论文WHEN AND WHY VISION-LANGUAGE MODELS BEHAVE LIKE BAGS-OF-WORDS, AND WHAT TO DO ABOUT IT笔记 RENNY 浙江大学 人工智能硕士在读5 人赞同了该文章 目录 收起 main idea When:模型什么时候像“词袋”? 评价关系理解和属性理解的新基准 评估顺序敏感性的新基准 在ARO上评价VLM Why:为什么会...
一个很有意思的探究VLM局限性的文章。 [1]THRUSH T, JIANG R, BARTOLO M, et al. Winoground: Probing Vision and Language Models for Visio-Linguistic Compositionality[J]. motivation 对于人类来说"the tree is in the shopping cart" and "the shopping cart is in the tree" 是完全不同的两幅图景,...
Unicoder-VL: A Universal Encoder for Vision and Language by Cross-modal Pre-training, AAAI 2020 Unified Vision-Language Pre-Training for Image Captioning and VQA, AAAI 2020,[code], (VLP) UNITER: Learning Universal Image-text Representations, arXiv 2019/09[code] Task-specific VCR:Fusion of De...
Our evaluation shows that we can generate adversarial examples with a high success rate (i.e., > 90%) for these models. Our work sheds new light on understanding adversarial attacks on vision systems which have a language component and shows that attention, bounding box localization, and ...
Models that have learned to construct cross-modal representations using both modalities are expected to perform worse when inputs are missing from a modality. We find that recently proposed models have much greater relative difficulty predicting text when visual information is ablated, compared to ...
In-depth Analysis,Behind the Scene: Revealing the Secrets of Pre-trained Vision-and-Language Models, ECCV 2020 Spotlight In-depth Analysis,A Closer Look at the Robustness of Vision-and-Language Pre-trained Models, arXiv 2020/12 Adversarial Training,Large-Scale Adversarial Training for Vision-and-...
Implementation of the deepmind Flamingo vision-language model, based on Hugging Face language models and ready for training - dhansmair/flamingo-mini
Efficient Sentence Representation Learning via Knowledge Distillation with Maximum Coding Rate Reductiondoi:10.20532/cit.2023.1005673LANGUAGE models... D Everdija,T Prusina,L Borozan,... - 《Journal of Computing & Information Technology》 被引量: 0发表: 2023年 Learning From Expert: Vision-Language ...
to perform visualgrounding –approaches for vision-and-language tasks lack a unif ied foundation to gain this capability.Instead, the dominant strategy is to start with separate language and vision models pretrained forother large-scale tasks and then learn grounding as part of task training –...
Despite the remarkable success of foundation models, their task-specific fine-tuning paradigm makes them inconsistent with the goal of general perception modeling. The key to eliminating this inconsistency is to use generalist models for general task modeling. However, existing attempts at generalist mod...