相关论文: Effects of Stop Words Elimination for Arabic Infor…

Large-alphabet strings are common in scenarios such as information retrieval and natural-language processing. The efficient storage and processing of such strings usually introduces several challenges that are not witnessed in…

This paper proposes a dual skipping guidance scheme with hybrid scoring to accelerate document retrieval that uses learned sparse representations while still delivering a good relevance. This scheme uses both lexical BM25 and learned neural…

Treebanks are valuable linguistic resources that include the syntactic structure of a language sentence in addition to POS-tags and morphological features. They are mainly utilized in modeling statistical parsers. Although the statistical…

The recent rise of Large Reasoning Models (LRMs) has significantly improved multi-step reasoning performance, but often at the cost of generating excessively long reasoning chains. This paper revisits the efficiency of such reasoning…

Arabic language is one of the most popular languages in the world. Hundreds of millions of people in many countries around the world speak Arabic as their native speaking. However, due to complexity of Arabic language, recognition of…

The Arabic language is a complex language; it is different from Western languages especially at the morphological and spelling variations. Indeed, the performance of information retrieval systems in the Arabic language is still a problem.…

The study of IR evaluation metrics through axiomatic analysis enables a better understanding of their numerical properties. Some works have modelled the effectiveness of retrieval metrics with axioms that capture desirable properties on the…

This research assesses the effectiveness of state-of-the-art large language models (LLMs), including ChatGPT, Llama, Aya, Jais, and ACEGPT, in the task of Arabic automated essay scoring (AES) using the AR-AES dataset. It explores various…

Searching for information on the internet and digital platforms requires effective retrieval solutions. However, such solutions are not yet available for Tetun, making it difficult to find relevant documents for search queries in this…

Document Clustering is a branch of a larger area of scientific study known as data mining .which is an unsupervised classification using to find a structure in a collection of unlabeled data. The useful information in the documents can be…

Annotation of training data is the major bottleneck in the creation of text classification systems. Active learning is a commonly used technique to reduce the amount of training data one needs to label. A crucial aspect of active learning…

Obtaining relevant information from a collection of informational resources in Afaan Oromo is very important for Afaan Oromo speakers, developing a system that help users of Afaan Oromo is mandatory. That is why this study is envisioned to…

Since the amount of information on the internet is growing rapidly, it is not easy for a user to find relevant information for his/her query. To tackle this issue, much attention has been paid to Automatic Document Summarization. The key…

This study investigates the position bias in information retrieval, where models tend to overemphasize content at the beginning of passages while neglecting semantically relevant information that appears later. To analyze the extent and…

Data contamination undermines the validity of Large Language Model evaluation by enabling models to rely on memorized benchmark content rather than true generalization. While prior work has proposed contamination detection methods, these…

Large Language Models (LLMs) have shown impressive results in multiple domains of natural language processing (NLP) but are mainly focused on the English language. Recently, more LLMs have incorporated a larger proportion of multilingual…

This paper addresses the classification of Arabic text data in the field of Natural Language Processing (NLP), with a particular focus on Natural Language Inference (NLI) and Contradiction Detection (CD). Arabic is considered a…

We propose a technique to improve the search efficiency of the bag-of-words (BoW) method for image retrieval. We introduce a notion of difficulty for the image matching problems and propose methods that reduce the amount of computations…

Research into statistical parsing for English has enjoyed over a decade of successful results. However, adapting these models to other languages has met with difficulties. Previous comparative work has shown that Modern Arabic is one of the…

This paper presents a comprehensive examination of the impact of tokenization strategies and vocabulary sizes on the performance of Arabic language models in downstream natural language processing tasks. Our investigation focused on the…