collaborators

6 papers

cs.RO2022

Implicit Kinematic Policies: Unifying Joint and Cartesian Action Spaces in End-to-End Robot Learning

Aditya Ganapathi, Pete Florence, Jake Varley +3

Action representation is an important yet often overlooked aspect in end-to-end robot learning with deep networks. Choosing one action space over another (e.g. target joint positio…

cs.CV2018

SPLAT: Semantic Pixel-Level Adaptation Transforms for Detection

Eric Tzeng, Kaylee Burns, Kate Saenko +1

Domain adaptation of visual detectors is a critical challenge, yet existing methods have overlooked pixel appearance transformations, focusing instead on bootstrapping and/or domai…

cs.CL2018

Object Hallucination in Image Captioning

Anna Rohrbach, Lisa Anne Hendricks, Kaylee Burns +2

Despite continuously improving performance, contemporary image captioning models are prone to "hallucinating" objects that are not actually in a scene. One problem is that standard…

cs.CL2018

Evaluating Theory of Mind in Question Answering

Aida Nematzadeh, Kaylee Burns, Erin Grant +2

We propose a new dataset for evaluating question answering models with respect to their capacity to reason about beliefs. Our tasks are inspired by theory-of-mind experiments that…

cs.CV2018

Women also Snowboard: Overcoming Bias in Captioning Models (Extended Abstract)

Lisa Anne Hendricks, Kaylee Burns, Kate Saenko +2

Most machine learning methods are known to capture and exploit biases of the training data. While some biases are beneficial for learning, others are harmful. Specifically, image c…

cs.CV2018

Women also Snowboard: Overcoming Bias in Captioning Models

Kaylee Burns, Lisa Anne Hendricks, Kate Saenko +2

Most machine learning methods are known to capture and exploit biases of the training data. While some biases are beneficial for learning, others are harmful. Specifically, image c…