Accuracy improvements were observed in all document question-answering datasets tested with the open source FlanT5-XL model when using layout-aware linearized text, as opposed to raw text (raster scan), in response to zero-shot prompts...
In this report we present results of the ICDAR 2021 edition of the Document Visual Question Challenges. This edition complements the previous tasks on Single Document VQA and Document Collection VQA with a newly introduced on Infographics VQA. Infographics VQA is based on a new dataset of more ...
ChatGPT 比较其他的大模型在基于对话的理解上表现更好 Dense Passage Retrieval for Open-Domain Question Answering# 摘要、引言、相关工作# Sparse Retrieval Dense Retrieval 自回归检索(Autoregressive retrieval) 作者提问:是否可以只用(问题,文章)对在没有额外的与训练是训练一个更好的 dense 潜入模型? 模型# Loss...
Add dataset creation and training scripts Jul 18, 2020 This repo hosts the basic functional code for our approach entitledHyperDQAin theDocument Visual Question Answeringcompetition hosted as a part ofWorkshop on Text and Documents in Deep Learning EraatCVPR2020. Our approach stands at position 4...
Recent advancements have made it possible to ask models to answer questions about an image - this is known as document visual question answering, or DocVQA for short. After being given a question, the model analyzes the image and responds with an answer. An example from the DocVQA da...
"Based the questions in the [MS-MARCO] Question Answering Dataset and the documents which answered the questions a document ranking task was formulated. There are 3.2 million documents and the goal is to rank based on their relevance. Relevance labels are derived from what passages was marked as...
Document Visual Question Answering competition数据集包含12K文档和50K的问答。验证指标使用的ANLS。 4.2. 配置 Encoder Swin-B - layer number {2, 2, 14, 2} - window size 10 Decoder BART的前4层 - token 长度 1536 GPU 64 * A100 batch size 196 steps 200k 优化器 Adam - learning rate 1e-4 ...
In this specific use case, differently from the few-shot approach, fine-tuning the IT5 model on our dataset led to very satisfactory results,with an increase of more than 70% in metrics for fixed model size and entity considered. The results were competitive with classical NER approaches. ...
Park, S., et al.: Cord: a consolidated receipt dataset for post-OCR parsing. In: Workshop on Document Intelligence at NeurIPS 2019 (2019) Google Scholar Peng, D., et al.: SPTS: Single-Point Text Spotting. CoRR abs/2112.07917 (2021).https://arxiv.org/abs/2112.07917 ...
Recent advancements have made it possible to ask models to answer questions about an image - this is known as document visual question answering, or DocVQA for short. After being given a question, the model analyzes the image and responds with an answer. An example from the DocVQA dataset is...