[PDF][PDF] Is ChatGPT a good translator? A preliminary study
This report provides a preliminary evaluation of ChatGPT for machine translation, including
translation prompt, multilingual translation, and translation robustness. We adopt the …
translation prompt, multilingual translation, and translation robustness. We adopt the …
Is ChatGPT a good translator? Yes with GPT-4 as the engine
This report provides a preliminary evaluation of ChatGPT for machine translation, including
translation prompt, multilingual translation, and translation robustness. We adopt the …
translation prompt, multilingual translation, and translation robustness. We adopt the …
Transformer: A general framework from machine translation to others
Abstract Machine translation is an important and challenging task that aims at automatically
translating natural language sentences from one language into another. Recently …
translating natural language sentences from one language into another. Recently …
Exploring human-like translation strategy with large language models
Large language models (LLMs) have demonstrated impressive capabilities in general
scenarios, exhibiting a level of aptitude that approaches, in some aspects even surpasses …
scenarios, exhibiting a level of aptitude that approaches, in some aspects even surpasses …
Chatgpt or grammarly? evaluating chatgpt on grammatical error correction benchmark
ChatGPT is a cutting-edge artificial intelligence language model developed by OpenAI,
which has attracted a lot of attention due to its surprisingly strong ability in answering follow …
which has attracted a lot of attention due to its surprisingly strong ability in answering follow …
Improving the transferability of adversarial samples by path-augmented method
Deep neural networks have achieved unprecedented success on diverse vision tasks.
However, they are vulnerable to adversarial noise that is imperceptible to humans. This …
However, they are vulnerable to adversarial noise that is imperceptible to humans. This …
Transferable adversarial attacks on vision transformers with token gradient regularization
Vision transformers (ViTs) have been successfully deployed in a variety of computer vision
tasks, but they are still vulnerable to adversarial samples. Transfer-based attacks use a local …
tasks, but they are still vulnerable to adversarial samples. Transfer-based attacks use a local …
Token-level self-evolution training for sequence-to-sequence learning
Adaptive training approaches, widely used in sequence-to-sequence models, commonly
reweigh the losses of different target tokens based on priors, eg word frequency. However …
reweigh the losses of different target tokens based on priors, eg word frequency. However …
Redistributing low-frequency words: Making the most of monolingual data in non-autoregressive translation
Abstract Knowledge distillation (KD) is the preliminary step for training non-autoregressive
translation (NAT) models, which eases the training of NAT models at the cost of losing …
translation (NAT) models, which eases the training of NAT models at the cost of losing …
On the complementarity between pre-training and random-initialization for resource-rich machine translation
Pre-Training (PT) of text representations has been successfully applied to low-resource
Neural Machine Translation (NMT). However, it usually fails to achieve notable gains …
Neural Machine Translation (NMT). However, it usually fails to achieve notable gains …