36 citations · 161 across the 34 of their papers we have counts for
15 papers · 1 filter
GanLM: Encoder-Decoder Pre-training with an Auxiliary Discriminator
Jian Yang, Shuming Ma, Li Dong +7
Pre-trained models have achieved remarkable success in natural language processing (NLP). However, existing pre-training methods underutilize the benefits of language understanding…
LVP-M3: Language-aware Visual Prompt for Multilingual Multimodal Machine Translation
Hongcheng Guo, Jiaheng Liu, Haoyang Huang +5
Multimodal Machine Translation (MMT) focuses on enhancing text-only translation with visual features, which has attracted considerable attention from both natural language processi…
PATS: Sensitivity-aware Noisy Learning for Pretrained Language Models
Yupeng Zhang, Hongzhi Zhang, Sirui Wang +2
A wide range of NLP tasks benefit from the fine-tuning of pretrained language models (PLMs). However, a number of redundant parameters which contribute less to the downstream task…
CROP: Zero-shot Cross-lingual Named Entity Recognition with Multilingual Labeled Sequence Translation
Jian Yang, Shaohan Huang, Shuming Ma +6
Named entity recognition (NER) suffers from the scarcity of annotated training data, especially for low-resource languages without labeled data. Cross-lingual NER has been proposed…
UM4: Unified Multilingual Multiple Teacher-Student Model for Zero-Resource Neural Machine Translation
Jian Yang, Yuwei Yin, Shuming Ma +5
Most translation tasks among languages belong to the zero-resource translation problem where parallel corpora are unavailable. Multilingual neural machine translation (MNMT) enable…
An Efficient Coarse-to-Fine Facet-Aware Unsupervised Summarization Framework based on Semantic Blocks
Xinnian Liang, Jing Li, Shuangzhi Wu +4
Unsupervised summarization methods have achieved remarkable results by incorporating representations from pre-trained language models. However, existing methods fail to consider ef…
Modeling Paragraph-Level Vision-Language Semantic Alignment for Multi-Modal Summarization
Chenhao Cui, Xinnian Liang, Shuangzhi Wu +1
Most current multi-modal summarization methods follow a cascaded manner, where an off-the-shelf object detector is first used to extract visual features, then these features are fu…
LogLG: Weakly Supervised Log Anomaly Detection via Log-Event Graph Construction
Hongcheng Guo, Yuhui Guo, Renjie Chen +7
Fully supervised log anomaly detection methods suffer the heavy burden of annotating massive unlabeled log data. Recently, many semi-supervised methods have been proposed to reduce…
HLT-MT: High-resource Language-specific Training for Multilingual Neural Machine Translation
Jian Yang, Yuwei Yin, Shuming Ma +3
Multilingual neural machine translation (MNMT) trained in multiple language pairs has attracted considerable attention due to fewer model parameters and lower training costs by sha…
GTrans: Grouping and Fusing Transformer Layers for Neural Machine Translation
Jian Yang, Yuwei Yin, Liqun Yang +5
Transformer structure, stacked by a sequence of encoder and decoder network layers, achieves significant development in neural machine translation. However, vanilla Transformer mai…
CQR-SQL: Conversational Question Reformulation Enhanced Context-Dependent Text-to-SQL Parsers
Dongling Xiao, Linzheng Chai, Qian-Wen Zhang +3
Context-dependent text-to-SQL is the task of translating multi-turn questions into database-related SQL queries. Existing methods typically focus on making full use of history cont…
TANet: Thread-Aware Pretraining for Abstractive Conversational Summarization
Ze Yang, Liran Wang, Zhoujin Tian +2
Although pre-trained language models (PLMs) have achieved great success and become a milestone in NLP, abstractive conversational summarization remains a challenging but less studi…
Modeling Multi-Granularity Hierarchical Features for Relation Extraction
Xinnian Liang, Shuangzhi Wu, Mu Li +1
Relation extraction is a key task in Natural Language Processing (NLP), which aims to extract relations between entity pairs from given texts. Recently, relation extraction (RE) ha…
TransLog: A Unified Transformer-based Framework for Log Anomaly Detection
Hongcheng Guo, Xingyu Lin, Jian Yang +5
Log anomaly detection is a key component in the field of artificial intelligence for IT operations (AIOps). Considering log data of variant domains, retraining the whole network fo…
PAEG: Phrase-level Adversarial Example Generation for Neural Machine Translation
Juncheng Wan, Jian Yang, Shuming Ma +4
While end-to-end neural machine translation (NMT) has achieved impressive progress, noisy input usually leads models to become fragile and unstable. Generating adversarial examples…