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08/29/2023
WeatherBench 2: A benchmark for the next generation of data-driven global weather models
WeatherBench 2 is an update to the global, medium-range (1-14 day) weath...
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06/24/2023
SEEDS: Emulation of Weather Forecast Ensembles with Diffusion Models
Probabilistic forecasting is crucial to decision-making under uncertaint...
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06/15/2023
Encyclopedic VQA: Visual questions about detailed properties of fine-grained categories
We propose Encyclopedic-VQA, a large scale visual question answering (VQ...
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06/13/2023
User-defined Event Sampling and Uncertainty Quantification in Diffusion Models for Physical Dynamical Systems
Diffusion models are a class of probabilistic generative models that hav...
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05/24/2023
Debias Coarsely, Sample Conditionally: Statistical Downscaling through Optimal Transport and Probabilistic Diffusion Models
We introduce a two-stage probabilistic framework for statistical downsca...
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05/11/2023
V2Meow: Meowing to the Visual Beat via Music Generation
Generating high quality music that complements the visual content of a v...
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02/12/2023
Policy-Induced Self-Supervision Improves Representation Finetuning in Visual RL
We study how to transfer representations pretrained on source tasks to t...
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01/25/2023
Pre-computed memory or on-the-fly encoding? A hybrid approach to retrieval augmentation makes the most of your compute
Retrieval-augmented language models such as Fusion-in-Decoder are powerf...
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01/25/2023
Evolve Smoothly, Fit Consistently: Learning Smooth Latent Dynamics For Advection-Dominated Systems
We present a data-driven, space-time continuous framework to learn surro...
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12/15/2022
FiDO: Fusion-in-Decoder optimized for stronger performance and faster inference
Fusion-in-Decoder (FiD) is a powerful retrieval-augmented language model...
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09/29/2022
Generate-and-Retrieve: use your predictions to improve retrieval for semantic parsing
A common recent approach to semantic parsing augments sequence-to-sequen...
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05/27/2022
ALMA: Hierarchical Learning for Composite Multi-Agent Tasks
Despite significant progress on multi-agent reinforcement learning (MARL...
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05/24/2022
Evaluating the Impact of Model Scale for Compositional Generalization in Semantic Parsing
Despite their strong performance on many tasks, pre-trained language mod...
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03/23/2022
Possibility Before Utility: Learning And Using Hierarchical Affordances
Reinforcement learning algorithms struggle on tasks with complex hierarc...
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02/16/2022
Policy Learning and Evaluation with Randomized Quasi-Monte Carlo
Reinforcement learning constantly deals with hard integrals, for example...
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12/14/2021
Improving Compositional Generalization with Latent Structure and Data Augmentation
Generic unstructured neural networks have been shown to struggle on out-...
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12/14/2021
Co-training Transformer with Videos and Images Improves Action Recognition
In learning action recognition, models are typically pre-trained on obje...
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11/09/2021
Learning to Generalize Compositionally by Transferring Across Semantic Parsing Tasks
Neural network models often generalize poorly to mismatched domains or d...
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10/28/2021
HyperPINN: Learning parameterized differential equations with physics-informed hypernetworks
Many types of physics-informed neural network models have been proposed ...
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10/12/2021
Mention Memory: incorporating textual knowledge into Transformers through entity mention attention
Natural language understanding tasks such as open-domain question answer...
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09/29/2021
Visually Grounded Concept Composition
We investigate ways to compose complex concepts in texts from primitive ...
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09/25/2021
Systematic Generalization on gSCAN: What is Nearly Solved and What is Next?
We analyze the grounded SCAN (gSCAN) benchmark, which was recently propo...
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05/10/2021
ReadTwice: Reading Very Large Documents with Memories
Knowledge-intensive tasks such as question answering often require assim...
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04/15/2021
Embedding Adaptation is Still Needed for Few-Shot Learning
Constructing new and more challenging tasksets is a fruitful methodology...
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02/26/2021
DOCENT: Learning Self-Supervised Entity Representations from Large Document Collections
This paper explores learning rich self-supervised entity representations...
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11/18/2020
A Hierarchical Multi-Modal Encoder for Moment Localization in Video Corpus
Identifying a short segment in a long video that semantically matches a ...
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10/23/2020
AQuaMuSe: Automatically Generating Datasets for Query-Based Multi-Document Summarization
Summarization is the task of compressing source document(s) into coheren...
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10/06/2020
Learning to Represent Image and Text with Denotation Graph
Learning to fuse vision and language information and representing them i...
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07/18/2020
Drinking from a Firehose: Continual Learning with Web-scale Natural Language
Continual learning systems will interact with humans, with each other, a...
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06/13/2020
Uncertainty Estimation with Infinitesimal Jackknife, Its Distribution and Mean-Field Approximation
Uncertainty quantification is an important research area in machine lear...
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06/07/2020
AI-QMIX: Attention and Imagination for Dynamic Multi-Agent Reinforcement Learning
Real world multi-agent tasks often involve varying types and quantities ...
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05/10/2020
BabyWalk: Going Farther in Vision-and-Language Navigation by Taking Baby Steps
Learning to follow instructions is of fundamental importance to autonomo...
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01/13/2020
Visual Storytelling via Predicting Anchor Word Embeddings in the Stories
We propose a learning model for the task of visual storytelling. The mai...
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10/30/2019
Decoupling Adaptation from Modeling with Meta-Optimizers for Meta Learning
Meta-learning methods, most notably Model-Agnostic Meta-Learning or MAML...
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08/19/2019
Topic Augmented Generator for Abstractive Summarization
Steady progress has been made in abstractive summarization with attentio...
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06/17/2019
Neural Theorem Provers Do Not Learn Rules Without Exploration
Neural symbolic processing aims to combine the generalization of logical...
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06/07/2019
Learning Classifier Synthesis for Generalized Few-Shot Learning
Visual recognition in real-world requires handling long-tailed and even ...
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06/06/2019
Amortized Inference of Variational Bounds for Learning Noisy-OR
Classical approaches for approximate inference depend on cleverly design...
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05/28/2019
Coordinated Exploration via Intrinsic Rewards for Multi-Agent Reinforcement Learning
Sparse rewards are one of the most important challenges in reinforcement...
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04/05/2019
Synthesized Policies for Transfer and Adaptation across Tasks and Environments
The ability to transfer in reinforcement learning is key towards buildin...
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02/01/2019
Hyper-parameter Tuning under a Budget Constraint
We study a budgeted hyper-parameter tuning problem, where we optimize th...
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12/16/2018
Classifier and Exemplar Synthesis for Zero-Shot Learning
Zero-shot learning (ZSL) enables solving a task without the need to see ...
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12/10/2018
Learning Embedding Adaptation for Few-Shot Learning
Learning with limited data is a key challenge for visual recognition. Fe...
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10/16/2018
Cross-Modal and Hierarchical Modeling of Video and Text
Visual data and text data are composed of information at multiple granul...
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10/05/2018
Actor-Attention-Critic for Multi-Agent Reinforcement Learning
Reinforcement learning in multi-agent scenarios is important for real-wo...
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08/21/2018
Aiming to Know You Better Perhaps Makes Me a More Engaging Dialogue Partner
There have been several attempts to define a plausible motivation for a ...
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08/13/2018
Multi-Task Learning for Sequence Tagging: An Empirical Study
We study three general multi-task learning (MTL) approaches on 11 sequen...
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06/10/2018
Cross-Dataset Adaptation for Visual Question Answering
We investigate the problem of cross-dataset adaptation for visual questi...
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06/10/2018
Learning Answer Embeddings for Visual Question Answering
We propose a novel probabilistic model for visual question answering (Vi...
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04/24/2017
