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09/08/2023
Graph Neural Networks Use Graphs When They Shouldn't
Predictions over graphs play a crucial role in various domains, includin...
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07/31/2023
Predicting masked tokens in stochastic locations improves masked image modeling
Self-supervised learning is a promising paradigm in deep learning that e...
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07/24/2023
Evaluating the Ripple Effects of Knowledge Editing in Language Models
Modern language models capture a large body of factual knowledge. Howeve...
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07/06/2023
Covering Uncommon Ground: Gap-Focused Question Generation for Answer Assessment
Human communication often involves information gaps between the interloc...
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05/22/2023
LM vs LM: Detecting Factual Errors via Cross Examination
A prominent weakness of modern language models (LMs) is their tendency t...
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05/10/2023
Incorporating Structured Representations into Pretrained Vision Language Models Using Scene Graphs
Vision and Language (VL) models have demonstrated remarkable zero-shot p...
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04/28/2023
Dissecting Recall of Factual Associations in Auto-Regressive Language Models
Transformer-based language models (LMs) are known to capture factual kno...
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01/30/2023
Crawling the Internal Knowledge-Base of Language Models
Language models are trained on large volumes of text, and as a result th...
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12/20/2022
What Are You Token About? Dense Retrieval as Distributions Over the Vocabulary
Dual encoders are now the dominant architecture for dense retrieval. Yet...
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12/08/2022
PromptonomyViT: Multi-Task Prompt Learning Improves Video Transformers using Synthetic Scene Data
Action recognition models have achieved impressive results by incorporat...
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10/25/2022
Learning Low Dimensional State Spaces with Overparameterized Recurrent Neural Network
Overparameterization in deep learning typically refers to settings where...
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09/01/2022
Visual Prompting via Image Inpainting
How does one adapt a pre-trained visual model to novel downstream tasks ...
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07/06/2022
Graph Trees with Attention
When dealing with tabular data, models based on regression and decision ...
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06/15/2022
Structured Video Tokens @ Ego4D PNR Temporal Localization Challenge 2022
This technical report describes the SViT approach for the Ego4D Point of...
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06/13/2022
Bringing Image Scene Structure to Video via Frame-Clip Consistency of Object Tokens
Recent action recognition models have achieved impressive results by int...
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04/10/2022
Active Learning with Label Comparisons
Supervised learning typically relies on manual annotation of the true la...
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02/09/2022
On the Implicit Bias of Gradient Descent for Temporal Extrapolation
Common practice when using recurrent neural networks (RNNs) is to apply ...
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12/14/2021
Learning to Retrieve Passages without Supervision
Dense retrievers for open-domain question answering (ODQA) have been sho...
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10/26/2021
On the Optimization Landscape of Maximum Mean Discrepancy
Generative models have been successfully used for generating realistic s...
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10/13/2021
Object-Region Video Transformers
Evidence from cognitive psychology suggests that understanding spatio-te...
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07/04/2021
A Theoretical Analysis of Fine-tuning with Linear Teachers
Fine-tuning is a common practice in deep learning, achieving excellent g...
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06/08/2021
DETReg: Unsupervised Pretraining with Region Priors for Object Detection
Unsupervised pretraining has recently proven beneficial for computer vis...
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04/27/2021
Explaining in Style: Training a GAN to explain a classifier in StyleSpace
Image classification models can depend on multiple different semantic at...
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03/09/2021
BERTese: Learning to Speak to BERT
Large pre-trained language models have been shown to encode large amount...
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02/19/2021
On the Implicit Bias of Initialization Shape: Beyond Infinitesimal Mirror Descent
Recent work has highlighted the role of initialization scale in determin...
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01/07/2021
Towards Understanding Learning in Neural Networks with Linear Teachers
Can a neural network minimizing cross-entropy learn linearly separable d...
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01/02/2021
Few-Shot Question Answering by Pretraining Span Selection
In a number of question answering (QA) benchmarks, pretrained models hav...
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10/25/2020
Regularizing Towards Permutation Invariance in Recurrent Models
In many machine learning problems the output should not depend on the or...
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10/10/2020
Maximin Optimization for Binary Regression
We consider regression problems with binary weights. Such optimization p...
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09/30/2020
Learning Object Detection from Captions via Textual Scene Attributes
Object detection is a fundamental task in computer vision, requiring lar...
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08/11/2020
Holdout SGD: Byzantine Tolerant Federated Learning
This work presents a new distributed Byzantine tolerant federated learni...
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06/27/2020
Compositional Video Synthesis with Action Graphs
Videos of actions are complex spatio-temporal signals, containing rich c...
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03/23/2020
Learning Object Permanence from Video
Object Permanence allows people to reason about the location of non-visi...
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02/22/2020
On the Inductive Bias of a CNN for Orthogonal Patterns Distributions
Training overparameterized convolutional neural networks with gradient b...
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12/16/2019
Learning Canonical Representations for Scene Graph to Image Generation
Generating realistic images of complex visual scenes becomes very challe...
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02/26/2019
Learning Latent Scene-Graph Representations for Referring Relationships
Understanding the semantics of complex visual scenes often requires anal...
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02/25/2019
Cross-Lingual Alignment of Contextual Word Embeddings, with Applications to Zero-shot Dependency Parsing
We introduce a novel method for multilingual transfer that utilizes deep...
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12/04/2018
Classifying Collisions with Spatio-Temporal Action Graph Networks
Events defined by the interaction of objects in a scene often are of cri...
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10/06/2018
Over-parameterization Improves Generalization in the XOR Detection Problem
Empirical evidence suggests that neural networks with ReLU activations g...
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08/14/2018
Explaining Queries over Web Tables to Non-Experts
Designing a reliable natural language (NL) interface for querying tables...
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03/08/2018
Learning with Rules
Complex classifiers may exhibit "embarassing" failures in cases that wou...
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02/15/2018
Mapping Images to Scene Graphs with Permutation-Invariant Structured Prediction
Structured prediction is concerned with predicting multiple inter-depend...
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02/13/2018
Predict and Constrain: Modeling Cardinality in Deep Structured Prediction
Many machine learning problems require the prediction of multi-dimension...
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11/14/2017
Weakly-supervised Semantic Parsing with Abstract Examples
Semantic parsers translate language utterances to programs, but are ofte...
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02/26/2017
Globally Optimal Gradient Descent for a ConvNet with Gaussian Inputs
Deep learning models are often successfully trained using gradient desce...
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08/27/2016
Learning to generalize to new compositions in image understanding
Recurrent neural networks have recently been used for learning to descri...
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09/19/2014
Tight Error Bounds for Structured Prediction
Structured prediction tasks in machine learning involve the simultaneous...
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09/26/2013
Tighter Linear Program Relaxations for High Order Graphical Models
Graphical models with High Order Potentials (HOPs) have received conside...
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09/26/2013
Learning Max-Margin Tree Predictors
Structured prediction is a powerful framework for coping with joint pred...
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10/19/2012