output
20022026
most citedStealing Machine Learning Models via Prediction APIs

733 citations

Showing 2020Show all

12 papers · 1 filter

cs.CL2020★ 9 cited

I like fish, especially dolphins: Addressing Contradictions in Dialogue Modeling

Yixin Nie, Mary Williamson, Mohit Bansal +2

To quantify how well natural language understanding models can capture consistency in a general conversation, we introduce the DialoguE COntradiction DEtection task (DECODE) and a…

astro-ph.HE2020★ 35 cited

Orbital Foregrounds for Ultra-Short Duration Transients

Hank Corbett, Nicholas M. Law, Alan Vasquez Soto +7

Reflections from objects in Earth orbit can produce sub-second, star-like optical flashes similar to astrophysical transients. Reflections have historically caused false alarms for…

cs.GR2020★ 15 cited

Generating Emotive Gaits for Virtual Agents Using Affect-Based Autoregression

Uttaran Bhattacharya, Nicholas Rewkowski, Pooja Guhan +4

We present a novel autoregression network to generate virtual agents that convey various emotions through their walking styles or gaits. Given the 3D pose sequences of a gait, our…

cs.CL2020

Summary-Source Proposition-level Alignment: Task, Datasets and Supervised Baseline

Ori Ernst, Ori Shapira, Ramakanth Pasunuru +4

Aligning sentences in a reference summary with their counterparts in source documents was shown as a useful auxiliary summarization task, notably for generating training data for s…

cond-mat.soft2020★ 5 cited

Cell nucleus as a microrheological probe to study the rheology of the cytoskeleton

Moslem Moradi, Ehssan Nazockdast

Mechanical properties of the cell are important biomarkers for probing its architectural changes caused by cellular processes and/or pathologies. The development of microfluidic te…

cs.CV2020★ 2 cited

Anatomical Data Augmentation via Fluid-based Image Registration

Zhengyang Shen, Zhenlin Xu, Sahin Olut +1

We introduce a fluid-based image augmentation method for medical image analysis. In contrast to existing methods, our framework generates anatomically meaningful images via interpo…

cs.CL2020★ 3 cited

Diagnosing the Environment Bias in Vision-and-Language Navigation

Yubo Zhang, Hao Tan, Mohit Bansal

Vision-and-Language Navigation (VLN) requires an agent to follow natural-language instructions, explore the given environments, and reach the desired target locations. These step-b…

cs.CL2020★ 3 cited

Multi-Source Domain Adaptation for Text Classification via DistanceNet-Bandits

Han Guo, Ramakanth Pasunuru, Mohit Bansal

Domain adaptation performance of a learning algorithm on a target domain is a function of its source domain error and a divergence measure between the data distribution of these tw…

eess.IV2020★ 4 cited

Automatic Data Augmentation via Deep Reinforcement Learning for Effective Kidney Tumor Segmentation

Tiexin Qin, Ziyuan Wang, Kelei He +3

Conventional data augmentation realized by performing simple pre-processing operations (\eg, rotation, crop, \etc) has been validated for its advantage in enhancing the performance…

cs.CL2020★ 2 cited

ManyModalQA: Modality Disambiguation and QA over Diverse Inputs

Darryl Hannan, Akshay Jain, Mohit Bansal

We present a new multimodal question answering challenge, ManyModalQA, in which an agent must answer a question by considering three distinct modalities: text, images, and tables.…

cs.CL2020★ 5 cited

Modality-Balanced Models for Visual Dialogue

Hyounghun Kim, Hao Tan, Mohit Bansal

The Visual Dialog task requires a model to exploit both image and conversational context information to generate the next response to the dialogue. However, via manual analysis, we…

cs.CL2020

AvgOut: A Simple Output-Probability Measure to Eliminate Dull Responses

Tong Niu, Mohit Bansal

Many sequence-to-sequence dialogue models tend to generate safe, uninformative responses. There have been various useful efforts on trying to eliminate them. However, these approac…