Search Results for author:
Found 26 papers, 10 papers with code
damo_nlp at MEDIQA 2021: Knowledge-based Preprocessing and Coverage-oriented Reranking for Medical Question Summarization
Medical question summarization is an important but difficult task, where the input is often complex and erroneous while annotated data is expensive to acquire.
Noisy Label Detection for Speaker Recognition
The success of deep neural networks requires both high annotation quality and massive data.
Text-Aware Dual Routing Network for Visual Question Answering
To address the above issues, we propose a Text-Aware Dual Routing Network (TDR) which simultaneously handles the VQA cases with and without understanding text information in the input images.
Knowledge-Driven Program Synthesis via Adaptive Replacement Mutation and Auto-constructed Subprogram Archives
We compare the proposed method with PushGP, as well as a method using subprograms manually extracted by a human.
Distributed Feature Selection for High-dimensional Additive Models
Distributed statistical learning is a common strategy for handling massive data where we divide the learning task into multiple local machines and aggregate the results afterward.
A Chinese Multi-type Complex Questions Answering Dataset over Wikidata
We finally analyze the performance of SOTA KBQA models on this dataset and identify the challenges facing Chinese KBQA.
Machine Learning for Electronic Design Automation: A Survey
With the down-scaling of CMOS technology, the design complexity of very large-scale integrated (VLSI) is increasing.
Learning Deep Interleaved Networks with Asymmetric Co-Attention for Image Restoration
In this paper, we present a deep interleaved network (DIN) that learns how information at different states should be combined for high-quality (HQ) images reconstruction.
Robust Layout-aware IE for Visually Rich Documents with Pre-trained Language Models
Many business documents processed in modern NLP and IR pipelines are visually rich: in addition to text, their semantics can also be captured by visual traits such as layout, format, and fonts.
Deep Interleaved Network for Image Super-Resolution With Asymmetric Co-Attention
Recently, Convolutional Neural Networks (CNN) based image super-resolution (SR) have shown significant success in the literature.
Solving Portfolio Optimization Problems Using MOEA/D and Levy Flight
Portfolio optimization is a financial task which requires the allocation of capital on a set of financial assets to achieve a better trade-off between return and risk.
Enriching Pre-trained Language Model with Entity Information for Relation Classification
In this paper, we propose a model that both leverages the pre-trained BERT language model and incorporates information from the target entities to tackle the relation classification task.
Ranked #15 on
Relation Extraction
on SemEval-2010 Task 8
Multi-Instance Learning for End-to-End Knowledge Base Question Answering
This paper proposes a novel approach based on multiple instance learning to address the problem of noisy answers by exploring consensus among answers to the same question in training end-to-end KBQA models.
Knowledge Base Question Answering
Multiple Instance Learning
Entity Linking with a Paraphrase Flavor
The task of Named Entity Linking is to link entity mentions in the document to their correct entries in a knowledge base and to cluster NIL mentions.
Jointly Embedding Relations and Mentions for Knowledge Population
This paper contributes a joint embedding model for predicting relations between a pair of entities in the scenario of relation inference.
Corpus and Method for Identifying Citations in Non-Academic Text
We attempt to identify citations in non-academic text such as patents.
Annotating Relations in Scientific Articles
Relations (ABBREVIATE, EXEMPLIFY, ORIGINATE, REL{\_}WORK, OPINION) between entities (citations, jargon, people, organizations) are annotated for PubMed scientific articles.
