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Large Language Models (LLMs) have demonstrated superior abilities in tasks such as chatting, reasoning, and question-answering. However, standard LLMs may ignore crucial paralinguistic information, such as sentiment, emotion, and speaking…

Transformer architectures contribute to managing long-term dependencies for Natural Language Processing, representing one of the most recent changes in the field. These architectures are the basis of the innovative, cutting-edge Large…

计算与语言 · 计算机科学 2024-09-06 Silvia García-Méndez , Francisco de Arriba-Pérez , María del Carmen Somoza-López

This paper investigates the emotional reasoning abilities of the GPT family of large language models via a component perspective. The paper first examines how the model reasons about autobiographical memories. Second, it systematically…

计算与语言 · 计算机科学 2023-07-27 Ala N. Tak , Jonathan Gratch

This article presents the development, implementation, and validation of a loss-optimized and circuit parameter-sensitive TPS modulation scheme for a dual-active-bridge DC-DC converter. The proposed approach dynamically adjusts control…

信号处理 · 电气工程与系统科学 2025-02-26 Saikat Dey , Ayan Mallik

Recent advancement of large language models (LLMs) represents a transformational capability at the frontier of artificial intelligence. However, LLMs are generalized models, trained on extensive text corpus, and often struggle to provide…

This paper introduces NeuGPT, a groundbreaking multi-modal language generation model designed to harmonize the fragmented landscape of neural recording research. Traditionally, studies in the field have been compartmentalized by signal…

计算与语言 · 计算机科学 2024-10-29 Yiqian Yang , Yiqun Duan , Hyejeong Jo , Qiang Zhang , Renjing Xu , Oiwi Parker Jones , Xuming Hu , Chin-teng Lin , Hui Xiong

In the pursuit of efficient automated content creation, procedural generation, leveraging modifiable parameters and rule-based systems, emerges as a promising approach. Nonetheless, it could be a demanding endeavor, given its intricate…

计算机视觉与模式识别 · 计算机科学 2024-05-30 Chunyi Sun , Junlin Han , Weijian Deng , Xinlong Wang , Zishan Qin , Stephen Gould

Chat GPT belongs to the category of Generative Pre-trained Transformer (GPT) language models, which have received specialized training to produce text based on natural language inputs. Its purpose is to imitate human-like conversation and…

人机交互 · 计算机科学 2023-11-03 Wei Zhou

Neural network models have achieved state-of-the-art performance on grapheme-to-phoneme (G2P) conversion. However, their performance relies on large-scale pronunciation dictionaries, which may not be available for a lot of languages.…

计算与语言 · 计算机科学 2022-01-27 Lu Dong , Zhi-Qiang Guo , Chao-Hong Tan , Ya-Jun Hu , Yuan Jiang , Zhen-Hua Ling

Automatic Sign Language Translation requires the integration of both computer vision and natural language processing to effectively bridge the communication gap between sign and spoken languages. However, the deficiency in large-scale…

计算机视觉与模式识别 · 计算机科学 2024-05-08 Ryan Wong , Necati Cihan Camgoz , Richard Bowden

Recent work on Grammatical Error Correction (GEC) has highlighted the importance of language modeling in that it is certainly possible to achieve good performance by comparing the probabilities of the proposed edits. At the same time,…

计算与语言 · 计算机科学 2019-06-06 Dimitrios Alikaniotis , Vipul Raheja

With the rapid evolution of Natural Language Processing (NLP), Large Language Models (LLMs) like ChatGPT have emerged as powerful tools capable of transforming various sectors. Their vast knowledge base and dynamic interaction capabilities…

计算机与社会 · 计算机科学 2024-01-02 Kevin Wang , Jason Ramos , Ramon Lawrence

Large Language Models (LLMs) and, more specifically, the Generative Pre-Trained Transformers (GPT) can help stakeholders in climate action explore digital knowledge bases and extract and utilize climate action knowledge in a sustainable…

计算机与社会 · 计算机科学 2024-02-02 Denis Havlik , Marcelo Pias

Pre-trained Transformer-based models have achieved state-of-the-art performance for various Natural Language Processing (NLP) tasks. However, these models often have billions of parameters, and, thus, are too resource-hungry and…

The success of large language models (LLMs), like GPT-4 and ChatGPT, has led to the development of numerous cost-effective and accessible alternatives that are created by finetuning open-access LLMs with task-specific data (e.g.,…

计算与语言 · 计算机科学 2023-10-10 Zhiqiang Hu , Lei Wang , Yihuai Lan , Wanyu Xu , Ee-Peng Lim , Lidong Bing , Xing Xu , Soujanya Poria , Roy Ka-Wei Lee

Mechanical metamaterials utilize intricate architectural designs to achieve advanced properties beyond those of their bulk counterparts. Existing metamaterial designs often rely on design inspirations and extensive experimental and…

We introduce Action-GPT, a plug-and-play framework for incorporating Large Language Models (LLMs) into text-based action generation models. Action phrases in current motion capture datasets contain minimal and to-the-point information. By…

计算机视觉与模式识别 · 计算机科学 2023-03-08 Sai Shashank Kalakonda , Shubh Maheshwari , Ravi Kiran Sarvadevabhatla

Recently, large language models (LLMs) have been successfully applied to many fields, showing outstanding comprehension and reasoning capabilities. Despite their great potential, LLMs usually require dedicated pre-training and fine-tuning…

网络与互联网体系结构 · 计算机科学 2024-12-31 Hao Zhou , Chengming Hu , Dun Yuan , Ye Yuan , Di Wu , Xi Chen , Hina Tabassum , Xue Liu

With the rapid development of large language models, AI assistants like ChatGPT have become increasingly integrated into people's works and lives but are limited in personalized services. In this paper, we present a plug-and-play framework…

计算与语言 · 计算机科学 2024-10-15 Ruifeng Yuan , Shichao Sun , Yongqi Li , Zili Wang , Ziqiang Cao , Wenjie Li

Large language models that use retrieval augmented generation have the potential to unlock valuable knowledge for researchers, policymakers, and the public by making long and technical climate-related documents more accessible. While this…

计算与语言 · 计算机科学 2025-05-22 David Thulke , Jakob Kemmler , Christian Dugast , Hermann Ney