Lisa Anne Hendricks | DeepAI

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∙ 05/23/2023

Weakly-Supervised Learning of Visual Relations in Multimodal Pretraining

Recent work in vision-and-language pretraining has investigated supervis...

2 Emanuele Bugliarello, et al. ∙

∙ 05/12/2023

Measuring Progress in Fine-grained Vision-and-Language Understanding

While pretraining on large-scale image-text data from the Web has facili...

2 Emanuele Bugliarello, et al. ∙

∙ 09/28/2022

Improving alignment of dialogue agents via targeted human judgements

We present Sparrow, an information-seeking dialogue agent trained to be ...

2 Amelia Glaese, et al. ∙

∙ 06/16/2022

Characteristics of Harmful Text: Towards Rigorous Benchmarking of Language Models

Large language models produce human-like text that drive a growing numbe...

0 Maribeth Rauh, et al. ∙

∙ 03/29/2022

Training Compute-Optimal Large Language Models

We investigate the optimal model size and number of tokens for training ...

6 Jordan Hoffmann, et al. ∙

∙ 12/08/2021

Ethical and social risks of harm from Language Models

This paper aims to help structure the risk landscape associated with lar...

0 Laura Weidinger, et al. ∙

∙ 09/15/2021

Challenges in Detoxifying Language Models

Large language models (LM) generate remarkably fluent text and can be ef...

7 Johannes Welbl, et al. ∙

∙ 06/16/2021

Probing Image-Language Transformers for Verb Understanding

Multimodal image-language transformers have achieved impressive results ...

0 Lisa Anne Hendricks, et al. ∙

∙ 01/31/2021

Decoupling the Role of Data, Attention, and Losses in Multimodal Transformers

Recently multimodal transformer models have gained popularity because th...

0 Lisa Anne Hendricks, et al. ∙

∙ 04/14/2020

Contrastive Examples for Addressing the Tyranny of the Majority

Computer vision algorithms, e.g. for face recognition, favour groups of ...

6 Viktoriia Sharmanska, et al. ∙

∙ 09/06/2018

Object Hallucination in Image Captioning

Despite continuously improving performance, contemporary image captionin...

0 Anna Rohrbach, et al. ∙

∙ 09/05/2018

Localizing Moments in Video with Temporal Language

Localizing moments in a longer video via natural language queries is a n...

2 Lisa Anne Hendricks, et al. ∙

∙ 07/25/2018

Grounding Visual Explanations

Existing visual explanation generating agents learn to fluently justify ...

0 Lisa Anne Hendricks, et al. ∙

∙ 07/02/2018

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

Most machine learning methods are known to capture and exploit biases of...

0 Lisa Anne Hendricks, et al. ∙

∙ 06/26/2018

Generating Counterfactual Explanations with Natural Language

Natural language explanations of deep neural network decisions provide a...

1 Lisa Anne Hendricks, et al. ∙

∙ 03/26/2018

Women also Snowboard: Overcoming Bias in Captioning Models

Most machine learning methods are known to capture and exploit biases of...

0 Kaylee Burns, et al. ∙

∙ 02/15/2018

Multimodal Explanations: Justifying Decisions and Pointing to the Evidence

Deep models that are both effective and explainable are desirable in man...

1 Dong Huk Park, et al. ∙

∙ 11/17/2017

Attentive Explanations: Justifying Decisions and Pointing to the Evidence (Extended Abstract)

Deep models are the defacto standard in visual decision problems due to ...

0 Dong Huk Park, et al. ∙

∙ 11/17/2017

Grounding Visual Explanations (Extended Abstract)

Existing models which generate textual explanations enforce task relevan...

0 Lisa Anne Hendricks, et al. ∙

∙ 08/04/2017

Localizing Moments in Video with Natural Language

We consider retrieving a specific temporal segment, or moment, from a vi...

0 Lisa Anne Hendricks, et al. ∙

∙ 03/30/2017

Speaking the Same Language: Matching Machine to Human Captions by Adversarial Training

While strong progress has been made in image captioning over the last ye...

0 Rakshith Shetty, et al. ∙

∙ 12/14/2016

Attentive Explanations: Justifying Decisions and Pointing to the Evidence

Deep models are the defacto standard in visual decision models due to th...

0 Dong Huk Park, et al. ∙

∙ 06/24/2016

Captioning Images with Diverse Objects

Recent captioning models are limited in their ability to scale and descr...

0 Subhashini Venugopalan, et al. ∙

∙ 04/06/2016

Improving LSTM-based Video Description with Linguistic Knowledge Mined from Text

This paper investigates how linguistic knowledge mined from large text c...

0 Subhashini Venugopalan, et al. ∙

∙ 03/28/2016

Generating Visual Explanations

Clearly explaining a rationale for a classification decision to an end-u...

0 Lisa Anne Hendricks, et al. ∙

∙ 11/17/2015

Deep Compositional Captioning: Describing Novel Object Categories without Paired Training Data

While recent deep neural network models have achieved promising results ...

0 Lisa Anne Hendricks, et al. ∙

∙ 12/22/2014

Learning Compact Convolutional Neural Networks with Nested Dropout

Recently, nested dropout was proposed as a method for ordering represent...

0 Chelsea Finn, et al. ∙

∙ 11/17/2014

Long-term Recurrent Convolutional Networks for Visual Recognition and Description

Models based on deep convolutional networks have dominated recent image ...

0 Jeff Donahue, et al. ∙

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