Cross-Lingual Paraphrase Identification
5 papers with code • 1 benchmarks • 2 datasets
PAWS-X
SV-Ident
Most implemented papers
ByT5: Towards a token-free future with pre-trained byte-to-byte models
Most widely-used pre-trained language models operate on sequences of tokens corresponding to word or subword units.
Rethinking embedding coupling in pre-trained language models
PaddlePaddle/PaddleNLP
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ICLR 2021
We re-evaluate the standard practice of sharing weights between input and output embeddings in state-of-the-art pre-trained language models.
mGPT: Few-Shot Learners Go Multilingual
ai-forever/mgpt
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Recent studies report that autoregressive language models can successfully solve many NLP tasks via zero- and few-shot learning paradigms, which opens up new possibilities for using the pre-trained language models.
PromptBench: Towards Evaluating the Robustness of Large Language Models on Adversarial Prompts
The increasing reliance on Large Language Models (LLMs) across academia and industry necessitates a comprehensive understanding of their robustness to prompts.
Do Multilingual Language Models Think Better in English?
In this work, we introduce a new approach called self-translate, which overcomes the need of an external translation system by leveraging the few-shot translation capabilities of multilingual language models.
