11 papers
PathFinder: Discovering Decision Pathways in Deep Neural Networks
Ozan İrsoy, Ethem Alpaydın
Explainability is becoming an increasingly important topic for deep neural networks. Though the operation in convolutional layers is easier to understand, processing becomes opaque…
Disentangling Online Chats with DAG-Structured LSTMs
Duccio Pappadopulo, Lisa Bauer, Marco Farina +2
Many modern messaging systems allow fast and synchronous textual communication among many users. The resulting sequence of messages hides a more complicated structure in which inde…
Diversity-Aware Batch Active Learning for Dependency Parsing
Tianze Shi, Adrian Benton, Igor Malioutov +1
While the predictive performance of modern statistical dependency parsers relies heavily on the availability of expensive expert-annotated treebank data, not all annotations contri…
Learning Syntax from Naturally-Occurring Bracketings
Tianze Shi, Ozan İrsoy, Igor Malioutov +1
Naturally-occurring bracketings, such as answer fragments to natural language questions and hyperlinks on webpages, can reflect human syntactic intuition regarding phrasal boundari…
Corrected CBOW Performs as well as Skip-gram
Ozan İrsoy, Adrian Benton, Karl Stratos
Mikolov et al. (2013a) observed that continuous bag-of-words (CBOW) word embeddings tend to underperform Skip-gram (SG) embeddings, and this finding has been reported in subsequent…
Semantic Role Labeling as Syntactic Dependency Parsing
Tianze Shi, Igor Malioutov, Ozan İrsoy
We reduce the task of (span-based) PropBank-style semantic role labeling (SRL) to syntactic dependency parsing. Our approach is motivated by our empirical analysis that shows three…