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Found 74 papers, 5 papers with code
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
Wizard of Tasks: A Novel Conversational Dataset for Solving Real-World Tasks in Conversational Settings
Conversational Task Assistants (CTAs) are conversational agents whose goal is to help humans perform real-world tasks.
Identifying High Consideration E-Commerce Search Queries
We consider the task of identifying High Consideration (HC) queries.
Bridging the Gap Between Information Seeking and Product Search Systems: Q&A Recommendation for E-commerce
Consumers on a shopping mission often leverage both product search and information seeking systems, such as web search engines and Question Answering (QA) systems, in an iterative process to improve their understanding of available products and reach a purchase decision.
Generative Explore-Exploit: Training-free Optimization of Generative Recommender Systems using LLM Optimizers
Recommender systems are widely used to suggest engaging content, and Large Language Models (LLMs) have given rise to generative recommenders.
Question Suggestion for Conversational Shopping Assistants Using Product Metadata
Digital assistants have become ubiquitous in e-commerce applications, following the recent advancements in Information Retrieval (IR), Natural Language Processing (NLP) and Generative Artificial Intelligence (AI).
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.
Leveraging Interesting Facts to Enhance User Engagement with Conversational Interfaces
Conversational Task Assistants (CTAs) guide users in performing a multitude of activities, such as making recipes.
Enhancing Low-Resource LLMs Classification with PEFT and Synthetic Data
Large Language Models (LLMs) operating in 0-shot or few-shot settings achieve competitive results in Text Classification tasks.
Controllable Decontextualization of Yes/No Question and Answers into Factual Statements
Yes/No or polar questions represent one of the main linguistic question categories.
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.
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.
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.
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.
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.
Faithful Low-Resource Data-to-Text Generation through Cycle Training
Cycle training uses two models which are inverses of each other: one that generates text from structured data, and one which generates the structured data from natural language text.
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
Preventing Catastrophic Forgetting in Continual Learning of New Natural Language Tasks
In this paper, we approach the problem of incrementally expanding MTL models' capability to solve new tasks over time by distilling the knowledge of an already trained model on n tasks into a new one for solving n+1 tasks.
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.
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.
GEMNET: Effective Gated Gazetteer Representations for Recognizing Complex Entities in Low-context Input
We propose GEMNET, a novel approach for gazetteer knowledge integration, including (1) a flexible Contextual Gazetteer Representation (CGR) encoder that can be fused with any word-level model; and (2) a Mixture-of- Experts gating network that overcomes the feature overuse issue by learning to conditionally combine the context and gazetteer features, instead of assigning them fixed weights.
Evaluating Aggression Identification in Social Media
The task consisted of two sub-tasks - aggression identification (sub-task A) and gendered identification (sub-task B) - in three languages - Bangla, Hindi and English.
Findings of the 2019 Conference on Machine Translation (WMT19)
This paper presents the results of the premier shared task organized alongside the Conference on Machine Translation (WMT) 2019.
A Report on the Third VarDial Evaluation Campaign
In this paper, we present the findings of the Third VarDial Evaluation Campaign organized as part of the sixth edition of the workshop on Natural Language Processing (NLP) for Similar Languages, Varieties and Dialects (VarDial), co-located with NAACL 2019.
UTFPR at SemEval-2019 Task 5: Hate Speech Identification with Recurrent Neural Networks
We tested our approach on the SemEval-2019 Task 5: Multilingual Detection of Hate Speech Against Immigrants and Women in Twitter (HatEval) shared task dataset.
SemEval-2019 Task 6: Identifying and Categorizing Offensive Language in Social Media (OffensEval)
We present the results and the main findings of SemEval-2019 Task 6 on Identifying and Categorizing Offensive Language in Social Media (OffensEval).
Predicting the Type and Target of Offensive Posts in Social Media
In particular, we model the task hierarchically, identifying the type and the target of offensive messages in social media.
Classifying Patent Applications with Ensemble Methods
We present methods for the automatic classification of patent applications using an annotated dataset provided by the organizers of the ALTA 2018 shared task - Classifying Patent Applications.
Native Language Identification With Classifier Stacking and Ensembles
Ensemble methods using multiple classifiers have proven to be among the most successful approaches for the task of Native Language Identification (NLI), achieving the current state of the art.
Classifier Ensembles for Dialect and Language Variety Identification
In this paper we present ensemble-based systems for dialect and language variety identification using the datasets made available by the organizers of the VarDial Evaluation Campaign 2018.
Language Identification and Morphosyntactic Tagging: The Second VarDial Evaluation Campaign
We present the results and the findings of the Second VarDial Evaluation Campaign on Natural Language Processing (NLP) for Similar Languages, Varieties and Dialects.
Benchmarking Aggression Identification in Social Media
For this task, the participants were provided with a dataset of 15, 000 aggression-annotated Facebook Posts and Comments each in Hindi (in both Roman and Devanagari script) and English for training and validation.
German Dialect Identification Using Classifier Ensembles
In this paper we present the GDI_classification entry to the second German Dialect Identification (GDI) shared task organized within the scope of the VarDial Evaluation Campaign 2018.
Discriminating between Indo-Aryan Languages Using SVM Ensembles
In this paper we present a system based on SVM ensembles trained on characters and words to discriminate between five similar languages of the Indo-Aryan family: Hindi, Braj Bhasha, Awadhi, Bhojpuri, and Magahi.
A Portuguese Native Language Identification Dataset
In this paper we present NLI-PT, the first Portuguese dataset compiled for Native Language Identification (NLI), the task of identifying an author's first language based on their second language writing.
A Report on the Complex Word Identification Shared Task 2018
We report the findings of the second Complex Word Identification (CWI) shared task organized as part of the BEA workshop co-located with NAACL-HLT'2018.
Challenges in Discriminating Profanity from Hate Speech
In this study we approach the problem of distinguishing general profanity from hate speech in social media, something which has not been widely considered.
Detecting Hate Speech in Social Media
In this paper we examine methods to detect hate speech in social media, while distinguishing this from general profanity.
Exploring the Use of Text Classification in the Legal Domain
In this paper, we investigate the application of text classification methods to support law professionals.
Complex Word Identification: Challenges in Data Annotation and System Performance
This paper revisits the problem of complex word identification (CWI) following up the SemEval CWI shared task.
A Report on the 2017 Native Language Identification Shared Task
We believe this makes for a more interesting shared task while building on the methods and results from the previous two shared tasks.
Open-Set Language Identification
We present the first open-set language identification experiments using one-class classification.
Including Dialects and Language Varieties in Author Profiling
This paper presents a computational approach to author profiling taking gender and language variety into account.
Unsupervised Text Segmentation Based on Native Language Characteristics
Most work on segmenting text does so on the basis of topic changes, but it can be of interest to segment by other, stylistically expressed characteristics such as change of authorship or native language.
Feature Hashing for Language and Dialect Identification
We evaluate feature hashing for language identification (LID), a method not previously used for this task.
Findings of the VarDial Evaluation Campaign 2017
We present the results of the VarDial Evaluation Campaign on Natural Language Processing (NLP) for Similar Languages, Varieties and Dialects, which we organized as part of the fourth edition of the VarDial workshop at EACL{'}2017.
German Dialect Identification in Interview Transcriptions
This paper presents three systems submitted to the German Dialect Identification (GDI) task at the VarDial Evaluation Campaign 2017.
Arabic Dialect Identification Using iVectors and ASR Transcripts
This paper presents the systems submitted by the MAZA team to the Arabic Dialect Identification (ADI) shared task at the VarDial Evaluation Campaign 2017.
Native Language Identification using Stacked Generalization
Ensemble methods using multiple classifiers have proven to be the most successful approach for the task of Native Language Identification (NLI), achieving the current state of the art.
Subdialectal Differences in Sorani Kurdish
In this study we apply classification methods for detecting subdialectal differences in Sorani Kurdish texts produced in different regions, namely Iran and Iraq.
Arabic Dialect Identification in Speech Transcripts
In this paper we describe a system developed to identify a set of four regional Arabic dialects (Egyptian, Gulf, Levantine, North African) and Modern Standard Arabic (MSA) in a transcribed speech corpus.
Discriminating between Similar Languages and Arabic Dialect Identification: A Report on the Third DSL Shared Task
We present the results of the third edition of the Discriminating between Similar Languages (DSL) shared task, which was organized as part of the VarDial{'}2016 workshop at COLING{'}2016.
Modeling Language Change in Historical Corpora: The Case of Portuguese
This paper presents a number of experiments to model changes in a historical Portuguese corpus composed of literary texts for the purpose of temporal text classification.
Discriminating Similar Languages: Evaluations and Explorations
We present an analysis of the performance of machine learning classifiers on discriminating between similar languages and language varieties.
