Search Results for author:
Found 22 papers, 2 papers with code
Neural OCR Post-Hoc Correction of Historical Corpora
Optical character recognition (OCR) is crucial for a deeper access to historical collections.
Optical Character Recognition
Optical Character Recognition (OCR)
Citation Needed: A Taxonomy and Algorithmic Assessment of Wikipedia's Verifiability
In this paper, we aim to provide an empirical characterization of the reasons why and how Wikipedia cites external sources to comply with its own verifiability guidelines.
Approaches for Enriching and Improving Textual Knowledge Bases
Even in cases where citations are provided, there are no explicit indicators for the span of a citation for a given piece of text.
Fine Grained Citation Span for References in Wikipedia
For a Wikipedia article, determining the \emph{citation span} of a citation, i. e. what content is covered by a citation, is important as it helps decide for which content citations are still missing.
Finding News Citations for Wikipedia
An important editing policy in Wikipedia is to provide citations for added statements in Wikipedia pages, where statements can be arbitrary pieces of text, ranging from a sentence to a paragraph.
Automated News Suggestions for Populating Wikipedia Entity Pages
We propose a two-stage supervised approach for suggesting news articles to entity pages for a given state of Wikipedia.
Neural Based Statement Classification for Biased Language
Biased language is introduced through the presence of inflammatory words or phrases, or statements that may be incorrect or one-sided, thus violating such consensus.
FAE: A Fairness-Aware Ensemble Framework
In the post-processing step, we tackle the problem of class overlapping by shifting the decision boundary in the direction of fairness.
SDR: Efficient Neural Re-ranking using Succinct Document Representation
BERT based ranking models have achieved superior performance on various information retrieval tasks.
SemEval-2022 Task 11: Multilingual Complex Named Entity Recognition (MultiCoNER)
Divided into 13 tracks, the task focused on methods to identify complex named entities (like names of movies, products and groups) in 11 languages in both monolingual and multi-lingual scenarios.
Dynamic Gazetteer Integration in Multilingual Models for Cross-Lingual and Cross-Domain Named Entity Recognition
Named entity recognition (NER) in a real-world setting remains challenging and is impacted by factors like text genre, corpus quality, and data availability.
Cross-Domain Named Entity Recognition
Cross-Lingual Transfer
+4
MultiCoNER: A Large-scale Multilingual dataset for Complex Named Entity Recognition
We present MultiCoNER, a large multilingual dataset for Named Entity Recognition that covers 3 domains (Wiki sentences, questions, and search queries) across 11 languages, as well as multilingual and code-mixing subsets.
Reinforced Question Rewriting for Conversational Question Answering
Furthermore, human evaluation shows that our method can generate more accurate and detailed rewrites when compared to human annotations.
SemEval-2023 Task 2: Fine-grained Multilingual Named Entity Recognition (MultiCoNER 2)
The task highlights the need for future research on improving NER robustness on noisy data containing complex entities.
Multilingual Named Entity Recognition
named-entity-recognition
+3
Answering Unanswered Questions through Semantic Reformulations in Spoken QA
Spoken Question Answering (QA) is a key feature of voice assistants, usually backed by multiple QA systems.
Generate-then-Retrieve: Intent-Aware FAQ Retrieval in Product Search
We propose an intent-aware FAQ retrieval system consisting of (1) an intent classifier that predicts when a user's information need can be answered by an FAQ; (2) a reformulation model that rewrites a query into a natural question.
MultiCoNER v2: a Large Multilingual dataset for Fine-grained and Noisy Named Entity Recognition
We present MULTICONER V2, a dataset for fine-grained Named Entity Recognition covering 33 entity classes across 12 languages, in both monolingual and multilingual settings.
InstructPTS: Instruction-Tuning LLMs for Product Title Summarization
E-commerce product catalogs contain billions of items.
Follow-on Question Suggestion via Voice Hints for Voice Assistants
Using a new dataset of 6681 input questions and human written hints, we evaluated the models with automatic metrics and human evaluation.
Instant Answering in E-Commerce Buyer-Seller Messaging using Message-to-Question Reformulation
E-commerce customers frequently seek detailed product information for purchase decisions, commonly contacting sellers directly with extended queries.
Controllable Decontextualization of Yes/No Question and Answers into Factual Statements
Yes/No or polar questions represent one of the main linguistic question categories.
Identifying Shopping Intent in Product QA for Proactive Recommendations
We focus on the domain of e-commerce, namely in identifying Shopping Product Questions (SPQs), where the user asking a product-related question may have an underlying shopping need.
