
-
Modality-specific Distillation
Large neural networks are impractical to deploy on mobile devices due to...
read it
-
Zero-shot Learning by Generating Task-specific Adapters
Pre-trained text-to-text transformers achieve impressive performance acr...
read it
-
Studying Strategically: Learning to Mask for Closed-book QA
Closed-book question-answering (QA) is a challenging task that requires ...
read it
-
DEER: A Data Efficient Language Model for Event Temporal Reasoning
Pretrained language models (LMs) such as BERT, RoBERTa, and ELECTRA are ...
read it
-
Learning Contextualized Knowledge Structures for Commonsense Reasoning
Recently, neural-symbolic architectures have achieved success on commons...
read it
-
Learning to Deceive Knowledge Graph Augmented Models via Targeted Perturbation
Symbolic knowledge (e.g., entities, relations, and facts in a knowledge ...
read it
-
Efficiently Mitigating Classification Bias via Transfer Learning
Prediction bias in machine learning models refers to unintended model be...
read it
-
Fair Hate Speech Detection through Evaluation of Social Group Counterfactuals
Approaches for mitigating bias in supervised models are designed to redu...
read it
-
Constrained Abstractive Summarization: Preserving Factual Consistency with Constrained Generation
Summaries generated by abstractive summarization are supposed to only co...
read it
-
Will This Idea Spread Beyond Academia? Understanding Knowledge Transfer of Scientific Concepts across Text Corpora
What kind of basic research ideas are more likely to get applied in prac...
read it
-
Semi-Automated Protocol Disambiguation and Code Generation
For decades, Internet protocols have been specified using natural langua...
read it
-
Multi-document Summarization with Maximal Marginal Relevance-guided Reinforcement Learning
While neural sequence learning methods have made significant progress in...
read it
-
Two Step Joint Model for Drug Drug Interaction Extraction
When patients need to take medicine, particularly taking more than one k...
read it
-
Gradient Based Memory Editing for Task-Free Continual Learning
Prior work on continual learning often operate in a "task-aware" manner,...
read it
-
Screenplay Quality Assessment: Can We Predict Who Gets Nominated?
Deciding which scripts to turn into movies is a costly and time-consumin...
read it
-
Contextualizing Hate Speech Classifiers with Post-hoc Explanation
Hate speech classifiers trained on imbalanced datasets struggle to deter...
read it
-
Teaching Machine Comprehension with Compositional Explanations
Advances in extractive machine reading comprehension (MRC) rely heavily ...
read it
-
ForecastQA: Machine Comprehension of Temporal Text for Answering Forecasting Questions
Textual data are often accompanied by time information (e.g., dates in n...
read it
-
Visually Grounded Continual Learning of Compositional Semantics
Children's language acquisition from the visual world is a real-world ex...
read it
-
Connecting the Dots: A Knowledgeable Path Generator for Commonsense Question Answering
Commonsense question answering (QA) requires the modeling of general bac...
read it
-
Learning Collaborative Agents with Rule Guidance for Knowledge Graph Reasoning
Walk-based models have shown their unique advantages in knowledge graph ...
read it
-
Generating Natural Language Adversarial Examples on a Large Scale with Generative Models
Today text classification models have been widely used. However, these c...
read it
-
Temporal Attribute Prediction via Joint Modeling of Multi-Relational Structure Evolution
Time series prediction is an important problem in machine learning. Prev...
read it
-
Mining News Events from Comparable News Corpora: A Multi-Attribute Proximity Network Modeling Approach
We present ProxiModel, a novel event mining framework for extracting hig...
read it
-
Improving BERT Fine-tuning with Embedding Normalization
Large pre-trained sentence encoders like BERT start a new chapter in nat...
read it
-
CommonGen: A Constrained Text Generation Dataset Towards Generative Commonsense Reasoning
Rational humans can generate sentences that cover a certain set of conce...
read it
-
Towards Hierarchical Importance Attribution: Explaining Compositional Semantics for Neural Sequence Models
The impressive performance of neural networks on natural language proces...
read it
-
Learning to Annotate: Modularizing Data Augmentation for Text Classifiers with Natural Language Explanations
Deep neural networks usually require massive labeled data, which restric...
read it
-
Learning to Annotate: Modularizing Data Augmentation for TextClassifiers with Natural Language Explanations
Deep neural networks usually require massive labeled data, which restric...
read it
-
HiExpan: Task-Guided Taxonomy Construction by Hierarchical Tree Expansion
Taxonomies are of great value to many knowledge-rich applications. As th...
read it
-
SetExpan: Corpus-Based Set Expansion via Context Feature Selection and Rank Ensemble
Corpus-based set expansion (i.e., finding the "complete" set of entities...
read it
-
Learning to Contextually Aggregate Multi-Source Supervision for Sequence Labeling
Sequence labeling is a fundamental framework for various natural languag...
read it
-
Neural Rule Grounding for Low-Resource Relation Extraction
While deep neural models have gained successes on information extraction...
read it
-
KagNet: Knowledge-Aware Graph Networks for Commonsense Reasoning
Commonsense reasoning aims to empower machines with the human ability to...
read it
-
Reporting the Unreported: Event Extraction for Analyzing the Local Representation of Hate Crimes
Official reports of hate crimes in the US are under-reported relative to...
read it
-
Learning Dynamic Context Augmentation for Global Entity Linking
Despite of the recent success of collective entity linking (EL) methods,...
read it
-
Collaborative Policy Learning for Open Knowledge Graph Reasoning
In recent years, there has been a surge of interests in interpretable gr...
read it
-
Hierarchical Text Classification with Reinforced Label Assignment
While existing hierarchical text classification (HTC) methods attempt to...
read it
-
Facet-Aware Evaluation for Extractive Text Summarization
Commonly adopted metrics for extractive text summarization like ROUGE fo...
read it
-
Raw-to-End Name Entity Recognition in Social Media
Taking word sequences as the input, typical named entity recognition (NE...
read it
-
Adversarial Representation Learning on Large-Scale Bipartite Graphs
Graph representation on large-scale bipartite graphs is central for a va...
read it
-
Eliciting Knowledge from Experts:Automatic Transcript Parsing for Cognitive Task Analysis
Cognitive task analysis (CTA) is a type of analysis in applied psycholog...
read it
-
KCAT: A Knowledge-Constraint Typing Annotation Tool
Fine-grained Entity Typing is a tough task which suffers from noise samp...
read it
-
Dynamic Network Embedding via Incremental Skip-gram with Negative Sampling
Network representation learning, as an approach to learn low dimensional...
read it
-
Characterizing and Forecasting User Engagement with In-app Action Graph: A Case Study of Snapchat
While mobile social apps have become increasingly important in people's ...
read it
-
Modeling Combinatorial Evolution in Time Series Prediction
Time series modeling aims to capture the intrinsic factors underpinning ...
read it
-
Looking Beyond Label Noise: Shifted Label Distribution Matters in Distantly Supervised Relation Extraction
In recent years there is surge of interest in applying distant supervisi...
read it
-
Posterior-regularized REINFORCE for Instance Selection in Distant Supervision
This paper provides a new way to improve the efficiency of the REINFORCE...
read it
-
Improving Distantly-supervised Entity Typing with Compact Latent Space Clustering
Recently, distant supervision has gained great success on Fine-grained E...
read it
-
Recurrent Event Network for Reasoning over Temporal Knowledge Graphs
Recently, there has been a surge of interest in learning representation ...
read it