Papers with Code 아카이브

XLM-R

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법전체 데이터셋

하위 태스크

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평가표

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보존된 평가 기록

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코드

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

https://github.com/pwc-1/Paper-9/tree/main/1/xlm_roberta

Unsupervised Cross-lingual Representation Learning at Scale

https://github.com/pwc-1/Paper-9/tree/main/5/xlm

XLM-V: Overcoming the Vocabulary Bottleneck in Multilingual Masked Language Models

https://github.com/rijgersberg/geitje

DUMB: A Benchmark for Smart Evaluation of Dutch Models

https://github.com/rita-nlp/italic

MASSIVE: A 1M-Example Multilingual Natural Language Understanding Dataset with 51 Typologically-Diverse Languages

https://github.com/sanderwood/clamp3

Unsupervised Cross-lingual Representation Learning at Scale

https://github.com/sb-b/steps-parser

Applying Occam's Razor to Transformer-Based Dependency Parsing: What Works, What Doesn't, and What is Really Necessary

https://github.com/skesiraju/pylibs

A Bayesian Multilingual Document Model for Zero-shot Topic Identification and Discovery

https://github.com/somiltg/xquad

Unsupervised Cross-lingual Representation Learning at Scale

https://github.com/stanleyjzheng/ignitionhacks

Unsupervised Cross-lingual Representation Learning at Scale

https://github.com/stareru/csqa_debertav3

DeBERTaV3: Improving DeBERTa using ELECTRA-Style Pre-Training with Gradient-Disentangled Embedding Sharing

https://github.com/zengyan-97/x-vlm

X$^2$-VLM: All-In-One Pre-trained Model For Vision-Language Tasks

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