Vivek Srikumar

research

∙ 06/30/2023

The Integer Linear Programming Inference Cookbook

Over the years, integer linear programs have been employed to model infe...

0 Vivek Srikumar, et al. ∙

research

∙ 05/25/2023

Don't Retrain, Just Rewrite: Countering Adversarial Perturbations by Rewriting Text

Can language models transform inputs to protect text classifiers against...

0 Ashim Gupta, et al. ∙

research

∙ 05/24/2023

Learning Semantic Role Labeling from Compatible Label Sequences

This paper addresses the question of how to efficiently learn from disjo...

0 Tao Li, et al. ∙

research

∙ 04/17/2023

An In-depth Investigation of User Response Simulation for Conversational Search

Conversational search has seen increased recent attention in both the IR...

0 Zhenduo Wang, et al. ∙

research

∙ 12/02/2022

AGRO: Adversarial Discovery of Error-prone groups for Robust Optimization

Models trained via empirical risk minimization (ERM) are known to rely o...

0 Bhargavi Paranjape, et al. ∙

research

∙ 09/02/2022

Elaboration-Generating Commonsense Question Answering at Scale

In question answering requiring common sense, language models (e.g., GPT...

0 Wenya Wang, et al. ∙

research

∙ 09/23/2021

Putting Words in BERT's Mouth: Navigating Contextualized Vector Spaces with Pseudowords

We present a method for exploring regions around individual points in a ...

0 Taelin Karidi, et al. ∙

research

∙ 07/28/2021

Evaluating Relaxations of Logic for Neural Networks: A Comprehensive Study

Symbolic knowledge can provide crucial inductive bias for training neura...

12 Mattia Medina Grespan, et al. ∙

research

∙ 06/27/2021

A Closer Look at How Fine-tuning Changes BERT

Given the prevalence of pre-trained contextualized representations in to...

0 Yichu Zhou, et al. ∙

research

∙ 06/17/2021

X-FACT: A New Benchmark Dataset for Multilingual Fact Checking

In this work, we introduce X-FACT: the largest publicly available multil...

11 Ashim Gupta, et al. ∙

research

∙ 05/26/2021

Database Workload Characterization with Query Plan Encoders

Smart databases are adopting artificial intelligence (AI) technologies t...

6 Debjyoti Paul, et al. ∙

research

∙ 04/13/2021

DirectProbe: Studying Representations without Classifiers

Understanding how linguistic structures are encoded in contextualized em...

0 Yichu Zhou, et al. ∙

research

∙ 04/06/2021

VERB: Visualizing and Interpreting Bias Mitigation Techniques for Word Representations

Word vector embeddings have been shown to contain and amplify biases in ...

4 Archit Rathore, et al. ∙

research

∙ 01/10/2021

BERT Family Eat Word Salad: Experiments with Text Understanding

In this paper, we study the response of large models from the BERT famil...

6 Ashim Gupta, et al. ∙

research

∙ 12/02/2020

Supertagging the Long Tail with Tree-Structured Decoding of Complex Categories

Although current CCG supertaggers achieve high accuracy on the standard ...

0 Jakob Prange, et al. ∙

research

∙ 10/06/2020

UNQOVERing Stereotyping Biases via Underspecified Questions

While language embeddings have been shown to have stereotyping biases, h...

0 Tao Li, et al. ∙

research

∙ 09/02/2020

A Simple Global Neural Discourse Parser

Discourse parsing is largely dominated by greedy parsers with manually-d...

0 Yichu Zhou, et al. ∙

research

∙ 06/30/2020

OSCaR: Orthogonal Subspace Correction and Rectification of Biases in Word Embeddings

Language representations are known to carry stereotypical biases and, as...

0 Sunipa Dev, et al. ∙

research

∙ 05/23/2020

Learning Constraints for Structured Prediction Using Rectifier Networks

Various natural language processing tasks are structured prediction prob...

0 Xingyuan Pan, et al. ∙

research

∙ 05/13/2020

INFOTABS: Inference on Tables as Semi-structured Data

In this paper, we observe that semi-structured tabulated text is ubiquit...

5 Vivek Gupta, et al. ∙

research

∙ 05/01/2020

Structured Tuning for Semantic Role Labeling

Recent neural network-driven semantic role labeling (SRL) systems have s...

0 Tao Li, et al. ∙

research

∙ 10/05/2019

On the Limits of Learning to Actively Learn Semantic Representations

One of the goals of natural language understanding is to develop models ...

0 Omri Koshorek, et al. ∙

research

∙ 08/31/2019

A Logic-Driven Framework for Consistency of Neural Models

While neural models show remarkable accuracy on individual predictions, ...

0 Tao Li, et al. ∙

research

∙ 08/25/2019

On Measuring and Mitigating Biased Inferences of Word Embeddings

Word embeddings carry stereotypical connotations from the text they are ...

0 Sunipa Dev, et al. ∙

research

∙ 06/30/2019

Observing Dialogue in Therapy: Categorizing and Forecasting Behavioral Codes

Automatically analyzing dialogue can help understand and guide behavior ...

0 Jie Cao, et al. ∙

research

∙ 06/14/2019

Augmenting Neural Networks with First-order Logic

Today, the dominant paradigm for training neural networks involves minim...

0 Tao Li, et al. ∙

research

∙ 05/27/2019

Learning In Practice: Reasoning About Quantization

There is a mismatch between the standard theoretical analyses of statist...

0 Annie Cherkaev, et al. ∙

research

∙ 06/11/2018

Learning to Speed Up Structured Output Prediction

Predicting structured outputs can be computationally onerous due to the ...

0 Xingyuan Pan, et al. ∙

research

∙ 05/13/2018

Comprehensive Supersense Disambiguation of English Prepositions and Possessives

Semantic relations are often signaled with prepositional or possessive m...

0 Nathan Schneider, et al. ∙

research

∙ 03/10/2018

Newton: Gravitating Towards the Physical Limits of Crossbar Acceleration

Many recent works have designed accelerators for Convolutional Neural Ne...

0 Anirban Nag, et al. ∙

research

∙ 04/07/2017

Adposition Supersenses v2

This document describes an inventory of 50 semantic labels designed to c...

0 Nathan Schneider, et al. ∙

research

∙ 03/10/2017

Coping with Construals in Broad-Coverage Semantic Annotation of Adpositions

We consider the semantics of prepositions, revisiting a broad-coverage a...

0 Jena D. Hwang, et al. ∙

research

∙ 05/08/2016

A corpus of preposition supersenses in English web reviews

We present the first corpus annotated with preposition supersenses, unle...

0 Nathan Schneider, et al. ∙

research

∙ 09/23/2015

IllinoisSL: A JAVA Library for Structured Prediction

IllinoisSL is a Java library for learning structured prediction models. ...

0 Kai-Wei Chang, et al. ∙

Vivek Srikumar

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