research
∙
09/20/2023
Localize, Retrieve and Fuse: A Generalized Framework for Free-Form Question Answering over Tables
Question answering on tabular data (a.k.a TableQA), which aims at genera...
share
research
∙
09/20/2023
Named Entity Recognition via Machine Reading Comprehension: A Multi-Task Learning Approach
Named Entity Recognition (NER) aims to extract and classify entity menti...
research
∙
01/02/2023
Rethinking the Video Sampling and Reasoning Strategies for Temporal Sentence Grounding
Temporal sentence grounding (TSG) aims to identify the temporal boundary...
research
∙
08/24/2022
Diverse Title Generation for Stack Overflow Posts with Multiple Sampling Enhanced Transformer
Stack Overflow is one of the most popular programming communities where ...
research
∙
06/15/2022
Collaborative Knowledge Graph Fusion by Exploiting the Open Corpus
To alleviate the challenges of building Knowledge Graphs (KG) from scrat...
research
∙
05/04/2022
CODE-MVP: Learning to Represent Source Code from Multiple Views with Contrastive Pre-Training
Recent years have witnessed increasing interest in code representation l...
research
∙
03/08/2022
Reinforced MOOCs Concept Recommendation in Heterogeneous Information Networks
Massive open online courses (MOOCs), which provide a large-scale interac...
research
∙
03/01/2022
Attend, Memorize and Generate: Towards Faithful Table-to-Text Generation in Few Shots
Few-shot table-to-text generation is a task of composing fluent and fait...
research
∙
02/14/2022
What Do They Capture? – A Structural Analysis of Pre-Trained Language Models for Source Code
Recently, many pre-trained language models for source code have been pro...
research
∙
01/19/2022
Cross-Language Binary-Source Code Matching with Intermediate Representations
Binary-source code matching plays an important role in many security and...
research
∙
12/06/2021
DANets: Deep Abstract Networks for Tabular Data Classification and Regression
Tabular data are ubiquitous in real world applications. Although many co...
research
∙
11/29/2021
FedHM: Efficient Federated Learning for Heterogeneous Models via Low-rank Factorization
The underlying assumption of recent federated learning (FL) paradigms is...
research
∙
10/12/2021
HETFORMER: Heterogeneous Transformer with Sparse Attention for Long-Text Extractive Summarization
To capture the semantic graph structure from raw text, most existing sum...
research
∙
08/10/2021
SynCoBERT: Syntax-Guided Multi-Modal Contrastive Pre-Training for Code Representation
Code representation learning, which aims to encode the semantics of sour...
research
∙
06/08/2021
Are Pretrained Transformers Robust in Intent Classification? A Missing Ingredient in Evaluation of Out-of-Scope Intent Detection
Pretrained Transformer-based models were reported to be robust in intent...
research
∙
01/22/2021
Enriching Non-Autoregressive Transformer with Syntactic and SemanticStructures for Neural Machine Translation
The non-autoregressive models have boosted the efficiency of neural mach...
research
∙
12/06/2020
NaturalCC: A Toolkit to Naturalize the Source Code Corpus
We present NaturalCC, an efficient and extensible toolkit to bridge the ...
research
∙
10/25/2020
Discriminative Nearest Neighbor Few-Shot Intent Detection by Transferring Natural Language Inference
Intent detection is one of the core components of goal-oriented dialog s...
research
∙
10/13/2020
Cross-Supervised Joint-Event-Extraction with Heterogeneous Information Networks
Joint-event-extraction, which extracts structural information (i.e., ent...
research
∙
09/26/2020
KG-BART: Knowledge Graph-Augmented BART for Generative Commonsense Reasoning
Generative commonsense reasoning which aims to empower machines to gener...
research
∙
10/08/2019
Find or Classify? Dual Strategy for Slot-Value Predictions on Multi-Domain Dialog State Tracking
Dialog State Tracking (DST) is a core component in task-oriented dialog ...
research
∙
09/30/2019
Multi-Modal Attention Network Learning for Semantic Source Code Retrieval
Code retrieval techniques and tools have been playing a key role in faci...
research
∙
08/13/2019
Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking
Counterfactual thinking describes a psychological phenomenon that people...
research
∙
04/03/2019
Multi-Modal Generative Adversarial Network for Short Product Title Generation in Mobile E-Commerce
Nowadays, more and more customers browse and purchase products in favor ...
research
∙
11/17/2018
Improving Automatic Source Code Summarization via Deep Reinforcement Learning
Code summarization provides a high level natural language description of...
research
∙
11/12/2018
Improved Dynamic Memory Network for Dialogue Act Classification with Adversarial Training
Dialogue Act (DA) classification is a challenging problem in dialogue in...
research
∙
11/11/2018