Search Results for author:
Found 20 papers, 8 papers with code
CSP:Code-Switching Pre-training for Neural Machine Translation
Unlike traditional pre-training method which randomly masks some fragments of the input sentence, the proposed CSP randomly replaces some words in the source sentence with their translation words in the target language.
Exploring Key Point Analysis with Pairwise Generation and Graph Partitioning
Our objective is to train a generative model that can simultaneously provide a score indicating the presence of shared key point between a pair of arguments and generate the shared key point.
EcomGPT-CT: Continual Pre-training of E-commerce Large Language Models with Semi-structured Data
Experimental results demonstrate the effectiveness of continual pre-training of E-commerce LLMs and the efficacy of our devised data mixing strategy.
SeqGPT: An Out-of-the-box Large Language Model for Open Domain Sequence Understanding
However, LLMs are sometimes too footloose for natural language understanding (NLU) tasks which always have restricted output and input format.
End-to-End Beam Retrieval for Multi-Hop Question Answering
This approach models the multi-hop retrieval process in an end-to-end manner by jointly optimizing an encoder and two classification heads across all hops.
Ranked #1 on
Question Answering
on HotpotQA
EcomGPT: Instruction-tuning Large Language Models with Chain-of-Task Tasks for E-commerce
EcomInstruct scales up the data size and task diversity by constructing atomic tasks with E-commerce basic data types, such as product information, user reviews.
DAMO-NLP at SemEval-2023 Task 2: A Unified Retrieval-augmented System for Multilingual Named Entity Recognition
Also, we discover that the limited context length causes the retrieval knowledge to be invisible to the model.
Multilingual Named Entity Recognition
named-entity-recognition
+4
Zero-Shot Information Extraction via Chatting with ChatGPT
Zero-shot information extraction (IE) aims to build IE systems from the unannotated text.
DAMO-NLP at NLPCC-2022 Task 2: Knowledge Enhanced Robust NER for Speech Entity Linking
Speech Entity Linking aims to recognize and disambiguate named entities in spoken languages.
PM-MMUT: Boosted Phone-Mask Data Augmentation using Multi-Modeling Unit Training for Phonetic-Reduction-Robust E2E Speech Recognition
To boost the performance of PMT, we propose multi-modeling unit training (MMUT) architecture fusion with PMT (PM-MMUT).
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
Adversarial Sample Detection for Speaker Verification by Neural Vocoders
We also show that the neural vocoder adopted in the detection framework is dataset-independent.
Stacked Acoustic-and-Textual Encoding: Integrating the Pre-trained Models into Speech Translation Encoders
To our knowledge, we are the first to develop an end-to-end ST system that achieves comparable or even better BLEU performance than the cascaded ST counterpart when large-scale ASR and MT data is available.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+4
Dynamic Curriculum Learning for Low-Resource Neural Machine Translation
This eases training by highlighting easy samples that the current model has enough competence to learn.
Code-switching pre-training for neural machine translation
Unlike traditional pre-training method which randomly masks some fragments of the input sentence, the proposed CSP randomly replaces some words in the source sentence with their translation words in the target language.
Cognitive Representation Learning of Self-Media Online Article Quality
The automatic quality assessment of self-media online articles is an urgent and new issue, which is of great value to the online recommendation and search.
A Multi-oriented Chinese Keyword Spotter Guided by Text Line Detection
Chinese keyword spotting is a challenging task as there is no visual blank for Chinese words.
Utterance-level end-to-end language identification using attention-based CNN-BLSTM
In this paper, we present an end-to-end language identification framework, the attention-based Convolutional Neural Network-Bidirectional Long-short Term Memory (CNN-BLSTM).
TencentFmRD Neural Machine Translation for WMT18
Our systems are neural machine translation systems trained with our original system TenTrans.
Addressing Domain Adaptation for Chinese Word Segmentation with Global Recurrent Structure
Boundary features are widely used in traditional Chinese Word Segmentation (CWS) methods as they can utilize unlabeled data to help improve the Out-of-Vocabulary (OOV) word recognition performance.
Bi-LSTM Neural Networks for Chinese Grammatical Error Diagnosis
Grammatical Error Diagnosis for Chinese has always been a challenge for both foreign learners and NLP researchers, for the variousity of grammar and the flexibility of expression.
