Search Results for author:
Found 9 papers, 3 papers with code
m3P: Towards Multimodal Multilingual Translation with Multimodal Prompt
Our method aims to minimize the representation distance of different languages by regarding the image as a central language.
OWL: A Large Language Model for IT Operations
However, there is a lack of specialized LLMs for IT operations.
MT4CrossOIE: Multi-stage Tuning for Cross-lingual Open Information Extraction
Cross-lingual open information extraction aims to extract structured information from raw text across multiple languages.
QURG: Question Rewriting Guided Context-Dependent Text-to-SQL Semantic Parsing
Context-dependent Text-to-SQL aims to translate multi-turn natural language questions into SQL queries.
HanoiT: Enhancing Context-aware Translation via Selective Context
Context-aware neural machine translation aims to use the document-level context to improve translation quality.
GanLM: Encoder-Decoder Pre-training with an Auxiliary Discriminator
Inspired by the idea of Generative Adversarial Networks (GANs), we propose a GAN-style model for encoder-decoder pre-training by introducing an auxiliary discriminator, unifying the ability of language understanding and generation in a single model.
Knowledge Distillation based Contextual Relevance Matching for E-commerce Product Search
In this paper, we design an efficient knowledge distillation framework for e-commerce relevance matching to integrate the respective advantages of Transformer-style models and classical relevance matching models.
GTrans: Grouping and Fusing Transformer Layers for Neural Machine Translation
Transformer structure, stacked by a sequence of encoder and decoder network layers, achieves significant development in neural machine translation.
The distance between the weights of the neural network is meaningful
In the application of neural networks, we need to select a suitable model based on the problem complexity and the dataset scale.
