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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...
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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...
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09/28/2022
Improving alignment of dialogue agents via targeted human judgements
We present Sparrow, an information-seeking dialogue agent trained to be ...
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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...
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03/29/2022
Training Compute-Optimal Large Language Models
We investigate the optimal model size and number of tokens for training ...
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12/08/2021
Ethical and social risks of harm from Language Models
This paper aims to help structure the risk landscape associated with lar...
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09/15/2021
Challenges in Detoxifying Language Models
Large language models (LM) generate remarkably fluent text and can be ef...
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06/16/2021
Probing Image-Language Transformers for Verb Understanding
Multimodal image-language transformers have achieved impressive results ...
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01/31/2021
Decoupling the Role of Data, Attention, and Losses in Multimodal Transformers
Recently multimodal transformer models have gained popularity because th...
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04/14/2020
Contrastive Examples for Addressing the Tyranny of the Majority
Computer vision algorithms, e.g. for face recognition, favour groups of ...
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09/06/2018
Object Hallucination in Image Captioning
Despite continuously improving performance, contemporary image captionin...
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09/05/2018
Localizing Moments in Video with Temporal Language
Localizing moments in a longer video via natural language queries is a n...
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07/25/2018
Grounding Visual Explanations
Existing visual explanation generating agents learn to fluently justify ...
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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...
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06/26/2018
Generating Counterfactual Explanations with Natural Language
Natural language explanations of deep neural network decisions provide a...
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03/26/2018
Women also Snowboard: Overcoming Bias in Captioning Models
Most machine learning methods are known to capture and exploit biases of...
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02/15/2018
Multimodal Explanations: Justifying Decisions and Pointing to the Evidence
Deep models that are both effective and explainable are desirable in man...
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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 ...
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11/17/2017
Grounding Visual Explanations (Extended Abstract)
Existing models which generate textual explanations enforce task relevan...
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08/04/2017
Localizing Moments in Video with Natural Language
We consider retrieving a specific temporal segment, or moment, from a vi...
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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...
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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...
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06/24/2016
Captioning Images with Diverse Objects
Recent captioning models are limited in their ability to scale and descr...
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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...
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03/28/2016
Generating Visual Explanations
Clearly explaining a rationale for a classification decision to an end-u...
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11/17/2015
Deep Compositional Captioning: Describing Novel Object Categories without Paired Training Data
While recent deep neural network models have achieved promising results ...
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12/22/2014
Learning Compact Convolutional Neural Networks with Nested Dropout
Recently, nested dropout was proposed as a method for ordering represent...
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11/17/2014
