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Large language models (LLMs) with billions of parameters exhibit in-context learning abilities, enabling few-shot learning on tasks that the model was not specifically trained for. Traditional models achieve breakthrough performance on…

Artificial Intelligence · Computer Science 2025-11-04 Aske Plaat , Annie Wong , Suzan Verberne , Joost Broekens , Niki van Stein , Thomas Back

The upsurge in pre-trained large models started by ChatGPT has swept across the entire deep learning community. Such powerful models demonstrate advanced generative ability and multimodal understanding capability, which quickly set new…

Computer Vision and Pattern Recognition · Computer Science 2025-02-28 Ning Ding , Yehui Tang , Zhongqian Fu , Chao Xu , Kai Han , Yunhe Wang

Recent advancements in Generative AI, particularly in Large Language Models (LLMs) and Large Vision-Language Models (LVLMs), offer new possibilities for integrating cognitive planning into robotic systems. In this work, we present a novel…

Robotics · Computer Science 2024-11-06 Arjun P S , Andrew Melnik , Gora Chand Nandi

We introduce Blink, a new benchmark for multimodal language models (LLMs) that focuses on core visual perception abilities not found in other evaluations. Most of the Blink tasks can be solved by humans "within a blink" (e.g., relative…

Computer Vision and Pattern Recognition · Computer Science 2024-07-04 Xingyu Fu , Yushi Hu , Bangzheng Li , Yu Feng , Haoyu Wang , Xudong Lin , Dan Roth , Noah A. Smith , Wei-Chiu Ma , Ranjay Krishna

Accurate prediction of human behavior is crucial for AI systems to effectively support real-world applications, such as autonomous robots anticipating and assisting with human tasks. Real-world scenarios frequently present challenges such…

Human-Computer Interaction · Computer Science 2025-07-21 Kojiro Takeyama , Yimeng Liu , Misha Sra

Advancements in large language models (LLMs) have demonstrated their potential in facilitating high-level reasoning, logical reasoning and robotics planning. Recently, LLMs have also been able to generate reward functions for low-level…

Robotics · Computer Science 2024-02-21 Marta Skreta , Zihan Zhou , Jia Lin Yuan , Kourosh Darvish , Alán Aspuru-Guzik , Animesh Garg

Large multimodal models (LMMs) have gained impressive performance due to their outstanding capability in various understanding tasks. However, these models still suffer from some fundamental limitations related to robustness and…

Computer Vision and Pattern Recognition · Computer Science 2025-11-27 Thanh-Dat Truong , Huu-Thien Tran , Tran Thai Son , Bhiksha Raj , Khoa Luu

The remarkable multimodal capabilities demonstrated by OpenAI's GPT-4 have sparked significant interest in the development of multimodal Large Language Models (LLMs). A primary research objective of such models is to align visual and…

Computer Vision and Pattern Recognition · Computer Science 2023-12-29 Yanda Li , Chi Zhang , Gang Yu , Zhibin Wang , Bin Fu , Guosheng Lin , Chunhua Shen , Ling Chen , Yunchao Wei

Engineering design is undergoing a transformative shift with the advent of AI, marking a new era in how we approach product, system, and service planning. Large language models have demonstrated impressive capabilities in enabling this…

Artificial Intelligence · Computer Science 2024-12-10 Cyril Picard , Kristen M. Edwards , Anna C. Doris , Brandon Man , Giorgio Giannone , Md Ferdous Alam , Faez Ahmed

Visual reasoning is dominated by end-to-end neural networks scaled to billions of model parameters and training examples. However, even the largest models struggle with compositional reasoning, generalization, fine-grained spatial and…

Computer Vision and Pattern Recognition · Computer Science 2024-05-16 Aleksandar Stanić , Sergi Caelles , Michael Tschannen

Multimodal large language models (MLLMs) are changing how Blind and Low Vision (BLV) people access visual information. Unlike traditional visual interpretation tools that only provide descriptions, MLLM-enabled applications offer…

Human-Computer Interaction · Computer Science 2026-02-20 Ricardo E. Gonzalez Penuela , Crescentia Jung , Sharon Y Lin , Ruiying Hu , Shiri Azenkot

With the rapid advancement of artificial intelligence and robotics, the integration of Large Language Models (LLMs) with 3D vision is emerging as a transformative approach to enhancing robotic sensing technologies. This convergence enables…

Robotics · Computer Science 2025-11-19 Vinit Mehta , Charu Sharma , Karthick Thiyagarajan

Artificial Intelligence have profoundly transformed the technological landscape in recent years. Large Language Models (LLMs) have demonstrated impressive abilities in reasoning, text comprehension, contextual pattern recognition, and…

Computer Vision and Pattern Recognition · Computer Science 2025-09-30 Efthymios Tsaprazlis , Tiantian Feng , Anil Ramakrishna , Rahul Gupta , Shrikanth Narayanan

Large Vision-Language Models (LVLMs) have demonstrated impressive capabilities in multimodal understanding, yet their reasoning abilities remain underexplored. Existing benchmarks tend to focus on perception or text-based comprehension,…

Computation and Language · Computer Science 2025-08-28 Xiang Li , Wenyue Hua , Kaijie Zhu , Lingyao Li , Haoyang Ling , Jinkui Chi , Qi Dou , Jindong Wang , Yongfeng Zhang , Xin Ma , Lizhou Fan

Large language models (LLMs) have substantially advanced machine learning research, including natural language processing, computer vision, data mining, etc., yet they still exhibit critical limitations in explainability, reliability,…

Machine Learning · Computer Science 2025-09-19 Xin Wang , Haoyang Li , Haibo Chen , Zeyang Zhang , Wenwu Zhu

With the emergence of Large Language Models (LLMs) and Vision Foundation Models (VFMs), multimodal AI systems benefiting from large models have the potential to equally perceive the real world, make decisions, and control tools as humans.…

Large Language Models (LLMs) have recently emerged as a focal point of research and application, driven by their unprecedented ability to understand and generate text with human-like quality. Even more recently, LLMs have been extended into…

Computation and Language · Computer Science 2024-04-03 Kilian Carolan , Laura Fennelly , Alan F. Smeaton

The development of Large Vision-Language Models (LVLMs) is striving to catch up with the success of Large Language Models (LLMs), yet it faces more challenges to be resolved. Very recent works enable LVLMs to localize object-level visual…

Computer Vision and Pattern Recognition · Computer Science 2024-03-20 Zhipeng Huang , Zhizheng Zhang , Zheng-Jun Zha , Yan Lu , Baining Guo

Large Language Models (LLMs), typified by OpenAI's GPT, have marked a significant advancement in artificial intelligence. Trained on vast amounts of text data, LLMs are capable of understanding and generating human-like text across a…

Artificial Intelligence · Computer Science 2024-10-29 Haochen Zhang , Yuyang Dong , Chuan Xiao , Masafumi Oyamada

Multi-modal large language models (MLLMs), such as GPT-4o, excel at integrating text and visual data but face systematic challenges when interpreting ambiguous or incomplete visual stimuli. This study leverages statistical modeling to…

Machine Learning · Computer Science 2024-12-09 Ching-Yi Wang