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08/15/2023
A Tight Competitive Ratio for Online Submodular Welfare Maximization
In this paper we consider the online Submodular Welfare (SW) problem. In...
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08/07/2023
An Improved Approximation Algorithm for the Max-3-Section Problem
We consider the Max-3-Section problem, where we are given an undirected ...
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07/06/2023
Read, Look or Listen? What's Needed for Solving a Multimodal Dataset
The prevalence of large-scale multimodal datasets presents unique challe...
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06/29/2023
Surveying (Dis)Parities and Concerns of Compute Hungry NLP Research
Many recent improvements in NLP stem from the development and use of lar...
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06/09/2023
Morphosyntactic probing of multilingual BERT models
We introduce an extensive dataset for multilingual probing of morphologi...
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06/04/2023
Finding the SWEET Spot: Analysis and Improvement of Adaptive Inference in Low Resource Settings
Adaptive inference is a simple method for reducing inference costs. The ...
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05/30/2023
Fighting Bias with Bias: Promoting Model Robustness by Amplifying Dataset Biases
NLP models often rely on superficial cues known as dataset biases to ach...
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05/22/2023
Textually Pretrained Speech Language Models
Speech language models (SpeechLMs) process and generate acoustic data on...
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03/13/2023
Breaking Common Sense: WHOOPS! A Vision-and-Language Benchmark of Synthetic and Compositional Images
Weird, unusual, and uncanny images pique the curiosity of observers beca...
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12/08/2022
VASR: Visual Analogies of Situation Recognition
A core process in human cognition is analogical mapping: the ability to ...
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11/07/2022
How Much Does Attention Actually Attend? Questioning the Importance of Attention in Pretrained Transformers
The attention mechanism is considered the backbone of the widely-used Tr...
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08/31/2022
Efficient Methods for Natural Language Processing: A Survey
Getting the most out of limited resources allows advances in natural lan...
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07/25/2022
WinoGAViL: Gamified Association Benchmark to Challenge Vision-and-Language Models
While vision-and-language models perform well on tasks such as visual qu...
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06/20/2022
Fewer Errors, but More Stereotypes? The Effect of Model Size on Gender Bias
The size of pretrained models is increasing, and so is their performance...
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06/10/2022
Measuring the Carbon Intensity of AI in Cloud Instances
By providing unprecedented access to computational resources, cloud comp...
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04/27/2022
On the Limitations of Dataset Balancing: The Lost Battle Against Spurious Correlations
Recent work has shown that deep learning models in NLP are highly sensit...
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04/13/2022
TangoBERT: Reducing Inference Cost by using Cascaded Architecture
The remarkable success of large transformer-based models such as BERT, R...
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04/05/2022
A deep learning framework for the detection and quantification of drusen and reticular pseudodrusen on optical coherence tomography
Purpose - To develop and validate a deep learning (DL) framework for the...
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03/15/2022
Data Contamination: From Memorization to Exploitation
Pretrained language models are typically trained on massive web-based da...
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10/06/2021
ABC: Attention with Bounded-memory Control
Transformer architectures have achieved state-of-the-art results on a va...
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10/01/2021
Expected Validation Performance and Estimation of a Random Variable's Maximum
Research in NLP is often supported by experimental results, and improved...
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09/05/2021
Data Efficient Masked Language Modeling for Vision and Language
Masked language modeling (MLM) is one of the key sub-tasks in vision-lan...
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06/10/2021
Graph Balancing with Orientation Costs
Motivated by the classic Generalized Assignment Problem, we consider the...
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05/03/2021
Fault Tolerant Max-Cut
In this work, we initiate the study of fault tolerant Max Cut, where giv...
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04/23/2021
The Metric Relaxation for 0-Extension Admits an Ω(log^2/3k) Gap
We consider the 0-Extension problem, where we are given an undirected gr...
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04/22/2021
Provable Limitations of Acquiring Meaning from Ungrounded Form: What will Future Language Models Understand?
Language models trained on billions of tokens have recently led to unpre...
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03/17/2021
Automatic Generation of Contrast Sets from Scene Graphs: Probing the Compositional Consistency of GQA
Recent works have shown that supervised models often exploit data artifa...
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03/03/2021
Random Feature Attention
Transformers are state-of-the-art models for a variety of sequence model...
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02/25/2021
A Refined Analysis of Submodular Greedy
Many algorithms for maximizing a monotone submodular function subject to...
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10/19/2020
Parameter Norm Growth During Training of Transformers
The capacity of neural networks like the widely adopted transformer is k...
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10/08/2020
Extracting a Knowledge Base of Mechanisms from COVID-19 Papers
The urgency of mitigating COVID-19 has spawned a large and diverse body ...
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05/13/2020
A Mixture of h-1 Heads is Better than h Heads
Multi-head attentive neural architectures have achieved state-of-the-art...
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04/18/2020
A Formal Hierarchy of RNN Architectures
We develop a formal hierarchy of the expressive capacity of RNN architec...
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04/16/2020
The Right Tool for the Job: Matching Model and Instance Complexities
As NLP models become larger, executing a trained model requires signific...
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02/15/2020
Fine-Tuning Pretrained Language Models: Weight Initializations, Data Orders, and Early Stopping
Fine-tuning pretrained contextual word embedding models to supervised do...
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09/09/2019
Knowledge Enhanced Contextual Word Representations
Contextual word representations, typically trained on unstructured, unla...
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09/06/2019
RNN Architecture Learning with Sparse Regularization
Neural models for NLP typically use large numbers of parameters to reach...
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09/06/2019
Show Your Work: Improved Reporting of Experimental Results
Research in natural language processing proceeds, in part, by demonstrat...
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09/04/2019
PaLM: A Hybrid Parser and Language Model
We present PaLM, a hybrid parser and neural language model. Building on ...
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07/22/2019
Green AI
The computations required for deep learning research have been doubling ...
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06/28/2019
Min-Max Correlation Clustering via MultiCut
Correlation clustering is a fundamental combinatorial optimization probl...
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05/07/2019
Online and Offline Greedy Algorithms for Routing with Switching Costs
Motivated by the use of high speed circuit switches in large scale data ...
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04/04/2019
Inoculation by Fine-Tuning: A Method for Analyzing Challenge Datasets
Several datasets have recently been constructed to expose brittleness in...
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12/19/2018
Sticky Brownian Rounding and its Applications to Constraint Satisfaction Problems
Semidefinite programming is a powerful tool in the design and analysis o...
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08/28/2018
Rational Recurrences
Despite the tremendous empirical success of neural models in natural lan...
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08/16/2018
SWAG: A Large-Scale Adversarial Dataset for Grounded Commonsense Inference
Given a partial description like "she opened the hood of the car," human...
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05/29/2018
LSTMs Exploit Linguistic Attributes of Data
While recurrent neural networks have found success in a variety of natur...
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05/15/2018
SoPa: Bridging CNNs, RNNs, and Weighted Finite-State Machines
Recurrent and convolutional neural networks comprise two distinct famili...
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04/29/2018
A Tight Approximation for Submodular Maximization with Mixed Packing and Covering Constraints
Motivated by applications in machine learning, such as subset selection ...
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04/25/2018