198 citations · 1.3k across the 62 of their papers we have counts for
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Cross-Model Comparative Loss for Enhancing Neuronal Utility in Language Understanding
Yunchang Zhu, Liang Pang, Kangxi Wu +3
Current natural language understanding (NLU) models have been continuously scaling up, both in terms of model size and input context, introducing more hidden and input neurons. Whi…
Adaptive Bridge between Training and Inference for Dialogue
Haoran Xu, Hainan Zhang, Yanyan Zou +3
Although exposure bias has been widely studied in some NLP tasks, it faces its unique challenges in dialogue response generation, the representative one-to-various generation scena…
FCM: A Fine-grained Comparison Model for Multi-turn Dialogue Reasoning
Xu Wang, Hainan Zhang, Shuai Zhao +5
Despite the success of neural dialogue systems in achieving high performance on the leader-board, they cannot meet users' requirements in practice, due to their poor reasoning skil…
Transductive Learning for Unsupervised Text Style Transfer
Fei Xiao, Liang Pang, Yanyan Lan +3
Unsupervised style transfer models are mainly based on an inductive learning approach, which represents the style as embeddings, decoder parameters, or discriminator parameters and…
Adaptive Information Seeking for Open-Domain Question Answering
Yunchang Zhu, Liang Pang, Yanyan Lan +2
Information seeking is an essential step for open-domain question answering to efficiently gather evidence from a large corpus. Recently, iterative approaches have been proven to b…
Sketch and Customize: A Counterfactual Story Generator
Changying Hao, Liang Pang, Yanyan Lan +3
Recent text generation models are easy to generate relevant and fluent text for the given text, while lack of causal reasoning ability when we change some parts of the given text.…
Probing Product Description Generation via Posterior Distillation
Haolan Zhan, Hainan Zhang, Hongshen Chen +5
In product description generation (PDG), the user-cared aspect is critical for the recommendation system, which can not only improve user's experiences but also obtain more clicks.…
Match-Ignition: Plugging PageRank into Transformer for Long-form Text Matching
Liang Pang, Yanyan Lan, Xueqi Cheng
Neural text matching models have been widely used in community question answering, information retrieval, and dialogue. However, these models designed for short texts cannot well a…
Beyond Language: Learning Commonsense from Images for Reasoning
Wanqing Cui, Yanyan Lan, Liang Pang +2
This paper proposes a novel approach to learn commonsense from images, instead of limited raw texts or costly constructed knowledge bases, for the commonsense reasoning problem in…
Query Understanding via Intent Description Generation
Ruqing Zhang, Jiafeng Guo, Yixing Fan +2
Query understanding is a fundamental problem in information retrieval (IR), which has attracted continuous attention through the past decades. Many different tasks have been propos…
Ranking Enhanced Dialogue Generation
Changying Hao, Liang Pang, Yanyan Lan +3
How to effectively utilize the dialogue history is a crucial problem in multi-turn dialogue generation. Previous works usually employ various neural network architectures (e.g., re…
Neural or Statistical: An Empirical Study on Language Models for Chinese Input Recommendation on Mobile
Hainan Zhang, Yanyan Lan, Jiafeng Guo +2
Chinese input recommendation plays an important role in alleviating human cost in typing Chinese words, especially in the scenario of mobile applications. The fundamental problem i…
ReCoSa: Detecting the Relevant Contexts with Self-Attention for Multi-turn Dialogue Generation
Hainan Zhang, Yanyan Lan, Liang Pang +2
In multi-turn dialogue generation, response is usually related with only a few contexts. Therefore, an ideal model should be able to detect these relevant contexts and produce a su…
Outline Generation: Understanding the Inherent Content Structure of Documents
Ruqing Zhang, Jiafeng Guo, Yixing Fan +2
In this paper, we introduce and tackle the Outline Generation (OG) task, which aims to unveil the inherent content structure of a multi-paragraph document by identifying its potent…
HAS-QA: Hierarchical Answer Spans Model for Open-domain Question Answering
Liang Pang, Yanyan Lan, Jiafeng Guo +3
This paper is concerned with open-domain question answering (i.e., OpenQA). Recently, some works have viewed this problem as a reading comprehension (RC) task, and directly applied…
A Tree Search Algorithm for Sequence Labeling
Yadi Lao, Jun Xu, Yanyan Lan +3
In this paper we propose a novel reinforcement learning based model for sequence tagging, referred to as MM-Tag. Inspired by the success and methodology of the AlphaGo Zero, MM-Tag…
Spherical Paragraph Model
Ruqing Zhang, Jiafeng Guo, Yanyan Lan +2
Representing texts as fixed-length vectors is central to many language processing tasks. Most traditional methods build text representations based on the simple Bag-of-Words (BoW)…
Match-SRNN: Modeling the Recursive Matching Structure with Spatial RNN
Shengxian Wan, Yanyan Lan, Jun Xu +3
Semantic matching, which aims to determine the matching degree between two texts, is a fundamental problem for many NLP applications. Recently, deep learning approach has been appl…
Semantic Regularities in Document Representations
Fei Sun, Jiafeng Guo, Yanyan Lan +2
Recent work exhibited that distributed word representations are good at capturing linguistic regularities in language. This allows vector-oriented reasoning based on simple linear…
Text Matching as Image Recognition
Liang Pang, Yanyan Lan, Jiafeng Guo +3
Matching two texts is a fundamental problem in many natural language processing tasks. An effective way is to extract meaningful matching patterns from words, phrases, and sentence…