Generative Artificial Intelligence (AI) has enabled the development of sophisticated models
that are capable of producing high-caliber text, images, and other outputs through the …

In the era of large language models, Mixture-of-Experts (MoE) is a promising architecture for
managing computational costs when scaling up model parameters. However, conventional …

In this paper, we establish a benchmark named HalluQA (Chinese Hallucination Question-
Answering) to measure the hallucination phenomenon in Chinese large language models …

In this work we systematically review the recent advancements in code processing with
language models, covering 50+ models, 30+ evaluation tasks, 170+ datasets, and 700 …

We propose the Data Contamination Quiz, a simple and effective approach to detect data
contamination in large language models (LLMs) and estimate the amount of it. Specifically …

Ocean science, which delves into the oceans that are reservoirs of life and biodiversity, is of
great significance given that oceans cover over 70% of our planet's surface. Recently …

Parameter-efficient fine-tuning (PEFT) of pre-trained language models (PLMs) has emerged
as a highly successful approach, with training only a small number of parameters without …

The recent advances in natural language processing (NLP), have led to a new trend of
applying large language models (LLMs) to real-world scenarios. While the latest LLMs are …

Abstract Generative Large Language Models (LLMs) have achieved significant success in
various natural language processing tasks, including Question-Answering (QA) and …

Large language models (LLMs), such as ChatGPT/GPT-4, have proven to be powerful tools
in promoting the user experience as an AI assistant. The continuous works are proposing …