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05/22/2023
Towards Dialogue Systems with Agency in Human-AI Collaboration Tasks
Agency, the capacity to proactively shape events, is crucial to how huma...
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05/17/2023
Reprompting: Automated Chain-of-Thought Prompt Inference Through Gibbs Sampling
We introduce Reprompting, an iterative sampling algorithm that searches ...
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03/25/2023
GPT is becoming a Turing machine: Here are some ways to program it
We demonstrate that, through appropriate prompting, GPT-3 family of mode...
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10/04/2022
ThinkSum: Probabilistic reasoning over sets using large language models
Large language models (LLMs) have a substantial capacity for high-level ...
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06/17/2022
Diffusion models as plug-and-play priors
We consider the problem of inferring high-dimensional data 𝐱 in a model ...
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02/28/2022
Resolving label uncertainty with implicit posterior models
We propose a method for jointly inferring labels across a collection of ...
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10/15/2021
Boosting coherence of language models
Naturality of long-term information structure – coherence – remains a ch...
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09/10/2021
Studying word order through iterative shuffling
As neural language models approach human performance on NLP benchmark ta...
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06/17/2021
Multi-Label Learning from Single Positive Labels
Predicting all applicable labels for a given image is known as multi-lab...
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06/07/2021
Video Imprint
A new unified video analytics framework (ER3) is proposed for complex ev...
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05/19/2021
Compositional Processing Emerges in Neural Networks Solving Math Problems
A longstanding question in cognitive science concerns the learning mecha...
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01/04/2021
High-resolution land cover change from low-resolution labels: Simple baselines for the 2021 IEEE GRSS Data Fusion Contest
We present simple algorithms for land cover change detection in the 2021...
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04/24/2020
Mining self-similarity: Label super-resolution with epitomic representations
We show that simple patch-based models, such as epitomes, can have super...
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04/08/2020
The GeoLifeCLEF 2020 Dataset
Understanding the geographic distribution of species is a key concern in...
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12/12/2019
Local Context Normalization: Revisiting Local Normalization
Normalization layers have been shown to improve convergence in deep neur...
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10/22/2019
A deep active learning system for species identification and counting in camera trap images
Biodiversity conservation depends on accurate, up-to-date information ab...
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10/15/2019
Enhancing the Transformer with Explicit Relational Encoding for Math Problem Solving
We incorporate Tensor-Product Representations within the Transformer in ...
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06/10/2019
Human-Machine Collaboration for Fast Land Cover Mapping
We propose incorporating human labelers in a model fine-tuning system th...
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04/09/2019
Label Super Resolution with Inter-Instance Loss
For the task of semantic segmentation, high-resolution (pixel-level) gro...
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02/08/2019
FSNet: Compression of Deep Convolutional Neural Networks by Filter Summary
We present a novel method of compression of deep Convolutional Neural Ne...
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09/09/2017
Steering Output Style and Topic in Neural Response Generation
We propose simple and flexible training and decoding methods for influen...
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09/05/2017
Discriminative Similarity for Clustering and Semi-Supervised Learning
Similarity-based clustering and semi-supervised learning methods separat...
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11/19/2015
Iterative Refinement of Approximate Posterior for Training Directed Belief Networks
Variational methods that rely on a recognition network to approximate th...
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03/12/2015
Hierarchical learning of grids of microtopics
The counting grid is a grid of microtopics, sparse word/feature distribu...
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10/23/2014
Capturing spatial interdependence in image features: the counting grid, an epitomic representation for bags of features
In recent scene recognition research images or large image regions are o...
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04/26/2013
In the sight of my wearable camera: Classifying my visual experience
We introduce and we analyze a new dataset which resembles the input to b...
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01/16/2013
Learning Graphical Models of Images, Videos and Their Spatial Transformations
Mixtures of Gaussians, factor analyzers (probabilistic PCA) and hidden M...
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07/12/2012
Probabilistic index maps for modeling natural signals
One of the major problems in modeling natural signals is that signals wi...
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02/14/2012
