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20202026
most citedText and Style Conditioned GAN for Generation of Offline Handwriting Lines

19 citations · 80 across the 17 of their papers we have counts for

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10 papers · 1 filter

cs.CL2026

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…

cs.CL2025

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…

cs.CL2024

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…

cs.CL20243 cited

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…

cs.CL2023

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…

cs.CL202217 cited

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…