Papers Multilingual NLP
“Multilingual NLP” 태그가 달린 논문 96편 · 필터 해제
Multilinguality Does not Make Sense: Investigating Factors Behind Zero-Shot Transfer in Sense-Aware Tasks
Cross-lingual transfer allows models to perform tasks in languages unseen during training and is often assumed to benefit from increased multilinguality. In this work, we challenge this assumption in the context of two u…
Cross-Lingual TransferMultilingual NLPSenWiCh: Sense-Annotation of Low-Resource Languages for WiC using Hybrid Methods
This paper addresses the critical need for high-quality evaluation datasets in low-resource languages to advance cross-lingual transfer. While cross-lingual transfer offers a key strategy for leveraging multilingual pret…
Cross-Lingual TransferMultilingual NLPShared Path: Unraveling Memorization in Multilingual LLMs through Language Similarities
We present the first comprehensive study of Memorization in Multilingual Large Language Models (MLLMs), analyzing 95 languages using models across diverse model scales, architectures, and memorization definitions. As MLL…
MemorizationMultilingual NLPLAGO: Few-shot Crosslingual Embedding Inversion Attacks via Language Similarity-Aware Graph Optimization
We propose LAGO - Language Similarity-Aware Graph Optimization - a novel approach for few-shot cross-lingual embedding inversion attacks, addressing critical privacy vulnerabilities in multilingual NLP systems. Unlike pr…
Distributed OptimizationMultilingual NLPPrivacy PreservingCross-Linguistic Transfer in Multilingual NLP: The Role of Language Families and Morphology
Cross-lingual transfer has become a crucial aspect of multilingual NLP, as it allows for models trained on resource-rich languages to be applied to low-resource languages more effectively. Recently massively multilingual…
Cross-Lingual TransferMultilingual NLPXLM-RHausaNLP: Current Status, Challenges and Future Directions for Hausa Natural Language Processing
Hausa Natural Language Processing (NLP) has gained increasing attention in recent years, yet remains understudied as a low-resource language despite having over 120 million first-language (L1) and 80 million second-langu…
Language ModelingLanguage ModellingMachine TranslationMultilingual NLP+7Multilingual Prompt Engineering in Large Language Models: A Survey Across NLP Tasks
Large language models (LLMs) have demonstrated impressive performance across a wide range of Natural Language Processing (NLP) tasks. However, ensuring their effectiveness across multiple languages presents unique challe…
Multilingual NLPPrompt EngineeringBias Beyond English: Evaluating Social Bias and Debiasing Methods in a Low-Resource Setting
Social bias in language models can potentially exacerbate social inequalities. Despite it having garnered wide attention, most research focuses on English data. In a low-resource scenario, the models often perform worse …
FairnessMultilingual NLPPoly-FEVER: A Multilingual Fact Verification Benchmark for Hallucination Detection in Large Language Models
Hallucinations in generative AI, particularly in Large Language Models (LLMs), pose a significant challenge to the reliability of multilingual applications. Existing benchmarks for hallucination detection focus primarily…
Fact CheckingFact VerificationHallucinationMultilingual NLPCode-Mixed Telugu-English Hate Speech Detection
Hate speech detection in low-resource languages like Telugu is a growing challenge in NLP. This study investigates transformer-based models, including TeluguHateBERT, HateBERT, DeBERTa, Muril, IndicBERT, Roberta, and Hin…
Hate Speech DetectionMultilingual NLPTranslationHow does a Multilingual LM Handle Multiple Languages?
Multilingual language models have significantly advanced due to rapid progress in natural language processing. Models like BLOOM 1.7B, trained on diverse multilingual datasets, aim to bridge linguistic gaps. However, the…
Multilingual NLPMultilingual Word Embeddingsnamed-entity-recognitionNamed Entity Recognition+9How Good is Your Wikipedia? Auditing Data Quality for Low-resource and Multilingual NLP
Wikipedia's perceived high quality and broad language coverage have established it as a fundamental resource in multilingual NLP. In the context of low-resource languages, however, these quality assumptions are increasin…
ArticlesMultilingual NLPDon't Touch My Diacritics
The common practice of preprocessing text before feeding it into NLP models introduces many decision points which have unintended consequences on model performance. In this opinion piece, we focus on the handling of diac…
Multilingual NLPSandboxAQ's submission to MRL 2024 Shared Task on Multi-lingual Multi-task Information Retrieval
This paper explores the problems of Question Answering (QA) and Named Entity Recognition (NER) in five diverse languages. We tested five Large Language Models with various prompting methods, including zero-shot, chain-of…
Information RetrievalMultilingual Named Entity RecognitionMultilingual NLPMultiple Choice Question Answering (MCQA)+7Adapting LLMs to Hebrew: Unveiling DictaLM 2.0 with Enhanced Vocabulary and Instruction Capabilities
Training large language models (LLMs) in low-resource languages such as Hebrew poses unique challenges. In this paper, we introduce DictaLM2.0 and DictaLM2.0-Instruct, two LLMs derived from the Mistral model, trained on …
Multilingual NLPQuestion AnsweringSentiment AnalysisOn the Evaluation Practices in Multilingual NLP: Can Machine Translation Offer an Alternative to Human Translations?
While multilingual language models (MLMs) have been trained on 100+ languages, they are typically only evaluated across a handful of them due to a lack of available test data in most languages. This is particularly probl…
Machine TranslationMultilingual NLPTranslationDravidian language family through Universal Dependencies lens
The Universal Dependencies (UD) project aims to create a cross-linguistically consistent dependency annotation for multiple languages, to facilitate multilingual NLP. It currently supports 114 languages. Dravidian langua…
Multilingual NLPLeveraging Large Language Models to Measure Gender Representation Bias in Gendered Language Corpora
Large language models (LLMs) often inherit and amplify social biases embedded in their training data. A prominent social bias is gender bias. In this regard, prior work has mainly focused on gender stereotyping bias - th…
Multilingual NLPNews Without Borders: Domain Adaptation of Multilingual Sentence Embeddings for Cross-lingual News Recommendation
Rapidly growing numbers of multilingual news consumers pose an increasing challenge to news recommender systems in terms of providing customized recommendations. First, existing neural news recommenders, even when powere…
Cross-Lingual TransferDomain AdaptationMultilingual NLPNews Recommendation+8ProxyLM: Predicting Language Model Performance on Multilingual Tasks via Proxy Models
Performance prediction is a method to estimate the performance of Language Models (LMs) on various Natural Language Processing (NLP) tasks, mitigating computational costs associated with model capacity and data for fine-…
Language ModelingLanguage ModellingModel SelectionMultilingual NLP