Search Results for author: Richard Zanibbi

Found 10 papers, 2 papers with code

Local and Global Graph Modeling with Edge-weighted Graph Attention Network for Handwritten Mathematical Expression Recognition

no code implementations24 Oct 2024 Yejing Xie, Richard Zanibbi, Harold Mouchère

Additionally, we propose a stroke-level Graph Modeling method for both local (LGM) and global (GGM) information, which applies an end-to-end model to Online HMER tasks, transforming the recognition problem into node and edge classification tasks in graph structure.

Classification Edge Classification +2

ColBERT's [MASK]-based Query Augmentation: Effects of Quadrupling the Query Input Length

no code implementations24 Aug 2024 Ben Giacalone, Richard Zanibbi

We then examine the effect of changing the number of [MASK] tokens from zero to up to four times past the query input length used in training, both for first stage retrieval, and for scoring candidates, observing an initial decrease in performance with few [MASK]s, a large increase when enough [MASK]s are added to pad queries to an average length of 32, then a plateau in performance afterwards.

Mathematical Information Retrieval: Search and Question Answering

no code implementations21 Aug 2024 Richard Zanibbi, Behrooz Mansouri, Anurag Agarwal

This book begins with a simple framework characterizing the information tasks that people and systems perform as we work to answer math-related questions.

Information Retrieval Math +2

A Study of PHOC Spatial Region Configurations for Math Formula Retrieval

no code implementations17 Aug 2024 Matt Langsenkamp, Bryan Amador, Richard Zanibbi

A Pyramidal Histogram Of Characters (PHOC) represents the spatial location of symbols as binary vectors.

Math Retrieval

Effects of context, complexity, and clustering on evaluation for math formula retrieval

no code implementations20 Nov 2021 Behrooz Mansouri, Douglas W. Oard, Anurag Agarwal, Richard Zanibbi

There are now several test collections for the formula retrieval task, in which a system's goal is to identify useful mathematical formulae to show in response to a query posed as a formula.

Clustering Math +1

ScanSSD: Scanning Single Shot Detector for Mathematical Formulas in PDF Document Images

1 code implementation18 Mar 2020 Parag Mali, Puneeth Kukkadapu, Mahshad Mahdavi, Richard Zanibbi

We introduce the Scanning Single Shot Detector (ScanSSD) for locating math formulas offset from text and embedded in textlines.

Math

Query Auto Completion for Math Formula Search

no code implementations9 Dec 2019 Shaurya Rohatgi, Wei Zhong, Richard Zanibbi, Jian Wu, C. Lee Giles

Query Auto Completion (QAC) is among the most appealing features of a web search engine.

Math

Detecting Figures and Part Labels in Patents: Competition-Based Development of Image Processing Algorithms

no code implementations24 Oct 2014 Christoph Riedl, Richard Zanibbi, Marti A. Hearst, Siyu Zhu, Michael Menietti, Jason Crusan, Ivan Metelsky, Karim R. Lakhani

We report the findings of a month-long online competition in which participants developed algorithms for augmenting the digital version of patent documents published by the United States Patent and Trademark Office (USPTO).

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