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Recent advances in multimodal large language models (MLLMs) have demonstrated strong capabilities in understanding general visual content. However, these general-domain MLLMs perform poorly in face perception tasks, often producing…

计算机视觉与模式识别 · 计算机科学 2025-04-29 Jingzhi Li , Changjiang Luo , Ruoyu Chen , Hua Zhang , Wenqi Ren , Jianhou Gan , Xiaochun Cao

This paper aims to efficiently enable Large Language Models (LLMs) to use multimodal tools. Advanced proprietary LLMs, such as ChatGPT and GPT-4, have shown great potential for tool usage through sophisticated prompt engineering.…

计算机视觉与模式识别 · 计算机科学 2023-05-31 Rui Yang , Lin Song , Yanwei Li , Sijie Zhao , Yixiao Ge , Xiu Li , Ying Shan

Large Language Models (LLMs) have emerged as powerful tools in various research domains. This article examines their potential through a literature review and firsthand experimentation. While LLMs offer benefits like cost-effectiveness and…

人机交互 · 计算机科学 2024-04-10 M. Namvarpour , A. Razi

Large Language Models(LLMs)have become effective tools for natural language processing and have been used in many different fields. This essay offers a succinct summary of various LLM subcategories. The survey emphasizes recent developments…

计算与语言 · 计算机科学 2023-07-21 Saurabh Pahune , Manoj Chandrasekharan

Although Large Language Models (LLMs) have demonstrated extraordinary capabilities in many domains, they still have a tendency to hallucinate and generate fictitious responses to user requests. This problem can be alleviated by augmenting…

信息检索 · 计算机科学 2023-06-09 Jiongnan Liu , Jiajie Jin , Zihan Wang , Jiehan Cheng , Zhicheng Dou , Ji-Rong Wen

Large Language Models (LLMs) exhibit emerging in-context learning abilities through prompt engineering. The recent progress in large-scale generative models has further expanded their use in real-world language applications. However, the…

计算与语言 · 计算机科学 2024-04-12 Linyi Yang , Shuibai Zhang , Zhuohao Yu , Guangsheng Bao , Yidong Wang , Jindong Wang , Ruochen Xu , Wei Ye , Xing Xie , Weizhu Chen , Yue Zhang

The rapid evolution of large language models (LLMs) has pushed their boundaries to many applications in various domains. Recently, the research community has started to evaluate their potential adoption in autonomous vehicles and especially…

机器人学 · 计算机科学 2025-09-09 Petros Loukas , David Bassir , Savvas Chatzichristofis , Angelos Amanatiadis

Building effective machine learning (ML) workflows to address complex tasks is a primary focus of the Automatic ML (AutoML) community and a critical step toward achieving artificial general intelligence (AGI). Recently, the integration of…

机器学习 · 计算机科学 2024-12-30 Yang Gu , Hengyu You , Jian Cao , Muran Yu , Haoran Fan , Shiyou Qian

This paper presents a comprehensive survey of ChatGPT-related (GPT-3.5 and GPT-4) research, state-of-the-art large language models (LLM) from the GPT series, and their prospective applications across diverse domains. Indeed, key innovations…

The rapid advancements in Large Language Models (LLMs) have significantly expanded their applications, ranging from multilingual support to domain-specific tasks and multimodal integration. In this paper, we present OmniEvalKit, a novel…

计算与语言 · 计算机科学 2024-12-10 Yi-Kai Zhang , Xu-Xiang Zhong , Shiyin Lu , Qing-Guo Chen , De-Chuan Zhan , Han-Jia Ye

We introduce MT-LENS, a framework designed to evaluate Machine Translation (MT) systems across a variety of tasks, including translation quality, gender bias detection, added toxicity, and robustness to misspellings. While several toolkits…

计算与语言 · 计算机科学 2024-12-17 Javier García Gilabert , Carlos Escolano , Audrey Mash , Xixian Liao , Maite Melero

Machine Translation (MT) has greatly advanced over the years due to the developments in deep neural networks. However, the emergence of Large Language Models (LLMs) like GPT-4 and ChatGPT is introducing a new phase in the MT domain. In this…

计算与语言 · 计算机科学 2024-04-03 Chenyang Lyu , Zefeng Du , Jitao Xu , Yitao Duan , Minghao Wu , Teresa Lynn , Alham Fikri Aji , Derek F. Wong , Siyou Liu , Longyue Wang

This paper deals with improving querying large language models (LLMs). It is well-known that without relevant contextual information, LLMs can provide poor quality responses or tend to hallucinate. Several initiatives have proposed…

计算与语言 · 计算机科学 2025-07-14 Nripesh Niketan , Hadj Batatia

As global demand for multilingual large language models (LLMs) grows, most LLMs still remain overly focused on English, leading to the limited access to advanced AI for non-English speakers. Current methods to enhance multilingual…

计算与语言 · 计算机科学 2025-05-27 Weixiang Zhao , Yulin Hu , Jiahe Guo , Xingyu Sui , Tongtong Wu , Yang Deng , Yanyan Zhao , Bing Qin , Wanxiang Che , Ting Liu

Large Language Models (LLMs) have revolutionized various aspects of engineering and science. Their utility is often bottlenecked by the lack of interaction with the external digital environment. To overcome this limitation and achieve…

软件工程 · 计算机科学 2024-12-24 Ioannis Tzachristas

The rapid development of Large Language Models (LLMs) demonstrates remarkable multilingual capabilities in natural language processing, attracting global attention in both academia and industry. To mitigate potential discrimination and…

In response to the growing complexity and volume of scientific literature, this paper introduces the LLMs4Synthesis framework, designed to enhance the capabilities of Large Language Models (LLMs) in generating high-quality scientific…

计算与语言 · 计算机科学 2024-09-30 Hamed Babaei Giglou , Jennifer D'Souza , Sören Auer

Large language models (LLMs) are powerful artificial intelligence (AI) tools transforming how research is conducted. However, their use in research has been met with skepticism, due to concerns about hallucinations, biases and potential…

人工智能 · 计算机科学 2025-07-08 Ruian Ke , Ruy M. Ribeiro

Recent advancements in Large Language Models (LLMs), particularly those built on Transformer architectures, have significantly broadened the scope of natural language processing (NLP) applications, transcending their initial use in chatbot…

计算与语言 · 计算机科学 2024-05-29 Chen Wang , Jin Zhao , Jiaqi Gong

In this paper, we propose and describe the first open Llama2 large language models (LLMs) for the Lithuanian language, including an accompanying question/answer (Q/A) dataset and translations of popular LLM benchmarks. We provide a brief…

计算与语言 · 计算机科学 2025-05-01 Artūras Nakvosas , Povilas Daniušis , Vytas Mulevičius