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Addressing the gap in understanding visual comprehension in Large Language Models (LLMs), we designed a challenge-response study, subjecting Google Bard and GPT-Vision to 64 visual tasks, spanning categories like "Visual Situational…

计算机视觉与模式识别 · 计算机科学 2023-10-18 David Noever , Samantha Elizabeth Miller Noever

Generative AI and large language models have the potential to drastically improve the landscape of computing education by automatically generating personalized feedback and content. Recent works have studied the capabilities of these models…

机器学习 · 计算机科学 2023-08-08 Adish Singla

Recent advancements in multimodal techniques open exciting possibilities for models excelling in diverse tasks involving text, audio, and image processing. Models like GPT-4V, blending computer vision and language modeling, excel in complex…

计算与语言 · 计算机科学 2023-10-20 Xiang Zhang , Senyu Li , Zijun Wu , Ning Shi

Large language models have seen widespread adoption in math problem-solving. However, in geometry problems that usually require visual aids for better understanding, even the most advanced multi-modal models currently still face challenges…

计算机视觉与模式识别 · 计算机科学 2024-06-18 Shihao Cai , Keqin Bao , Hangyu Guo , Jizhi Zhang , Jun Song , Bo Zheng

Recent developments in multimodal methodologies have marked the beginning of an exciting era for models adept at processing diverse data types, encompassing text, audio, and visual content. Models like GPT-4V, which merge computer vision…

Large language models (LLMs) have undergone significant expansion and have been increasingly integrated across various domains. Notably, in the realm of robot task planning, LLMs harness their advanced reasoning and language comprehension…

In this paper, we critically evaluate the capabilities of the state-of-the-art multimodal large language model, i.e., GPT-4 with Vision (GPT-4V), on Visual Question Answering (VQA) task. Our experiments thoroughly assess GPT-4V's…

计算机视觉与模式识别 · 计算机科学 2023-10-31 Zhiling Yan , Kai Zhang , Rong Zhou , Lifang He , Xiang Li , Lichao Sun

NLP models today strive for supporting multiple languages and modalities, improving accessibility for diverse users. In this paper, we evaluate their multilingual, multimodal capabilities by testing on a visual reasoning task. We observe…

计算与语言 · 计算机科学 2025-02-11 Yueqi Song , Simran Khanuja , Graham Neubig

Large Language Models (LLMs) and Large Multimodal Models (LMMs) exhibit impressive problem-solving skills in many tasks and domains, but their ability in mathematical reasoning in visual contexts has not been systematically studied. To…

计算机视觉与模式识别 · 计算机科学 2024-01-23 Pan Lu , Hritik Bansal , Tony Xia , Jiacheng Liu , Chunyuan Li , Hannaneh Hajishirzi , Hao Cheng , Kai-Wei Chang , Michel Galley , Jianfeng Gao

Generative AI and large language models hold great promise in enhancing computing education by powering next-generation educational technologies for introductory programming. Recent works have studied these models for different scenarios…

Recent advancements in generative AI systems have raised concerns about academic integrity among educators. Beyond excelling at solving programming problems and text-based multiple-choice questions, recent research has also found that large…

Large Language Models (LLMs) like GPT and Bard are capable of producing code based on textual descriptions, with remarkable efficacy. Such technology will have profound implications for computing education, raising concerns about cheating,…

新兴技术 · 计算机科学 2024-04-29 Bruno Pereira Cipriano , Pedro Alves

Large multimodal models extend the impressive capabilities of large language models by integrating multimodal understanding abilities. However, it is not clear how they can emulate the general intelligence and reasoning ability of humans.…

计算机视觉与模式识别 · 计算机科学 2024-08-20 Yew Ken Chia , Vernon Toh Yan Han , Deepanway Ghosal , Lidong Bing , Soujanya Poria

Large language models and multimodal large language models have revolutionized artificial intelligence recently. An increasing number of regions are now embracing these advanced technologies. Within this context, robot coding education is…

This paper introduces the novel task of multimodal puzzle solving, framed within the context of visual question-answering. We present a new dataset, AlgoPuzzleVQA designed to challenge and evaluate the capabilities of multimodal language…

计算机视觉与模式识别 · 计算机科学 2024-03-14 Deepanway Ghosal , Vernon Toh Yan Han , Chia Yew Ken , Soujanya Poria

As large language models (LLMs) continue to advance, evaluating their comprehensive capabilities becomes significant for their application in various fields. This research study comprehensively evaluates the language, vision, speech, and…

Large language models have demonstrated robust performance on various language tasks using zero-shot or few-shot learning paradigms. While being actively researched, multimodal models that can additionally handle images as input have yet to…

计算与语言 · 计算机科学 2023-05-24 Sherzod Hakimov , David Schlangen

This paper studies recent developments in large language models' (LLM) abilities to pass assessments in introductory and intermediate Python programming courses at the postsecondary level. The emergence of ChatGPT resulted in heated debates…

计算机与社会 · 计算机科学 2023-10-05 Jaromir Savelka , Arav Agarwal , Marshall An , Chris Bogart , Majd Sakr

Google's Bard has emerged as a formidable competitor to OpenAI's ChatGPT in the field of conversational AI. Notably, Bard has recently been updated to handle visual inputs alongside text prompts during conversations. Given Bard's impressive…

计算机视觉与模式识别 · 计算机科学 2023-08-31 Haotong Qin , Ge-Peng Ji , Salman Khan , Deng-Ping Fan , Fahad Shahbaz Khan , Luc Van Gool

Determining the extent to which the perceptual world can be recovered from language is a longstanding problem in philosophy and cognitive science. We show that state-of-the-art large language models can unlock new insights into this problem…

计算与语言 · 计算机科学 2023-06-16 Raja Marjieh , Ilia Sucholutsky , Pol van Rijn , Nori Jacoby , Thomas L. Griffiths
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