Search Results for author:
Found 6 papers, 3 papers with code
Document Understanding Dataset and Evaluation (DUDE)
We call on the Document AI (DocAI) community to reevaluate current methodologies and embrace the challenge of creating more practically-oriented benchmarks.
STable: Table Generation Framework for Encoder-Decoder Models
The output structure of database-like tables, consisting of values structured in horizontal rows and vertical columns identifiable by name, can cover a wide range of NLP tasks.
Joint Entity and Relation Extraction
Knowledge Base Population
Going Full-TILT Boogie on Document Understanding with Text-Image-Layout Transformer
We address the challenging problem of Natural Language Comprehension beyond plain-text documents by introducing the TILT neural network architecture which simultaneously learns layout information, visual features, and textual semantics.
Ranked #7 on
Visual Question Answering (VQA)
on InfographicVQA
(using extra training data)
Dynamic Boundary Time Warping for Sub-sequence Matching with Few Examples
The paper presents a novel method of finding a fragment in a long temporal sequence similar to the set of shorter sequences.
Ranked #2 on
Semantic Retrieval
on Contract Discovery
ApplicaAI at SemEval-2020 Task 11: On RoBERTa-CRF, Span CLS and Whether Self-Training Helps Them
This paper presents the winning system for the propaganda Technique Classification (TC) task and the second-placed system for the propaganda Span Identification (SI) task.
Contract Discovery: Dataset and a Few-Shot Semantic Retrieval Challenge with Competitive Baselines
We propose a new shared task of semantic retrieval from legal texts, in which a so-called contract discovery is to be performed, where legal clauses are extracted from documents, given a few examples of similar clauses from other legal acts.
Ranked #1 on
Semantic Retrieval
on Contract Discovery
