SOTAVerified

Cross-Lingual Transfer

Cross-lingual transfer refers to transfer learning 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.

Papers

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Showing 326–350 of 782 papers

TitleStatusHype
One For All & All For One: Bypassing Hyperparameter Tuning with Model Averaging For Cross-Lingual TransferCode0
ToPro: Token-Level Prompt Decomposition for Cross-Lingual Sequence Labeling TasksCode0
Oolong: Investigating What Makes Transfer Learning Hard with Controlled StudiesCode0
Overlap-based Vocabulary Generation Improves Cross-lingual Transfer Among Related LanguagesCode0
How to (Properly) Evaluate Cross-Lingual Word Embeddings: On Strong Baselines, Comparative Analyses, and Some MisconceptionsCode0
Boosting Cross-Lingual Transfer via Self-Learning with Uncertainty EstimationCode0
Cross-Lingual Approaches to Reference Resolution in Dialogue Systems—0
Efficiently Adapting Pretrained Language Models To New Languages—0
A Systematic Analysis of Subwords and Cross-Lingual Transfer in Multilingual Translation—0
Efficient Cross-Lingual Transfer for Chinese Stable Diffusion with Images as Pivots—0
Effects of Language Relatedness for Cross-lingual Transfer Learning in Character-Based Language Models—0
Cross-lingual and Supervised Models for Morphosyntactic Annotation: a Comparison on Romanian—0
A Survey of Multilingual Models for Automatic Speech Recognition—0
A Multi-dimensional Evaluation of Tokenizer-free Multilingual Pretrained Models—0
Earth Mover's Distance Minimization for Unsupervised Bilingual Lexicon Induction—0
Dynamic Gazetteer Integration in Multilingual Models for Cross-Lingual and Cross-Domain Named Entity Recognition—0
Cross-lingual alignment transfer: a chicken-and-egg story?—0
Dual-view Curricular Optimal Transport for Cross-lingual Cross-modal Retrieval—0
Don't Parse, Insert: Multilingual Semantic Parsing with Insertion Based Decoding—0
Cross-lingual Alignment Methods for Multilingual BERT: A Comparative Study—0
A Survey Of Cross-lingual Word Embedding Models—0
Don’t Forget Cheap Training Signals Before Building Unsupervised Bilingual Word Embeddings—0
Cross-lingual Adaption Model-Agnostic Meta-Learning for Natural Language Understanding—0
Don’t Forget Cheap Training Signals Before Building Unsupervised Bilingual Word Embeddings—0
Don't Forget Cheap Training Signals Before Building Unsupervised Bilingual Word Embeddings—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1PaLM 2 (few-shot)Accuracy94.4—Unverified
2mT0-13BAccuracy84.45—Unverified
3RoBERTa Large (translate test)Accuracy76.05—Unverified
4BLOOMZAccuracy75.5—Unverified
5MAD-X BaseAccuracy60.94—Unverified
6mGPTAccuracy55.5—Unverified