Francis Ferraro | DeepAI

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∙ 05/24/2023

InteractiveIE: Towards Assessing the Strength of Human-AI Collaboration in Improving the Performance of Information Extraction

Learning template based information extraction from documents is a cruci...

0 Ishani Mondal, et al. ∙

∙ 12/05/2022

POQue: Asking Participant-specific Outcome Questions for a Deeper Understanding of Complex Events

Knowledge about outcomes is critical for complex event understanding but...

0 Sai Vallurupalli, et al. ∙

∙ 10/16/2022

A General Framework for Auditing Differentially Private Machine Learning

We present a framework to statistically audit the privacy guarantee conf...

0 Fred Lu, et al. ∙

∙ 07/31/2022

PASTA: A Dataset for Modeling Participant States in Narratives

The events in a narrative can be understood as a coherent whole via the ...

0 Sayontan Ghosh, et al. ∙

∙ 06/09/2022

Neural Bregman Divergences for Distance Learning

Many metric learning tasks, such as triplet learning, nearest neighbor r...

0 Fred Lu, et al. ∙

∙ 05/24/2022

RevUp: Revise and Update Information Bottleneck for Event Representation

In machine learning, latent variables play a key role to capture the und...

0 Mehdi Rezaee, et al. ∙

∙ 02/14/2022

Continuously Generalized Ordinal Regression for Linear and Deep Models

Ordinal regression is a classification task where classes have an order ...

0 Fred Lu, et al. ∙

∙ 12/27/2021

Bridging the Gap: Using Deep Acoustic Representations to Learn Grounded Language from Percepts and Raw Speech

Learning to understand grounded language, which connects natural languag...

0 Gaoussou Youssouf Kebe, et al. ∙

∙ 10/14/2021

Transferring Semantic Knowledge Into Language Encoders

We introduce semantic form mid-tuning, an approach for transferring sema...

0 Mohammad Umair, et al. ∙

∙ 09/15/2021

Discriminative and Generative Transformer-based Models For Situation Entity Classification

We re-examine the situation entity (SE) classification task with varying...

13 Mehdi Rezaee, et al. ∙

∙ 07/20/2021

Neural Variational Learning for Grounded Language Acquisition

We propose a learning system in which language is grounded in visual per...

0 Nisha Pillai, et al. ∙

∙ 06/30/2021

Learning a Reversible Embedding Mapping using Bi-Directional Manifold Alignment

We propose a Bi-Directional Manifold Alignment (BDMA) that learns a non-...

0 Ashwinkumar Ganesan, et al. ∙

∙ 11/16/2020

Sampling Approach Matters: Active Learning for Robotic Language Acquisition

Ordering the selection of training data using active learning can lead t...

0 Nisha Pillai, et al. ∙

∙ 10/22/2020

A Discrete Variational Recurrent Topic Model without the Reparametrization Trick

We show how to learn a neural topic model with discrete random variables...

0 Mehdi Rezaee, et al. ∙

∙ 10/12/2020

On the Complementary Nature of Knowledge Graph Embedding, Fine Grain Entity Types, and Language Modeling

We demonstrate the complementary natures of neural knowledge graph embed...

5 Rajat Patel, et al. ∙

∙ 10/09/2020

Event Representation with Sequential, Semi-Supervised Discrete Variables

Within the context of event modeling and understanding, we propose a new...

0 Mohammad Mehdi Rezaee Taghiabadi, et al. ∙

∙ 09/30/2019

The Universal Decompositional Semantics Dataset and Decomp Toolkit

We present the Universal Decompositional Semantics (UDS) dataset (v1.0),...

0 Aaron Steven White, et al. ∙

∙ 02/08/2019

Knowledge Graph Fact Prediction via Knowledge-Enriched Tensor Factorization

We present a family of novel methods for embedding knowledge graphs into...

16 Ankur Padia, et al. ∙

∙ 10/31/2018

SURFACE: Semantically Rich Fact Validation with Explanations

Judging the veracity of a sentence making one or more claims is an impor...

0 Ankur Padia, et al. ∙

∙ 06/29/2017

Frame-Based Continuous Lexical Semantics through Exponential Family Tensor Factorization and Semantic Proto-Roles

We study how different frame annotations complement one another when lea...

0 Francis Ferraro, et al. ∙

∙ 04/13/2016

Visual Storytelling

We introduce the first dataset for sequential vision-to-language, and ex...

0 Ting-Hao, et al. ∙

∙ 06/23/2015

A Survey of Current Datasets for Vision and Language Research

Integrating vision and language has long been a dream in work on artific...

0 Francis Ferraro, et al. ∙

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