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Large language models (LLMs) have become the foundation of many applications, leveraging their extensive capabilities in processing and understanding natural language. While many open-source LLMs have been released with technical reports,…

Datasets are foundational to many breakthroughs in modern artificial intelligence. Many recent achievements in the space of natural language processing (NLP) can be attributed to the finetuning of pre-trained models on a diverse set of…

To ensure equitable access to the benefits of large language models (LLMs), it is essential to evaluate their capabilities across the world's languages. We introduce the AI Language Proficiency Monitor, a comprehensive multilingual…

Computation and Language · Computer Science 2025-07-14 David Pomerenke , Jonas Nothnagel , Simon Ostermann

Over the last few years, large language models (LLMs) have emerged as the most important breakthroughs in natural language processing (NLP) that fundamentally transform research and developments in the field. ChatGPT represents one of the…

Computation and Language · Computer Science 2023-04-13 Viet Dac Lai , Nghia Trung Ngo , Amir Pouran Ben Veyseh , Hieu Man , Franck Dernoncourt , Trung Bui , Thien Huu Nguyen

Instruction tuning plays a critical role in aligning large language models (LLMs) with human preference. Despite the vast amount of open instruction datasets, naively training a LLM on all existing instructions may not be optimal and…

Computer Vision and Pattern Recognition · Computer Science 2024-12-31 Yulei Qin , Yuncheng Yang , Pengcheng Guo , Gang Li , Hang Shao , Yuchen Shi , Zihan Xu , Yun Gu , Ke Li , Xing Sun

Large-scale pre-training and instruction tuning have been successful at creating general-purpose language models with broad competence. However, building general-purpose vision-language models is challenging due to the rich input…

Computer Vision and Pattern Recognition · Computer Science 2023-06-16 Wenliang Dai , Junnan Li , Dongxu Li , Anthony Meng Huat Tiong , Junqi Zhao , Weisheng Wang , Boyang Li , Pascale Fung , Steven Hoi

Despite the advancements of open-source large language models (LLMs), e.g., LLaMA, they remain significantly limited in tool-use capabilities, i.e., using external tools (APIs) to fulfill human instructions. The reason is that current…

Entity-level fine-grained sentiment analysis in the financial domain is a crucial subtask of sentiment analysis and currently faces numerous challenges. The primary challenge stems from the lack of high-quality and large-scale annotated…

Computation and Language · Computer Science 2023-09-18 Yinyu Lan , Yanru Wu , Wang Xu , Weiqiang Feng , Youhao Zhang

In this report, we introduce Qwen2.5, a comprehensive series of large language models (LLMs) designed to meet diverse needs. Compared to previous iterations, Qwen 2.5 has been significantly improved during both the pre-training and…

Humor plays a significant role in daily language communication. With the rapid development of large language models (LLMs), natural language processing has made significant strides in understanding and generating various genres of texts.…

Computation and Language · Computer Science 2025-03-27 Zhenghan Yu , Xinyu Hu , Xiaojun Wan

Instruction tuning enhances large language models (LLMs) to follow human instructions across diverse tasks, relying on high-quality datasets to guide behavior. However, these datasets, whether manually curated or synthetically generated,…

Prompt tuning for vision-language models such as CLIP involves optimizing the text prompts used to generate image-text pairs for specific downstream tasks. While hand-crafted or template-based prompts are generally applicable to a wider…

Computer Vision and Pattern Recognition · Computer Science 2025-01-23 Qian Zhang

The difficulty of the information extraction task lies in dealing with the task-specific label schemas and heterogeneous data structures. Recent work has proposed methods based on large language models to uniformly model different…

Computation and Language · Computer Science 2024-04-03 Xinglin Xiao , Yijie Wang , Nan Xu , Yuqi Wang , Hanxuan Yang , Minzheng Wang , Yin Luo , Lei Wang , Wenji Mao , Daniel Zeng

Large language models (LLMs) with billions of parameters have demonstrated outstanding performance on various natural language processing tasks. This report presents OpenBA, an open-sourced 15B bilingual asymmetric seq2seq model, to…

Computation and Language · Computer Science 2024-11-26 Juntao Li , Zecheng Tang , Yuyang Ding , Pinzheng Wang , Pei Guo , Wangjie You , Dan Qiao , Wenliang Chen , Guohong Fu , Qiaoming Zhu , Guodong Zhou , Min Zhang

Large Language Models (LLMs) have gained significant attention in the field of natural language processing (NLP) due to their wide range of applications. However, training LLMs for languages other than English poses significant challenges,…

Computation and Language · Computer Science 2024-05-20 Yudong Li , Yuhao Feng , Wen Zhou , Zhe Zhao , Linlin Shen , Cheng Hou , Xianxu Hou

ChatGPT (Chat Generative Pre-trained Transformer) is a chatbot launched by OpenAI on November 30, 2022. OpenAI's GPT-3 family of large language models serve as the foundation for ChatGPT. ChatGPT is fine-tuned with both supervised and…

Software Engineering · Computer Science 2023-05-29 Giriprasad Sridhara , Ranjani H. G. , Sourav Mazumdar

Large language models (LLMs) have shown impressive ability for open-domain NLP tasks. However, LLMs are sometimes too footloose for natural language understanding (NLU) tasks which always have restricted output and input format. Their…

A key technology for the development of large language models (LLMs) involves instruction tuning that helps align the models' responses with human expectations to realize impressive learning abilities. Two major approaches for instruction…

Computation and Language · Computer Science 2023-08-03 Viet Dac Lai , Chien Van Nguyen , Nghia Trung Ngo , Thuat Nguyen , Franck Dernoncourt , Ryan A. Rossi , Thien Huu Nguyen

Large-scale Pretrained Language Models (LLMs), such as ChatGPT and GPT4, have shown strong abilities in multilingual translations, without being explicitly trained on parallel corpora. It is interesting how the LLMs obtain their ability to…

Computation and Language · Computer Science 2024-04-16 Jiahuan Li , Hao Zhou , Shujian Huang , Shanbo Cheng , Jiajun Chen

Large Language Models (LLMs) are advanced Artificial Intelligence (AI) systems that have undergone extensive training using large datasets in order to understand and produce language that closely resembles that of humans. These models have…

Software Engineering · Computer Science 2023-08-10 Alessio Buscemi
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