204 citations · 243 across the 16 of their papers we have counts for
7 papers · 1 filter
Automatic Multi-Path Web Story Creation from a Structural Article
Daniel Nkemelu, Peggy Chi, Daniel Castro Chin +2
Web articles such as Wikipedia serve as one of the major sources of knowledge dissemination and online learning. However, their in-depth information--often in a dense text format--…
Ambiguity-Aware In-Context Learning with Large Language Models
Lingyu Gao, Aditi Chaudhary, Krishna Srinivasan +3
In-context learning (ICL) i.e. showing LLMs only a few task-specific demonstrations has led to downstream gains with no task-specific fine-tuning required. However, LLMs are sensit…
Exploring the Viability of Synthetic Query Generation for Relevance Prediction
Aditi Chaudhary, Karthik Raman, Krishna Srinivasan +3
Query-document relevance prediction is a critical problem in Information Retrieval systems. This problem has increasingly been tackled using (pretrained) transformer-based models w…
Characterizing Image Accessibility on Wikipedia across Languages
Elisa Kreiss, Krishna Srinivasan, Tiziano Piccardi +5
We make a first attempt to characterize image accessibility on Wikipedia across languages, present new experimental results that can inform efforts to assess description quality, a…
WikiWeb2M: A Page-Level Multimodal Wikipedia Dataset
Andrea Burns, Krishna Srinivasan, Joshua Ainslie +5
Webpages have been a rich resource for language and vision-language tasks. Yet only pieces of webpages are kept: image-caption pairs, long text articles, or raw HTML, never all in…
A Suite of Generative Tasks for Multi-Level Multimodal Webpage Understanding
Andrea Burns, Krishna Srinivasan, Joshua Ainslie +5
Webpages have been a rich, scalable resource for vision-language and language only tasks. Yet only pieces of webpages are kept in existing datasets: image-caption pairs, long text…
AToMiC: An Image/Text Retrieval Test Collection to Support Multimedia Content Creation
Jheng-Hong Yang, Carlos Lassance, Rafael Sampaio de Rezende +4
This paper presents the AToMiC (Authoring Tools for Multimedia Content) dataset, designed to advance research in image/text cross-modal retrieval. While vision-language pretrained…