Logo embedding plays a crucial role in various e-commerce applications b...
Recently, several multi-modal models have been developed for joint image...
Few-shot Named Entity Recognition (NER) aims to identify named entities ...
Prompt-based fine-tuning has boosted the performance of Pre-trained Lang...
Extractive Question Answering (EQA) is one of the most important tasks i...
The success of Pre-Trained Models (PTMs) has reshaped the development of...
Knowledge graph (KG) plays an increasingly important role in recommender...
Pre-trained Language Models (PLMs) have achieved remarkable performance ...
Knowledge-Enhanced Pre-trained Language Models (KEPLMs) are pre-trained
...
On many natural language processing tasks, large pre-trained language mo...
Recently, the performance of Pre-trained Language Models (PLMs) has been...
Meta-learning has emerged as a trending technique to tackle few-shot tex...
Session-based recommendation (SBR) is a challenging task, which aims at
...
We present a new vision-language (VL) pre-training model dubbed Kaleido-...
Despite pre-trained language models such as BERT have achieved appealing...
Pre-trained language models have been applied to various NLP tasks with
...
Intelligent personal assistant systems for information-seeking conversat...
Session-based recommendation (SBR) is a challenging task, which aims at
...
The literature has witnessed the success of applying deep Transfer Learn...
Structured information extraction from document images usually consists ...
Transfer learning is widely used for transferring knowledge from a sourc...
Machine Reading Comprehension (MRC) aims to extract answers to questions...
Conversational search is one of the ultimate goals of information retrie...
In this paper, we address the text and image matching in cross-modal
ret...
ROUGE is the de facto criterion for summarization research. However, its...
Pre-trained neural language models bring significant improvement for var...
Lexical relations describe how concepts are semantically related, in the...
Personal assistant systems, such as Apple Siri, Google Assistant, Amazon...
Large pre-trained language models such as BERT have shown their effectiv...
Conversational question answering (ConvQA) is a simplified but concrete
...
Conversational search is an emerging topic in the information retrieval
...
Intelligent personal assistant systems, with either text-based or voice-...
In the NeurIPS 2018 Artificial Intelligence for Prosthetics challenge,
p...
Conversational assistants are being progressively adopted by the general...
Deep text matching approaches have been widely studied for many applicat...
Product reviews, in the form of texts dominantly, significantly help
con...
Building multi-turn information-seeking conversation systems is an impor...
Incidental scene text detection, especially for multi-oriented text regi...
Intelligent personal assistant systems with either text-based or voice-b...
Understanding and characterizing how people interact in information-seek...
We present AliMe Assist, an intelligent assistant designed for creating ...
In this paper, we study transfer learning for the PI and NLI problems, a...
We present PS-DBSCAN, a communication efficient parallel DBSCAN algorith...