Adam Trischler

research

∙ 06/21/2023

Deep Language Networks: Joint Prompt Training of Stacked LLMs using Variational Inference

We view large language models (LLMs) as stochastic language layers in a ...

0 Alessandro Sordoni, et al. ∙

research

∙ 03/16/2023

Investigating Failures to Generalize for Coreference Resolution Models

Coreference resolution models are often evaluated on multiple datasets. ...

0 Ian Porada, et al. ∙

research

∙ 12/15/2022

The KITMUS Test: Evaluating Knowledge Integration from Multiple Sources in Natural Language Understanding Systems

Many state-of-the-art natural language understanding (NLU) models are ba...

0 Akshatha Arodi, et al. ∙

research

∙ 05/13/2022

Deconstructing NLG Evaluation: Evaluation Practices, Assumptions, and Their Implications

There are many ways to express similar things in text, which makes evalu...

0 Kaitlyn Zhou, et al. ∙

research

∙ 04/20/2021

Modeling Event Plausibility with Consistent Conceptual Abstraction

Understanding natural language requires common sense, one aspect of whic...

0 Ian Porada, et al. ∙

research

∙ 11/09/2020

An Analysis of Dataset Overlap on Winograd-Style Tasks

The Winograd Schema Challenge (WSC) and variants inspired by it have bec...

0 Ali Emami, et al. ∙

research

∙ 10/08/2020

ALFWorld: Aligning Text and Embodied Environments for Interactive Learning

Given a simple request (e.g., Put a washed apple in the kitchen fridge),...

10 Mohit Shridhar, et al. ∙

research

∙ 09/22/2020

An Empirical Study on Neural Keyphrase Generation

Recent years have seen a flourishing of neural keyphrase generation work...

0 Rui Meng, et al. ∙

research

∙ 05/02/2020

Exploring and Predicting Transferability across NLP Tasks

Recent advances in NLP demonstrate the effectiveness of training large-s...

0 Tu Vu, et al. ∙

research

∙ 04/29/2020

Exploiting Structured Knowledge in Text via Graph-Guided Representation Learning

In this work, we aim at equipping pre-trained language models with struc...

0 Tao Shen, et al. ∙

research

∙ 04/19/2020

Role-Wise Data Augmentation for Knowledge Distillation

Knowledge Distillation (KD) is a common method for transferring the “kno...

4 Jie Fu, et al. ∙

research

∙ 02/21/2020

Learning Dynamic Knowledge Graphs to Generalize on Text-Based Games

Playing text-based games requires skill in processing natural language a...

0 Ashutosh Adhikari, et al. ∙

research

∙ 10/21/2019

Building Dynamic Knowledge Graphs from Text-based Games

We are interested in learning how to update Knowledge Graphs (KG) from t...

0 Mikuláš Zelinka, et al. ∙

research

∙ 09/09/2019

Does Order Matter? An Empirical Study on Generating Multiple Keyphrases as a Sequence

Recently, concatenating multiple keyphrases as a target sequence has bee...

0 Rui Meng, et al. ∙

research

∙ 08/28/2019

Interactive Language Learning by Question Answering

Humans observe and interact with the world to acquire knowledge. However...

0 Xingdi Yuan, et al. ∙

research

∙ 08/27/2019

Interactive Machine Comprehension with Information Seeking Agents

Existing machine reading comprehension (MRC) models do not scale effecti...

5 Xingdi Yuan, et al. ∙

research

∙ 07/23/2019

Metalearned Neural Memory

We augment recurrent neural networks with an external memory mechanism t...

10 Tsendsuren Munkhdalai, et al. ∙

research

∙ 06/21/2019

A Study of State Aliasing in Structured Prediction with RNNs

End-to-end reinforcement learning agents learn a state representation an...

5 Layla El Asri, et al. ∙

research

∙ 12/12/2018

An Empirical Study of Example Forgetting during Deep Neural Network Learning

Inspired by the phenomenon of catastrophic forgetting, we investigate th...

14 Mariya Toneva, et al. ∙

research

∙ 11/05/2018

On the Evaluation of Common-Sense Reasoning in Natural Language Understanding

The NLP and ML communities have long been interested in developing model...

10 Paul Trichelair, et al. ∙

research

∙ 11/02/2018

The Hard-CoRe Coreference Corpus: Removing Gender and Number Cues for Difficult Pronominal Anaphora Resolution

We introduce a new benchmark task for coreference resolution, Hard-CoRe,...

0 Ali Emami, et al. ∙

research

∙ 10/12/2018

Building Dynamic Knowledge Graphs from Text using Machine Reading Comprehension

We propose a neural machine-reading model that constructs dynamic knowle...

0 Rajarshi Das, et al. ∙

research

∙ 10/11/2018

Generating Diverse Numbers of Diverse Keyphrases

Existing keyphrase generation studies suffer from the problems of genera...

0 Xingdi Yuan, et al. ∙

research

∙ 10/02/2018

A Knowledge Hunting Framework for Common Sense Reasoning

We introduce an automatic system that achieves state-of-the-art results ...

0 Ali Emami, et al. ∙

research

∙ 08/20/2018

Learning deep representations by mutual information estimation and maximization

Many popular representation-learning algorithms use training objectives ...

0 R Devon Hjelm, et al. ∙

research

∙ 07/12/2018

Metalearning with Hebbian Fast Weights

We unify recent neural approaches to one-shot learning with older ideas ...

4 Tsendsuren Munkhdalai, et al. ∙

research

∙ 06/29/2018

TextWorld: A Learning Environment for Text-based Games

We introduce TextWorld, a sandbox learning environment for the training ...

4 Marc-Alexandre Côté, et al. ∙

research

∙ 06/29/2018

Counting to Explore and Generalize in Text-based Games

We propose a recurrent RL agent with an episodic exploration mechanism t...

0 Xingdi Yuan, et al. ∙

research

∙ 06/12/2018

Focused Hierarchical RNNs for Conditional Sequence Processing

Recurrent Neural Networks (RNNs) with attention mechanisms have obtained...

0 Nan Rosemary Ke, et al. ∙

research

∙ 03/30/2018

Learning General Purpose Distributed Sentence Representations via Large Scale Multi-task Learning

A lot of the recent success in natural language processing (NLP) has bee...

0 Sandeep Subramanian, et al. ∙

research

∙ 12/28/2017

Rapid Adaptation with Conditionally Shifted Neurons

We describe a mechanism by which artificial neural networks can learn ra...

0 Tsendsuren Munkhdalai, et al. ∙

research

∙ 12/28/2017

Learning Rapid-Temporal Adaptations

A hallmark of human intelligence and cognition is its flexibility. One o...

0 Tsendsuren Munkhdalai, et al. ∙

research

∙ 11/28/2017

Plan, Attend, Generate: Planning for Sequence-to-Sequence Models

We investigate the integration of a planning mechanism into sequence-to-...

0 Francis Dutil, et al. ∙

research

∙ 11/15/2017

Variational Bi-LSTMs

Recurrent neural networks like long short-term memory (LSTM) are importa...

0 Samira Shabanian, et al. ∙

research

∙ 10/19/2017

FigureQA: An Annotated Figure Dataset for Visual Reasoning

We introduce FigureQA, a visual reasoning corpus of over one million que...

0 Samira Ebrahimi Kahou, et al. ∙

research

∙ 06/14/2017

Neural Models for Key Phrase Detection and Question Generation

We propose a two-stage neural model to tackle question generation from d...

0 Sandeep Subramanian, et al. ∙

research

∙ 06/13/2017

Plan, Attend, Generate: Character-level Neural Machine Translation with Planning in the Decoder

We investigate the integration of a planning mechanism into an encoder-d...

0 Caglar Gulcehre, et al. ∙

research

∙ 06/05/2017

A Joint Model for Question Answering and Question Generation

We propose a generative machine comprehension model that learns jointly ...

0 Tong Wang, et al. ∙

research

∙ 05/04/2017

Machine Comprehension by Text-to-Text Neural Question Generation

We propose a recurrent neural model that generates natural-language ques...

0 Xingdi Yuan, et al. ∙

research

∙ 11/29/2016

NewsQA: A Machine Comprehension Dataset

We present NewsQA, a challenging machine comprehension dataset of over 1...

0 Adam Trischler, et al. ∙

research

∙ 06/07/2016

Natural Language Comprehension with the EpiReader

We present the EpiReader, a novel model for machine comprehension of tex...

0 Adam Trischler, et al. ∙

research

∙ 06/07/2016

Iterative Alternating Neural Attention for Machine Reading

We propose a novel neural attention architecture to tackle machine compr...

0 Alessandro Sordoni, et al. ∙

research

∙ 03/29/2016

A Parallel-Hierarchical Model for Machine Comprehension on Sparse Data

Understanding unstructured text is a major goal within natural language ...

0 Adam Trischler, et al. ∙

research

∙ 12/17/2015

Synthesis of recurrent neural networks for dynamical system simulation

We review several of the most widely used techniques for training recurr...

0 Adam Trischler, et al. ∙

Adam Trischler

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