246 citations · 1.2k across the 71 of their papers we have counts for
73 papers
DenseCLIP: Language-Guided Dense Prediction with Context-Aware Prompting
Yongming Rao, Wenliang Zhao, Guangyi Chen +5
Recent progress has shown that large-scale pre-training using contrastive image-text pairs can be a promising alternative for high-quality visual representation learning from natur…
RAP: Robustness-Aware Perturbations for Defending against Backdoor Attacks on NLP Models
Wenkai Yang, Yankai Lin, Peng Li +2
Backdoor attacks, which maliciously control a well-trained model's outputs of the instances with specific triggers, are recently shown to be serious threats to the safety of reusin…
Improving Graph-based Sentence Ordering with Iteratively Predicted Pairwise Orderings
Shaopeng Lai, Ante Wang, Fandong Meng +6
Dominant sentence ordering models can be classified into pairwise ordering models and set-to-sequence models. However, there is little attempt to combine these two types of models,…
Topology-Imbalance Learning for Semi-Supervised Node Classification
Deli Chen, Yankai Lin, Guangxiang Zhao +4
The class imbalance problem, as an important issue in learning node representations, has drawn increasing attention from the community. Although the imbalance considered by existin…
NerfingMVS: Guided Optimization of Neural Radiance Fields for Indoor Multi-view Stereo
Yi Wei, Shaohui Liu, Yongming Rao +3
In this work, we present a new multi-view depth estimation method that utilizes both conventional reconstruction and learning-based priors over the recently proposed neural radianc…
Deep Asymmetric Hashing with Dual Semantic Regression and Class Structure Quantization
Jianglin Lu, Hailing Wang, Jie Zhou +2
Recently, deep hashing methods have been widely used in image retrieval task. Most existing deep hashing approaches adopt one-to-one quantization to reduce information loss. Howeve…
WeTS: A Benchmark for Translation Suggestion
Zhen Yang, Fandong Meng, Yingxue Zhang +2
Translation Suggestion (TS), which provides alternatives for specific words or phrases given the entire documents translated by machine translation (MT) \cite{lee2021intellicat}, h…
Simulated annealing for optimization of graphs and sequences
Xianggen Liu, Pengyong Li, Fandong Meng +5
Optimization of discrete structures aims at generating a new structure with the better property given an existing one, which is a fundamental problem in machine learning. Different…
Structure-Preserving Image Super-Resolution
Cheng Ma, Yongming Rao, Jiwen Lu +1
Structures matter in single image super-resolution (SISR). Benefiting from generative adversarial networks (GANs), recent studies have promoted the development of SISR by recoverin…
Dynamic Knowledge Distillation for Pre-trained Language Models
Lei Li, Yankai Lin, Shuhuai Ren +3
Knowledge distillation~(KD) has been proved effective for compressing large-scale pre-trained language models. However, existing methods conduct KD statically, e.g., the student mo…
Constructing Emotion Consensus and Utilizing Unpaired Data for Empathetic Dialogue Generation
Lei Shen, Jinchao Zhang, Jiao Ou +2
Researches on dialogue empathy aim to endow an agent with the capacity of accurate understanding and proper responding for emotions. Existing models for empathetic dialogue generat…
Multimodal Incremental Transformer with Visual Grounding for Visual Dialogue Generation
Feilong Chen, Fandong Meng, Xiuyi Chen +2
Visual dialogue is a challenging task since it needs to answer a series of coherent questions on the basis of understanding the visual environment. Previous studies focus on the im…
Challenging Instances are Worth Learning: Generating Valuable Negative Samples for Response Selection Training
Yao Qiu, Jinchao Zhang, Huiying Ren +1
Retrieval-based chatbot selects the appropriate response from candidates according to the context, which heavily depends on a response selection module. A response selection module…
Improving Gradient-based Adversarial Training for Text Classification by Contrastive Learning and Auto-Encoder
Yao Qiu, Jinchao Zhang, Jie Zhou
Recent work has proposed several efficient approaches for generating gradient-based adversarial perturbations on embeddings and proved that the model's performance and robustness c…
Different Strokes for Different Folks: Investigating Appropriate Further Pre-training Approaches for Diverse Dialogue Tasks
Yao Qiu, Jinchao Zhang, Jie Zhou
Loading models pre-trained on the large-scale corpus in the general domain and fine-tuning them on specific downstream tasks is gradually becoming a paradigm in Natural Language Pr…
Competence-based Curriculum Learning for Multilingual Machine Translation
Mingliang Zhang, Fandong Meng, Yunhai Tong +1
Currently, multilingual machine translation is receiving more and more attention since it brings better performance for low resource languages (LRLs) and saves more space. However,…
Enhancing Visual Dialog Questioner with Entity-based Strategy Learning and Augmented Guesser
Duo Zheng, Zipeng Xu, Fandong Meng +3
Considering the importance of building a good Visual Dialog (VD) Questioner, many researchers study the topic under a Q-Bot-A-Bot image-guessing game setting, where the Questioner…
Towards Expressive Communication with Internet Memes: A New Multimodal Conversation Dataset and Benchmark
Zhengcong Fei, Zekang Li, Jinchao Zhang +2
As a kind of new expression elements, Internet memes are popular and extensively used in online chatting scenarios since they manage to make dialogues vivid, moving, and interestin…
Towards Making the Most of Dialogue Characteristics for Neural Chat Translation
Yunlong Liang, Chulun Zhou, Fandong Meng +4
Neural Chat Translation (NCT) aims to translate conversational text between speakers of different languages. Despite the promising performance of sentence-level and context-aware n…
GoG: Relation-aware Graph-over-Graph Network for Visual Dialog
Feilong Chen, Xiuyi Chen, Fandong Meng +2
Visual dialog, which aims to hold a meaningful conversation with humans about a given image, is a challenging task that requires models to reason the complex dependencies among vis…
Structure-Enhanced Pop Music Generation via Harmony-Aware Learning
Xueyao Zhang, Jinchao Zhang, Yao Qiu +2
Pop music generation has always been an attractive topic for both musicians and scientists for a long time. However, automatically composing pop music with a satisfactory structure…
Text AutoAugment: Learning Compositional Augmentation Policy for Text Classification
Shuhuai Ren, Jinchao Zhang, Lei Li +2
Data augmentation aims to enrich training samples for alleviating the overfitting issue in low-resource or class-imbalanced situations. Traditional methods first devise task-specif…
Scheduled Sampling Based on Decoding Steps for Neural Machine Translation
Yijin Liu, Fandong Meng, Yufeng Chen +2
Scheduled sampling is widely used to mitigate the exposure bias problem for neural machine translation. Its core motivation is to simulate the inference scene during training by re…
Deep Relational Metric Learning
Wenzhao Zheng, Borui Zhang, Jiwen Lu +1
This paper presents a deep relational metric learning (DRML) framework for image clustering and retrieval. Most existing deep metric learning methods learn an embedding space with…