19 citations · 92 across the 21 of their papers we have counts for
23 papers
ColorA11Y: Enhancing Creative Design Workflows with Just-in-Time Color Accessibility Recommendations
Alexa Siu, Rajiv Jain, Abhinav Kannan +7
Effective color contrast in visual design is essential for content accessibility. While existing tools can identify contrast issues, they often operate in isolation from design wor…
FLARE: Diffusion for Hybrid Language Model
Yuchen Zhu, Jing Shi, Chongjian Ge +9
Autoregressive (AR) large language models (LLMs) have achieved broad practical success, but sequential decoding remains a key bottleneck for low-latency deployment. Recent efficien…
DocArena: Turning Raw Documents into Controllable Training Environments for Document Search Agents
Jiamian Wang, Ruiyi Zhang, Tong Yu +5
Recent methods train search agents via reinforcement learning from (question, answer, evidence) tuples without requiring expert trajectories. The tuples serve as the training envir…
OpenExempt: A Diagnostic Benchmark for Legal Reasoning and a Framework for Creating Custom Benchmarks on Demand
Sergio Servantez, Sarah B. Lawsky, Rajiv Jain +2
Reasoning benchmarks have played a crucial role in the progress of language models. Yet rigorous evaluation remains a significant challenge as static question-answer pairs provide…
LegalCore: A Dataset for Event Coreference Resolution in Legal Documents
Kangda Wei, Xi Shi, Jonathan Tong +5
Recognizing events and their coreferential mentions in a document is essential for understanding semantic meanings of text. The existing research on event coreference resolution is…
DocEdit-v2: Document Structure Editing Via Multimodal LLM Grounding
Manan Suri, Puneet Mathur, Franck Dernoncourt +5
Document structure editing involves manipulating localized textual, visual, and layout components in document images based on the user's requests. Past works have shown that multim…
FlexDoc: Flexible Document Adaptation through Optimizing both Content and Layout
Yue Jiang, Christof Lutteroth, Rajiv Jain +4
Designing adaptive documents that are visually appealing across various devices and for diverse viewers is a challenging task. This is due to the wide variety of devices and differ…
DocSynthv2: A Practical Autoregressive Modeling for Document Generation
Sanket Biswas, Rajiv Jain, Vlad I. Morariu +5
While the generation of document layouts has been extensively explored, comprehensive document generation encompassing both layout and content presents a more complex challenge. Th…
Chain of Logic: Rule-Based Reasoning with Large Language Models
Sergio Servantez, Joe Barrow, Kristian Hammond +1
Rule-based reasoning, a fundamental type of legal reasoning, enables us to draw conclusions by accurately applying a rule to a set of facts. We explore causal language models as ru…
Improving a Named Entity Recognizer Trained on Noisy Data with a Few Clean Instances
Zhendong Chu, Ruiyi Zhang, Tong Yu +4
To achieve state-of-the-art performance, one still needs to train NER models on large-scale, high-quality annotated data, an asset that is both costly and time-intensive to accumul…
User-Entity Differential Privacy in Learning Natural Language Models
Phung Lai, NhatHai Phan, Tong Sun +4
In this paper, we introduce a novel concept of user-entity differential privacy (UeDP) to provide formal privacy protection simultaneously to both sensitive entities in textual dat…
Certified Neural Network Watermarks with Randomized Smoothing
Arpit Bansal, Ping-yeh Chiang, Michael Curry +5
Watermarking is a commonly used strategy to protect creators' rights to digital images, videos and audio. Recently, watermarking methods have been extended to deep learning models…
Unified Pretraining Framework for Document Understanding
Jiuxiang Gu, Jason Kuen, Vlad I. Morariu +5
Document intelligence automates the extraction of information from documents and supports many business applications. Recent self-supervised learning methods on large-scale unlabel…
MACRONYM: A Large-Scale Dataset for Multilingual and Multi-Domain Acronym Extraction
Amir Pouran Ben Veyseh, Nicole Meister, Seunghyun Yoon +3
Acronym extraction is the task of identifying acronyms and their expanded forms in texts that is necessary for various NLP applications. Despite major progress for this task in rec…
CLAUSEREC: A Clause Recommendation Framework for AI-aided Contract Authoring
Vinay Aggarwal, Aparna Garimella, Balaji Vasan Srinivasan +2
Contracts are a common type of legal document that frequent in several day-to-day business workflows. However, there has been very limited NLP research in processing such documents…
Readability Research: An Interdisciplinary Approach
Sofie Beier, Sam Berlow, Esat Boucaud +25
Readability is on the cusp of a revolution. Fixed text is becoming fluid as a proliferation of digital reading devices rewrite what a document can do. As past constraints make way…
SelfDoc: Self-Supervised Document Representation Learning
Peizhao Li, Jiuxiang Gu, Jason Kuen +5
We propose SelfDoc, a task-agnostic pre-training framework for document image understanding. Because documents are multimodal and are intended for sequential reading, our framework…
Mitigating the Effects of Reading Interruptions by Providing Reviews and Previews
Namrata Srivastava, Rajiv Jain, Jennifer Healey +2
As reading on mobile devices is becoming more ubiquitous, content is consumed in shorter intervals and is punctuated by frequent interruptions. In this work, we explore the best wa…
Towards Interpreting and Mitigating Shortcut Learning Behavior of NLU Models
Mengnan Du, Varun Manjunatha, Rajiv Jain +5
Recent studies indicate that NLU models are prone to rely on shortcut features for prediction, without achieving true language understanding. As a result, these models fail to gene…
IGA : An Intent-Guided Authoring Assistant
Simeng Sun, Wenlong Zhao, Varun Manjunatha +5
While large-scale pretrained language models have significantly improved writing assistance functionalities such as autocomplete, more complex and controllable writing assistants h…
Text and Style Conditioned GAN for Generation of Offline Handwriting Lines
Brian Davis, Chris Tensmeyer, Brian Price +3
This paper presents a GAN for generating images of handwritten lines conditioned on arbitrary text and latent style vectors. Unlike prior work, which produce stroke points or singl…
Black-box Explanation of Object Detectors via Saliency Maps
Vitali Petsiuk, Rajiv Jain, Varun Manjunatha +4
We propose D-RISE, a method for generating visual explanations for the predictions of object detectors. Utilizing the proposed similarity metric that accounts for both localization…
Using Behavioral Interactions from a Mobile Device to Classify the Reader's Prior Familiarity and Goal Conditions
Sungjin Nam, Zoya Bylinskii, Christopher Tensmeyer +3
A student reads a textbook to learn a new topic; an attorney leafs through familiar legal documents. Each reader may have a different goal for, and prior knowledge of, their readin…