Search Results for author: Haoyang Huang

Found 23 papers, 7 papers with code

Not All Metrics Are Guilty: Improving NLG Evaluation with LLM Paraphrasing

1 code implementation24 May 2023 Tianyi Tang, Hongyuan Lu, Yuchen Eleanor Jiang, Haoyang Huang, Dongdong Zhang, Wayne Xin Zhao, Furu Wei

Most research about natural language generation (NLG) relies on evaluation benchmarks with limited references for a sample, which may result in poor correlations with human judgements.

Machine Translation Text Generation +1

One-stop Training of Multiple Capacity Models

no code implementations23 May 2023 Lan Jiang, Haoyang Huang, Dongdong Zhang, Rui Jiang, Furu Wei

Notably, the analysis demonstrates that our method significantly influences the initial training process, leading to more efficient convergence and superior solutions.

Knowledge Distillation Machine Translation +1

Chain-of-Dictionary Prompting Elicits Translation in Large Language Models

no code implementations11 May 2023 Hongyuan Lu, Haoyang Huang, Dongdong Zhang, Haoran Yang, Wai Lam, Furu Wei

Large language models (LLMs) have shown surprisingly good performance in multilingual neural machine translation (MNMT) even when trained without parallel data.

Machine Translation Translation

GanLM: Encoder-Decoder Pre-training with an Auxiliary Discriminator

1 code implementation20 Dec 2022 Jian Yang, Shuming Ma, Li Dong, Shaohan Huang, Haoyang Huang, Yuwei Yin, Dongdong Zhang, Liqun Yang, Furu Wei, Zhoujun Li

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.

Denoising Text Generation

Advancing Multilingual Pre-training: TRIP Triangular Document-level Pre-training for Multilingual Language Models

no code implementations15 Dec 2022 Hongyuan Lu, Haoyang Huang, Shuming Ma, Dongdong Zhang, Wai Lam, Furu Wei

Despite the success of multilingual sequence-to-sequence pre-training, most existing approaches rely on document-level monolingual corpora in many different languages, sentence-level bilingual corpora,\footnote{In this paper, we use `bilingual corpora' to denote parallel corpora with `bilingual translation pairs' in many different language pairs, each consisting of two sentences/documents with the same meaning written in different languages.

Abstractive Text Summarization Cross-Lingual Abstractive Summarization +3

LVP-M3: Language-aware Visual Prompt for Multilingual Multimodal Machine Translation

no code implementations19 Oct 2022 Hongcheng Guo, Jiaheng Liu, Haoyang Huang, Jian Yang, Zhoujun Li, Dongdong Zhang, Zheng Cui, Furu Wei

To this end, we first propose the Multilingual MMT task by establishing two new Multilingual MMT benchmark datasets covering seven languages.

Multimodal Machine Translation Translation

Revamping Multilingual Agreement Bidirectionally via Switched Back-translation for Multilingual Neural Machine Translation

no code implementations28 Sep 2022 Hongyuan Lu, Haoyang Huang, Shuming Ma, Dongdong Zhang, Furu Wei, Wai Lam

Despite the fact that multilingual agreement (MA) has shown its importance for multilingual neural machine translation (MNMT), current methodologies in the field have two shortages: (i) require parallel data between multiple language pairs, which is not always realistic and (ii) optimize the agreement in an ambiguous direction, which hampers the translation performance.

Document Level Machine Translation Document Translation +2

GTrans: Grouping and Fusing Transformer Layers for Neural Machine Translation

1 code implementation29 Jul 2022 Jian Yang, Yuwei Yin, Liqun Yang, Shuming Ma, Haoyang Huang, Dongdong Zhang, Furu Wei, Zhoujun Li

Transformer structure, stacked by a sequence of encoder and decoder network layers, achieves significant development in neural machine translation.

Machine Translation Translation

NÜWA-LIP: Language Guided Image Inpainting with Defect-free VQGAN

no code implementations10 Feb 2022 Minheng Ni, Chenfei Wu, Haoyang Huang, Daxin Jiang, WangMeng Zuo, Nan Duan

Language guided image inpainting aims to fill in the defective regions of an image under the guidance of text while keeping non-defective regions unchanged.

Image Inpainting

SMDT: Selective Memory-Augmented Neural Document Translation

no code implementations5 Jan 2022 Xu Zhang, Jian Yang, Haoyang Huang, Shuming Ma, Dongdong Zhang, Jinlong Li, Furu Wei

Existing document-level neural machine translation (NMT) models have sufficiently explored different context settings to provide guidance for target generation.

Document Level Machine Translation Document Translation +3

Hierarchical Context-aware Network for Dense Video Event Captioning

1 code implementation ACL 2021 Lei Ji, Xianglin Guo, Haoyang Huang, Xilin Chen

Dense video event captioning aims to generate a sequence of descriptive captions for each event in a long untrimmed video.

Multilingual Agreement for Multilingual Neural Machine Translation

no code implementations ACL 2021 Jian Yang, Yuwei Yin, Shuming Ma, Haoyang Huang, Dongdong Zhang, Zhoujun Li, Furu Wei

Although multilingual neural machine translation (MNMT) enables multiple language translations, the training process is based on independent multilingual objectives.

Machine Translation Translation

M3P: Learning Universal Representations via Multitask Multilingual Multimodal Pre-training

1 code implementation CVPR 2021 Minheng Ni, Haoyang Huang, Lin Su, Edward Cui, Taroon Bharti, Lijuan Wang, Jianfeng Gao, Dongdong Zhang, Nan Duan

We present M3P, a Multitask Multilingual Multimodal Pre-trained model that combines multilingual pre-training and multimodal pre-training into a unified framework via multitask pre-training.

Image Captioning Image Retrieval +4

XGPT: Cross-modal Generative Pre-Training for Image Captioning

no code implementations3 Mar 2020 Qiaolin Xia, Haoyang Huang, Nan Duan, Dong-dong Zhang, Lei Ji, Zhifang Sui, Edward Cui, Taroon Bharti, Xin Liu, Ming Zhou

While many BERT-based cross-modal pre-trained models produce excellent results on downstream understanding tasks like image-text retrieval and VQA, they cannot be applied to generation tasks directly.

Data Augmentation Denoising +7

UniVL: A Unified Video and Language Pre-Training Model for Multimodal Understanding and Generation

2 code implementations15 Feb 2020 Huaishao Luo, Lei Ji, Botian Shi, Haoyang Huang, Nan Duan, Tianrui Li, Jason Li, Taroon Bharti, Ming Zhou

However, most of the existing multimodal models are pre-trained for understanding tasks, leading to a pretrain-finetune discrepancy for generation tasks.

 Ranked #1 on Action Segmentation on COIN (using extra training data)

Action Segmentation Language Modelling +2

Improving the Robustness of Deep Reading Comprehension Models by Leveraging Syntax Prior

no code implementations WS 2019 Bowen Wu, Haoyang Huang, Zongsheng Wang, Qihang Feng, Jingsong Yu, Baoxun Wang

Despite the remarkable progress on Machine Reading Comprehension (MRC) with the help of open-source datasets, recent studies indicate that most of the current MRC systems unfortunately suffer from weak robustness against adversarial samples.

Machine Reading Comprehension

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