https://github.com/hltcoe/colbert-x
공식 코드Transfer Learning Approaches for Building Cross-Language Dense Retrieval Models
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XLM-R
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
Transfer Learning Approaches for Building Cross-Language Dense Retrieval Models
GreekBART: The First Pretrained Greek Sequence-to-Sequence Model
GreekBART: The First Pretrained Greek Sequence-to-Sequence Model
IndoNLI: A Natural Language Inference Dataset for Indonesian
Cross-Lingual Text Classification of Transliterated Hindi and Malayalam
LEXTREME: A Multi-Lingual and Multi-Task Benchmark for the Legal Domain
CICLe: Conformal In-Context Learning for Largescale Multi-Class Food Risk Classification
A Simple and Effective Method to Improve Zero-Shot Cross-Lingual Transfer Learning
FOCUS: Effective Embedding Initialization for Monolingual Specialization of Multilingual Models
Prix-LM: Pretraining for Multilingual Knowledge Base Construction
ESCOXLM-R: Multilingual Taxonomy-driven Pre-training for the Job Market Domain
Lost in Translation, Found in Spans: Identifying Claims in Multilingual Social Media
VLUE: A Multi-Task Benchmark for Evaluating Vision-Language Models
KBioXLM: A Knowledge-anchored Biomedical Multilingual Pretrained Language Model
Improving Cross-Lingual Transfer through Subtree-Aware Word Reordering
Emotion Classification in a Resource Constrained Language Using Transformer-based Approach
The Impact of Cross-Lingual Adjustment of Contextual Word Representations on Zero-Shot Transfer
Exploring the Relationship between Alignment and Cross-lingual Transfer in Multilingual Transformers
XSemPLR: Cross-Lingual Semantic Parsing in Multiple Natural Languages and Meaning Representations
QASiNa: Religious Domain Question Answering using Sirah Nabawiyah
Emotion Classification in a Resource Constrained Language Using Transformer-based Approach
Code-Mixing on Sesame Street: Dawn of the Adversarial Polyglots
DAMP: Doubly Aligned Multilingual Parser for Task-Oriented Dialogue
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.