6 citations · 12 across the 5 of their papers we have counts for
5 papers
DocKD: Knowledge Distillation from LLMs for Open-World Document Understanding Models
Sungnyun Kim, Haofu Liao, Srikar Appalaraju +6
Visual document understanding (VDU) is a challenging task that involves understanding documents across various modalities (text and image) and layouts (forms, tables, etc.). This s…
DEED: Dynamic Early Exit on Decoder for Accelerating Encoder-Decoder Transformer Models
Peng Tang, Pengkai Zhu, Tian Li +3
Encoder-decoder transformer models have achieved great success on various vision-language (VL) tasks, but they suffer from high inference latency. Typically, the decoder takes up m…
Multiple-Question Multiple-Answer Text-VQA
Peng Tang, Srikar Appalaraju, R. Manmatha +2
We present Multiple-Question Multiple-Answer (MQMA), a novel approach to do text-VQA in encoder-decoder transformer models. The text-VQA task requires a model to answer a question…
DocTr: Document Transformer for Structured Information Extraction in Documents
Haofu Liao, Aruni RoyChowdhury, Weijian Li +6
We present a new formulation for structured information extraction (SIE) from visually rich documents. It aims to address the limitations of existing IOB tagging or graph-based for…
PolyFormer: Referring Image Segmentation as Sequential Polygon Generation
Jiang Liu, Hui Ding, Zhaowei Cai +4
In this work, instead of directly predicting the pixel-level segmentation masks, the problem of referring image segmentation is formulated as sequential polygon generation, and the…