeds them into an ON-LSTM network with self-attention. This results in sequence representation vectors that are used to predict the relation between the question pairs. The model is ranked in the 1st place with 96.499 F1-score (same as the second place F1-score) and the 2nd place with 94.848 F1-score (differs…

阿拉伯语大语言模型（ALLMs）全景：阿拉伯语语言技术的新时代

The Landscape of Arabic Large Language Models (ALLMs): A New Era for Arabic Language Technology

本文综述阿拉伯语大语言模型（ALLMs）的发展历程、评估基准与排行榜，并探讨其为阿拉伯世界带来的技术机遇与挑战。

Combining Context-Free and Contextualized Representations for Arabic Sarcasm Detection and Sentiment Identification

Since their inception, transformer-based language models have led to impressive performance gains across multiple natural language processing tasks. For Arabic, the current state-of-the-art results on most datasets are achieved by the AraBERT language model. Notwithstanding these recent advancements, sarcasm and sentiment detection persist to be challenging tasks in Arabic, given the language's rich morphology, linguistic disparity and dialectal variations. This paper proffers team SPPU-AASM's submission for the WANLP ArSarcasm shared-task 2021, which centers around the sarcasm and sentiment p…

Jais 2：以阿拉伯语为核心的开源大语言模型家族

Jais 2: A Family of Arabic-Centric Open Large Language Models

Jais 2是MBZUAI等联合开发的以阿拉伯语为核心的开源大语言模型家族，含70B、8B参数变体，在阿拉伯语及文化相关基准上表现领先，已开源并部署为多平台聊天应用，可支撑相关研究开发。

Jais 与 Jais-chat：以阿拉伯语为中心的基础型与指令微调开放式生成式大型语言模型

Jais and Jais-chat: Arabic-Centric Foundation and Instruction-Tuned Open Generative Large Language Models

本文提出并开源 130 亿参数的 Jais 与 Jais-chat 阿拉伯语中心大模型，基于 GPT-3 仅解码器架构，在阿英及代码语料上训练，显著提升阿拉伯语知识与推理能力。