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Cross-Lingual

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Cross-lingual natural language processing is the task of using data and models available for one language for which ample such resources are available (e.g., English) to solve tasks in another, commonly more low-resource, language.

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/boleima/profit

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Is Prompt-Based Finetuning Always Better than Vanilla Finetuning? Insights from Cross-Lingual Language Understanding

https://github.com/boleima/topro

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ToPro: Token-Level Prompt Decomposition for Cross-Lingual Sequence Labeling Tasks

https://github.com/bplank/DaNplus

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DaN+: Danish Nested Named Entities and Lexical Normalization

https://github.com/bplank/danish_ner_transfer

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Neural Cross-Lingual Transfer and Limited Annotated Data for Named Entity Recognition in Danish

https://github.com/cambridgeltl/adversarial-postspec

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Adversarial Propagation and Zero-Shot Cross-Lingual Transfer of Word Vector Specialization

https://github.com/cambridgeltl/composable-sft

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Composable Sparse Fine-Tuning for Cross-Lingual Transfer

https://github.com/cambridgeltl/parameter-factorization

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Parameter Space Factorization for Zero-Shot Learning across Tasks and Languages

https://github.com/cambridgeltl/sapbert

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Learning Domain-Specialised Representations for Cross-Lingual Biomedical Entity Linking

https://github.com/cambridgeltl/xcopa

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MAD-X: An Adapter-Based Framework for Multi-Task Cross-Lingual Transfer

https://github.com/ccasimiro88/self-distillation-gxlt-qa

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Promoting Generalized Cross-lingual Question Answering in Few-resource Scenarios via Self-knowledge Distillation

https://github.com/ccsasuke/adan

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Adversarial Deep Averaging Networks for Cross-Lingual Sentiment Classification

https://github.com/charlottepouw/crosslingual-complexity-transfer

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Cross-Lingual Transfer of Cognitive Processing Complexity

https://github.com/ciarabee/fake_news_classification

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Transforming Fake News: Robust Generalisable News Classification Using Transformers

https://github.com/cindyxinyiwang/emea

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Efficient Test Time Adapter Ensembling for Low-resource Language Varieties

https://github.com/cindyxinyiwang/multiview-subword-regularization

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Multi-view Subword Regularization

https://github.com/cisnlp/mplm-sim

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mPLM-Sim: Better Cross-Lingual Similarity and Transfer in Multilingual Pretrained Language Models

https://github.com/cisnlp/transliteration-ppa

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Breaking the Script Barrier in Multilingual Pre-Trained Language Models with Transliteration-Based Post-Training Alignment

https://github.com/clarinsi/megahr-crossling

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Predicting Concreteness and Imageability of Words Within and Across Languages via Word Embeddings

https://github.com/cltl/unkown_script

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Unknown Script: Impact of Script on Cross-Lingual Transfer

https://github.com/coastalcph/seq2sparql

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Compositional Generalization in Multilingual Semantic Parsing over Wikidata

https://github.com/codogogo/xling-eval

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How to (Properly) Evaluate Cross-Lingual Word Embeddings: On Strong Baselines, Comparative Analyses, and Some Misconceptions

https://github.com/copenlu/X-MAML

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Zero-Shot Cross-Lingual Transfer with Meta Learning

https://github.com/cpjku/wechsel

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WECHSEL: Effective initialization of subword embeddings for cross-lingual transfer of monolingual language models

https://github.com/cross-lingual-ner/projection-data-transfer-cross-lingual-ner

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Revisiting Projection-based Data Transfer for Cross-Lingual Named Entity Recognition in Low-Resource Languages

https://github.com/csalt-research/llm-based-augmentations-with-effective-data-selection

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Boosting Zero-Shot Crosslingual Performance using LLM-Based Augmentations with Effective Data Selection

https://github.com/csalt-research/translation-errors-crosslingual-learning

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Translation Errors Significantly Impact Low-Resource Languages in Cross-Lingual Learning

https://github.com/csjianyang/multilingual-multimodal-nlp

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MT4CrossOIE: Multi-stage Tuning for Cross-lingual Open Information Extraction

https://github.com/csu-signal/xlingual-robustness

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Cross-Lingual Transfer Robustness to Lower-Resource Languages on Adversarial Datasets

https://github.com/dadelani/sib-200

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SIB-200: A Simple, Inclusive, and Big Evaluation Dataset for Topic Classification in 200+ Languages and Dialects

https://github.com/dair-iitd/SSP

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SSP: Self-Supervised Prompting for Cross-Lingual Transfer to Low-Resource Languages using Large Language Models

https://github.com/dair-iitd/zgul

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ZGUL: Zero-shot Generalization to Unseen Languages using Multi-source Ensembling of Language Adapters

https://github.com/damo-nlp-sg/adamergex

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AdaMergeX: Cross-Lingual Transfer with Large Language Models via Adaptive Adapter Merging

https://github.com/damo-nlp-sg/contproto

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Improving Self-training for Cross-lingual Named Entity Recognition with Contrastive and Prototype Learning

https://github.com/damo-nlp-sg/dpa

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Enhancing Cross-lingual Prompting with Dual Prompt Augmentation

https://github.com/dannigt/mid-align

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Middle-Layer Representation Alignment for Cross-Lingual Transfer in Fine-Tuned LLMs

https://github.com/deokhk/cbp

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Cross-lingual Back-Parsing: Utterance Synthesis from Meaning Representation for Zero-Resource Semantic Parsing

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.