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Matching papers

HPD-Parsing: Hierarchical Parallel Document Parsing

8 upvotes · 21 JUL 2026 · Shu Wei, Jingjing Wu, Lingshu Zhang et al.

This paper introduces HPD-Parsing, a new approach to document parsing that uses hierarchical parallel decoding to improve efficiency and throughput. Practitioners in natural language processing and computer vision might care because it could lead to faster and more accurate document parsing models.

vision-language modelsdocument parsinghierarchical parallel decodingautoregressive modelsbenchmarks

UI2App: Benchmarking Visual Interaction Inference in Executable Web Application Generation

2 upvotes · 7 JUL 2026 · Grace Man Chen, Litao Guo, Yifan Wu et al.

This paper introduces UI2App, a benchmark to evaluate the ability of large language models to infer interaction behavior from screenshots of web applications, which is crucial for real-world development workflows. Practitioners might care about this research because it highlights the limitations of current visual-driven approaches and the need for better interaction inference capabilities in web application generation.

web application generationvisual interaction inferencecontinual learningbenchmarksvision-language models

ENTRAP-VL: A Taxonomic Probe for Dual Contextual Entrainment in Vision-Language Models

2 upvotes · 22 JUL 2026 · Karan Goyal, Afreen Hossain, Debojyoti Das et al.

This paper introduces a new dataset and tool to study contextual entrainment in vision-language models, which is the tendency for models to respond to irrelevant or false context in their inputs. Practitioners in AI and ML might care about this because it can affect the accuracy and reliability of vision-language models in real-world applications.

vision-language modelscontextual entrainmentmultimodal learningtaxonomiesbenchmarks