A systematic survey and critical review on evaluating large language models: Challenges, limitations, and recommendations
Abstract Large Language Models (LLMs) have recently gained significant attention due to
their remarkable capabilities in performing diverse tasks across various domains. However …
their remarkable capabilities in performing diverse tasks across various domains. However …
Exploring ChatGPT for next-generation information retrieval: Opportunities and challenges
The rapid advancement of artificial intelligence (AI) has spotlighted ChatGPT as a key
technology in the realm of information retrieval (IR). Unlike its predecessors, it offers notable …
technology in the realm of information retrieval (IR). Unlike its predecessors, it offers notable …
GPTs Are Multilingual Annotators for Sequence Generation Tasks
Data annotation is an essential step for constructing new datasets. However, the
conventional approach of data annotation through crowdsourcing is both time-consuming …
conventional approach of data annotation through crowdsourcing is both time-consuming …
MMM: Multilingual Mutual Reinforcement Effect Mix Datasets & Test with Open-domain Information Extraction Large Language Models
The Mutual Reinforcement Effect (MRE) represents a promising avenue in information
extraction and multitasking research. Nevertheless, its applicability has been constrained …
extraction and multitasking research. Nevertheless, its applicability has been constrained …
based Recommender Systems: A Survey of Approaches, Challenges and Future Perspectives
Recommender systems play a pivotal role in helping users navigate an overwhelming
selection of products and services. On online platforms, users have the opportunity to share …
selection of products and services. On online platforms, users have the opportunity to share …
A Systematic Survey of Text Summarization: From Statistical Methods to Large Language Models
Text summarization research has undergone several significant transformations with the
advent of deep neural networks, pre-trained language models (PLMs), and recent large …
advent of deep neural networks, pre-trained language models (PLMs), and recent large …