Conversational recommendation systems (CRS) aim to interactively acquire...
The dominant text generation models compose the output by sequentially
s...
Generalization beyond in-domain experience to out-of-distribution data i...
Recent studies have exhibited remarkable capabilities of pre-trained
mul...
Annotating long-document question answering (long-document QA) pairs is
...
Currently, human-bot symbiosis dialog systems, e.g., pre- and after-sale...
Open-ended text generation with autoregressive language models (LMs) is ...
Aspect Sentiment Triplet Extraction (ASTE) has become an emerging task i...
Conventional event detection models under supervised learning settings s...
Recently, topic-grounded dialogue system has attracted significant atten...
Long document question answering is a challenging task due to its demand...
Recently, to improve the unsupervised image retrieval performance, plent...
Sequential recommendation (SR) aims to predict the subsequent behaviors ...
Unsupervised question answering is an attractive task due to its indepen...
Incorporating Knowledge Graphs (KG) into recommeder system has attracted...
Existing online recruitment platforms depend on automatic ways of conduc...
Extracting relational triples from unstructured text is an essential tas...
Knowledge graph (KG) plays an increasingly important role in recommender...
Aspect-based sentiment analysis (ABSA) is a fine-grained sentiment analy...
It is the most important way for researchers to acquire academic progres...
Joint entity and relation extraction is an essential task in natural lan...
Recent research on dialogue response selection has been mainly focused o...
The success of pretrained cross-lingual language models relies on two
es...
Knowledge graph entity typing aims to infer entities' missing types in
k...
The cross-lingual language models are typically pretrained with masked
l...
Session-based recommendation (SBR) is a challenging task, which aims at
...
Chinese Spell Checking (CSC) aims to detect and correct erroneous charac...
Dialogue state tracking (DST) plays a key role in task-oriented dialogue...
Recently, it has attracted much attention to build reliable named entity...
Since the pre-trained language models are widely used, retrieval-based
o...
We study the coarse-grained selection module in retrieval-based chatbot....
Session-based recommendation (SBR) is a challenging task, which aims to
...
Session-based recommendation (SBR) is a challenging task, which aims at
...
Due to the huge commercial interests behind online reviews, a
tremendous...
Due to their high retrieval efficiency and low storage cost for cross-mo...
Node classification in structural networks has been proven to be useful ...
Currently, open-domain generative dialog systems have attracted consider...
In this work, we formulate cross-lingual language model pre-training as
...
Recently, open-domain dialogue systems have attracted growing attention....
As a key component in a dialogue system, dialogue state tracking plays a...
Open-domain generative dialogue systems have attracted considerable atte...
In end-to-end dialogue modeling and agent learning, it is important to (...
Multilingual pretrained language models (such as multilingual BERT) have...
We introduce a new scientific named entity recognizer called SEPT, which...
In this work we focus on transferring supervision signals of natural lan...
Second language acquisition (SLA) modeling is to predict whether second
...
Learning an efficient manager of dialogue agent from data with little ma...
The task of table structure recognition aims to recognize the internal
s...
Network embedding is a promising way of network representation, facilita...
Network embedding is a promising way of network representation, facilita...