37 citations · 194 across the 44 of their papers we have counts for
16 papers · 1 filter
Reasoning Chain Based Adversarial Attack for Multi-hop Question Answering
Jiayu Ding, Siyuan Wang, Qin Chen +1
Recent years have witnessed impressive advances in challenging multi-hop QA tasks. However, these QA models may fail when faced with some disturbance in the input text and their in…
Curriculum Learning for Vision-and-Language Navigation
Jiwen Zhang, Zhongyu Wei, Jianqing Fan +1
Vision-and-Language Navigation (VLN) is a task where an agent navigates in an embodied indoor environment under human instructions. Previous works ignore the distribution of sample…
Negative Sample is Negative in Its Own Way: Tailoring Negative Sentences for Image-Text Retrieval
Zhihao Fan, Zhongyu Wei, Zejun Li +2
Matching model is essential for Image-Text Retrieval framework. Existing research usually train the model with a triplet loss and explore various strategy to retrieve hard negative…
Learning Implicit Sentiment in Aspect-based Sentiment Analysis with Supervised Contrastive Pre-Training
Zhengyan Li, Yicheng Zou, Chong Zhang +2
Aspect-based sentiment analysis aims to identify the sentiment polarity of a specific aspect in product reviews. We notice that about 30% of reviews do not contain obvious opinion…
SAM: A Self-adaptive Attention Module for Context-Aware Recommendation System
Jiabin Liu, Zheng Wei, Zhengpin Li +4
Recently, textual information has been proved to play a positive role in recommendation systems. However, most of the existing methods only focus on representation learning of text…
Constructing Phrase-level Semantic Labels to Form Multi-Grained Supervision for Image-Text Retrieval
Zhihao Fan, Zhongyu Wei, Zejun Li +4
Existing research for image text retrieval mainly relies on sentence-level supervision to distinguish matched and mismatched sentences for a query image. However, semantic mismatch…
Fine-Grained Element Identification in Complaint Text of Internet Fraud
Tong Liu, Siyuan Wang, Jingchao Fu +7
Existing system dealing with online complaint provides a final decision without explanations. We propose to analyse the complaint text of internet fraud in a fine-grained manner. C…
A Partition Filter Network for Joint Entity and Relation Extraction
Zhiheng Yan, Chong Zhang, Jinlan Fu +2
In joint entity and relation extraction, existing work either sequentially encode task-specific features, leading to an imbalance in inter-task feature interaction where features e…
Contextual Fine-to-Coarse Distillation for Coarse-grained Response Selection in Open-Domain Conversations
Wei Chen, Yeyun Gong, Can Xu +9
We study the problem of coarse-grained response selection in retrieval-based dialogue systems. The problem is equally important with fine-grained response selection, but is less ex…
From LSAT: The Progress and Challenges of Complex Reasoning
Siyuan Wang, Zhongkun Liu, Wanjun Zhong +4
Complex reasoning aims to draw a correct inference based on complex rules. As a hallmark of human intelligence, it involves a degree of explicit reading comprehension, interpretati…
TCIC: Theme Concepts Learning Cross Language and Vision for Image Captioning
Zhihao Fan, Zhongyu Wei, Siyuan Wang +4
Existing research for image captioning usually represents an image using a scene graph with low-level facts (objects and relations) and fails to capture the high-level semantics. I…
Logic-Driven Context Extension and Data Augmentation for Logical Reasoning of Text
Siyuan Wang, Wanjun Zhong, Duyu Tang +5
Logical reasoning of text requires understanding critical logical information in the text and performing inference over them. Large-scale pre-trained models for logical reasoning m…
Premise-based Multimodal Reasoning: Conditional Inference on Joint Textual and Visual Clues
Qingxiu Dong, Ziwei Qin, Heming Xia +9
It is a common practice for recent works in vision language cross-modal reasoning to adopt a binary or multi-choice classification formulation taking as input a set of source image…
Who Responded to Whom: The Joint Effects of Latent Topics and Discourse in Conversation Structure
Lu Ji, Jing Li, Zhongyu Wei +2
Numerous online conversations are produced on a daily basis, resulting in a pressing need to conversation understanding. As a basis to structure a discussion, we identify the respo…
Mask Attention Networks: Rethinking and Strengthen Transformer
Zhihao Fan, Yeyun Gong, Dayiheng Liu +6
Transformer is an attention-based neural network, which consists of two sublayers, namely, Self-Attention Network (SAN) and Feed-Forward Network (FFN). Existing research explores t…
An Unsupervised Sampling Approach for Image-Sentence Matching Using Document-Level Structural Information
Zejun Li, Zhongyu Wei, Zhihao Fan +2
In this paper, we focus on the problem of unsupervised image-sentence matching. Existing research explores to utilize document-level structural information to sample positive and n…