Search Results for author:
Found 14 papers, 8 papers with code
Length Control in Abstractive Summarization by Pretraining Information Selection
In this paper, we propose a length-aware attention mechanism (LAAM) to adapt the encoding of the source based on the desired length.
Reference-free Summarization Evaluation via Semantic Correlation and Compression Ratio
In this paper, we propose a new automatic reference-free evaluation metric that compares semantic distribution between source document and summary by pretrained language models and considers summary compression ratio.
ChatMatch: Evaluating Chatbots by Autonomous Chat Tournaments
Existing automatic evaluation systems of chatbots mostly rely on static chat scripts as ground truth, which is hard to obtain, and requires access to the models of the bots as a form of “white-box testing”.
Specializing Pre-trained Language Models for Better Relational Reasoning via Network Pruning
Pretrained masked language models (PLMs) were shown to be inheriting a considerable amount of relational knowledge from the source corpora.
Does My Dog ''Speak'' Like Me? The Acoustic Correlation between Pet Dogs and Their Human Owners
How hosts language influence their pets' vocalization is an interesting yet underexplored problem.
Towards Lexical Analysis of Dog Vocalizations via Online Videos
This study presents a data-driven investigation into the semantics of dog vocalizations via correlating different sound types with consistent semantics.
Knowledge Base Question Answering via Encoding of Complex Query Graphs
Answering complex questions that involve multiple entities and multiple relations using a standard knowledge base is an open and challenging task.
ExtRA: Extracting Prominent Review Aspects from Customer Feedback
Many existing systems for analyzing and summarizing customer reviews about products or service are based on a number of prominent review aspects.
Controlling Length in Abstractive Summarization Using a Convolutional Neural Network
Convolutional neural networks (CNNs) have met great success in abstractive summarization, but they cannot effectively generate summaries of desired lengths.
Adaptive Multi-Task Transfer Learning for Chinese Word Segmentation in Medical Text
Chinese word segmentation (CWS) trained from open source corpus faces dramatic performance drop when dealing with domain text, especially for a domain with lots of special terms and diverse writing styles, such as the biomedical domain.
Mining Cross-Cultural Differences and Similarities in Social Media
Cross-cultural differences and similarities are common in cross-lingual natural language understanding, especially for research in social media.
Multi-channel BiLSTM-CRF Model for Emerging Named Entity Recognition in Social Media
In this paper, we present our multi-channel neural architecture for recognizing emerging named entity in social media messages, which we applied in the Novel and Emerging Named Entity Recognition shared task at the EMNLP 2017 Workshop on Noisy User-generated Text (W-NUT).
Towards Non-projective High-Order Dependency Parser
This paper presents a novel high-order dependency parsing framework that targets non-projective treebanks.
