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Found 21 papers, 4 papers with code
Contrapositive Local Class Inference
Certain types of classification problems may be performed at multiple levels of granularity; for example, we might want to know the sentiment polarity of a document or a sentence, or a phrase.
Quantifying the Evaluation of Heuristic Methods for Textual Data Augmentation
Data augmentation has been shown to be effective in providing more training data for machine learning and resulting in more robust classifiers.
Tribe or Not? Critical Inspection of Group Differences Using TribalGram
With the rise of AI and data mining techniques, group profiling and group-level analysis have been increasingly used in many domains including policy making and direct marketing.
ArgRewrite V.2: an Annotated Argumentative Revisions Corpus
The variety of revision unit scope and purpose granularity levels in ArgRewrite, along with the inclusion of new types of meta-data, can make it a useful resource for research and applications that involve revision analysis.
BasisNet: Two-stage Model Synthesis for Efficient Inference
With early termination, the average cost can be further reduced to 198M MAdds while maintaining accuracy of 80. 0% on ImageNet.
Ranked #633 on
Image Classification
on ImageNet
Domain-robust VQA with diverse datasets and methods but no target labels
The observation that computer vision methods overfit to dataset specifics has inspired diverse attempts to make object recognition models robust to domain shifts.
Detecting Persuasive Atypicality by Modeling Contextual Compatibility
We propose a new approach to detect atypicality in persuasive imagery.
Inflating Topic Relevance with Ideology: A Case Study of Political Ideology Bias in Social Topic Detection Models
We investigate the impact of political ideology biases in training data.
Heuristically Informed Unsupervised Idiom Usage Recognition
This information then serves as a form of distant supervision to guide the unsupervised training process for the probabilistic models.
Equal But Not The Same: Understanding the Implicit Relationship Between Persuasive Images and Text
Images and text in advertisements interact in complex, non-literal ways.
An Interactive Tool for Natural Language Processing on Clinical Text
Natural Language Processing (NLP) systems often make use of machine learning techniques that are unfamiliar to end-users who are interested in analyzing clinical records.
A Corpus of Annotated Revisions for Studying Argumentative Writing
This paper presents ArgRewrite, a corpus of between-draft revisions of argumentative essays.
A Comparison of MT Errors and ESL Errors
We describe a method for the automatic classification of MT errors according to English as a Second Language (ESL) error categories and conduct a large comparison experiment that includes both high-performing and low-performing translate-to-English MT systems for several source languages.
