64 citations · 92 across the 7 of their papers we have counts for
9 papers
When to Use What: An In-Depth Comparative Empirical Analysis of OpenIE Systems for Downstream Applications
Kevin Pei, Ishan Jindal, Kevin Chen-Chuan Chang +2
Open Information Extraction (OpenIE) has been used in the pipelines of various NLP tasks. Unfortunately, there is no clear consensus on which models to use in which tasks. Muddying…
PriMeSRL-Eval: A Practical Quality Metric for Semantic Role Labeling Systems Evaluation
Ishan Jindal, Alexandre Rademaker, Khoi-Nguyen Tran +4
Semantic role labeling (SRL) identifies the predicate-argument structure in a sentence. This task is usually accomplished in four steps: predicate identification, predicate sense d…
Improved Semantic Role Labeling using Parameterized Neighborhood Memory Adaptation
Ishan Jindal, Ranit Aharonov, Siddhartha Brahma +2
Deep neural models achieve some of the best results for semantic role labeling. Inspired by instance-based learning that utilizes nearest neighbors to handle low-frequency context-…
CLAR: A Cross-Lingual Argument Regularizer for Semantic Role Labeling
Ishan Jindal, Yunyao Li, Siddhartha Brahma +1
Semantic role labeling (SRL) identifies predicate-argument structure(s) in a given sentence. Although different languages have different argument annotations, polyglot training, th…
An Effective Label Noise Model for DNN Text Classification
Ishan Jindal, Daniel Pressel, Brian Lester +1
Because large, human-annotated datasets suffer from labeling errors, it is crucial to be able to train deep neural networks in the presence of label noise. While training image cla…
Optimizing Taxi Carpool Policies via Reinforcement Learning and Spatio-Temporal Mining
Ishan Jindal, Zhiwei Qin, Xuewen Chen +2
In this paper, we develop a reinforcement learning (RL) based system to learn an effective policy for carpooling that maximizes transportation efficiency so that fewer cars are req…