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Bort: Towards Explainable Neural Networks with Bounded Orthogonal Constraint
Borui Zhang, Wenzhao Zheng, Jie Zhou +1
Deep learning has revolutionized human society, yet the black-box nature of deep neural networks hinders further application to reliability-demanded industries. In the attempt to u…
Summary-Oriented Vision Modeling for Multimodal Abstractive Summarization
Yunlong Liang, Fandong Meng, Jinan Xu +3
Multimodal abstractive summarization (MAS) aims to produce a concise summary given the multimodal data (text and vision). Existing studies mainly focus on how to effectively use th…
Understanding Translationese in Cross-Lingual Summarization
Jiaan Wang, Fandong Meng, Yunlong Liang +4
Given a document in a source language, cross-lingual summarization (CLS) aims at generating a concise summary in a different target language. Unlike monolingual summarization (MS),…
FLAG3D: A 3D Fitness Activity Dataset with Language Instruction
Yansong Tang, Jinpeng Liu, Aoyang Liu +6
With the continuously thriving popularity around the world, fitness activity analytic has become an emerging research topic in computer vision. While a variety of new tasks and alg…
DC-MBR: Distributional Cooling for Minimum Bayesian Risk Decoding
Jianhao Yan, Jin Xu, Fandong Meng +2
Minimum Bayesian Risk Decoding (MBR) emerges as a promising decoding algorithm in Neural Machine Translation. However, MBR performs poorly with label smoothing, which is surprising…
Diffusion-SDF: Text-to-Shape via Voxelized Diffusion
Muheng Li, Yueqi Duan, Jie Zhou +1
With the rising industrial attention to 3D virtual modeling technology, generating novel 3D content based on specified conditions (e.g. text) has become a hot issue. In this paper,…
Findings of the WMT 2022 Shared Task on Translation Suggestion
Zhen Yang, Fandong Meng, Yingxue Zhang +2
We report the result of the first edition of the WMT shared task on Translation Suggestion (TS). The task aims to provide alternatives for specific words or phrases given the entir…
Token-Label Alignment for Vision Transformers
Han Xiao, Wenzhao Zheng, Zheng Zhu +2
Data mixing strategies (e.g., CutMix) have shown the ability to greatly improve the performance of convolutional neural networks (CNNs). They mix two images as inputs for training…
OPERA: Omni-Supervised Representation Learning with Hierarchical Supervisions
Chengkun Wang, Wenzhao Zheng, Zheng Zhu +2
The pretrain-finetune paradigm in modern computer vision facilitates the success of self-supervised learning, which tends to achieve better transferability than supervised learning…
Summer: WeChat Neural Machine Translation Systems for the WMT22 Biomedical Translation Task
Ernan Li, Fandong Meng, Jie Zhou
This paper introduces WeChat's participation in WMT 2022 shared biomedical translation task on Chinese to English. Our systems are based on the Transformer, and use several differe…
BJTU-WeChat's Systems for the WMT22 Chat Translation Task
Yunlong Liang, Fandong Meng, Jinan Xu +2
This paper introduces the joint submission of the Beijing Jiaotong University and WeChat AI to the WMT'22 chat translation task for English-German. Based on the Transformer, we app…
Planning Irregular Object Packing via Hierarchical Reinforcement Learning
Sichao Huang, Ziwei Wang, Jie Zhou +1
Object packing by autonomous robots is an im-portant challenge in warehouses and logistics industry. Most conventional data-driven packing planning approaches focus on regular cubo…
Probabilistic Deep Metric Learning for Hyperspectral Image Classification
Chengkun Wang, Wenzhao Zheng, Xian Sun +2
This paper proposes a probabilistic deep metric learning (PDML) framework for hyperspectral image classification, which aims to predict the category of each pixel for an image capt…
Empathetic Dialogue Generation via Sensitive Emotion Recognition and Sensible Knowledge Selection
Lanrui Wang, Jiangnan Li, Zheng Lin +4
Empathy, which is widely used in psychological counselling, is a key trait of everyday human conversations. Equipped with commonsense knowledge, current approaches to empathetic re…
CSCD-NS: a Chinese Spelling Check Dataset for Native Speakers
Yong Hu, Fandong Meng, Jie Zhou
In this paper, we present CSCD-NS, the first Chinese spelling check (CSC) dataset designed for native speakers, containing 40,000 samples from a Chinese social platform. Compared w…
Question-Interlocutor Scope Realized Graph Modeling over Key Utterances for Dialogue Reading Comprehension
Jiangnan Li, Mo Yu, Fandong Meng +4
In this work, we focus on dialogue reading comprehension (DRC), a task extracting answer spans for questions from dialogues. Dialogue context modeling in DRC is tricky due to compl…
Towards Robust k-Nearest-Neighbor Machine Translation
Hui Jiang, Ziyao Lu, Fandong Meng +4
k-Nearest-Neighbor Machine Translation (kNN-MT) becomes an important research direction of NMT in recent years. Its main idea is to retrieve useful key-value pairs from an addition…
Categorizing Semantic Representations for Neural Machine Translation
Yongjing Yin, Yafu Li, Fandong Meng +2
Modern neural machine translation (NMT) models have achieved competitive performance in standard benchmarks. However, they have recently been shown to suffer limitation in composit…
A Win-win Deal: Towards Sparse and Robust Pre-trained Language Models
Yuanxin Liu, Fandong Meng, Zheng Lin +5
Despite the remarkable success of pre-trained language models (PLMs), they still face two challenges: First, large-scale PLMs are inefficient in terms of memory footprint and compu…
Language Prior Is Not the Only Shortcut: A Benchmark for Shortcut Learning in VQA
Qingyi Si, Fandong Meng, Mingyu Zheng +6
Visual Question Answering (VQA) models are prone to learn the shortcut solution formed by dataset biases rather than the intended solution. To evaluate the VQA models' reasoning ab…
Towards Robust Visual Question Answering: Making the Most of Biased Samples via Contrastive Learning
Qingyi Si, Yuanxin Liu, Fandong Meng +5
Models for Visual Question Answering (VQA) often rely on the spurious correlations, i.e., the language priors, that appear in the biased samples of training set, which make them br…
Cross-Align: Modeling Deep Cross-lingual Interactions for Word Alignment
Siyu Lai, Zhen Yang, Fandong Meng +3
Word alignment which aims to extract lexicon translation equivalents between source and target sentences, serves as a fundamental tool for natural language processing. Recent studi…
Dynamics-aware Adversarial Attack of Adaptive Neural Networks
An Tao, Yueqi Duan, Yingqi Wang +2
In this paper, we investigate the dynamics-aware adversarial attack problem of adaptive neural networks. Most existing adversarial attack algorithms are designed under a basic assu…
Rethink about the Word-level Quality Estimation for Machine Translation from Human Judgement
Zhen Yang, Fandong Meng, Yuanmeng Yan +1
Word-level Quality Estimation (QE) of Machine Translation (MT) aims to find out potential translation errors in the translated sentence without reference. Typically, conventional w…