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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 ...
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11/15/2022
On the Compositional Generalization Gap of In-Context Learning
Pretrained large generative language models have shown great performance...
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11/07/2022
Multi-Head Adapter Routing for Data-Efficient Fine-Tuning
Parameter-efficient fine-tuning (PEFT) methods can adapt large language ...
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06/02/2022
Expressiveness and Learnability: A Unifying View for Evaluating Self-Supervised Learning
We propose a unifying view to analyze the representation quality of self...
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03/24/2022
Evaluating Distributional Distortion in Neural Language Modeling
A fundamental characteristic of natural language is the high rate at whi...
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03/21/2022
Better Language Model with Hypernym Class Prediction
Class-based language models (LMs) have been long devised to address cont...
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02/28/2022
Combining Modular Skills in Multitask Learning
A modular design encourages neural models to disentangle and recombine d...
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12/16/2021
Does Pre-training Induce Systematic Inference? How Masked Language Models Acquire Commonsense Knowledge
Transformer models pre-trained with a masked-language-modeling objective...
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09/17/2021
Self-training with Few-shot Rationalization: Teacher Explanations Aid Student in Few-shot NLU
While pre-trained language models have obtained state-of-the-art perform...
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09/13/2021
The Emergence of the Shape Bias Results from Communicative Efficiency
By the age of two, children tend to assume that new word categories are ...
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06/25/2021
Decomposed Mutual Information Estimation for Contrastive Representation Learning
Recent contrastive representation learning methods rely on estimating mu...
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05/07/2021
Understanding by Understanding Not: Modeling Negation in Language Models
Negation is a core construction in natural language. Despite being very ...
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04/18/2021
Linguistic dependencies and statistical dependence
What is the relationship between linguistic dependencies and statistical...
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10/09/2020
Recursive Top-Down Production for Sentence Generation with Latent Trees
We model the recursive production property of context-free grammars for ...
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05/02/2020
Exploring and Predicting Transferability across NLP Tasks
Recent advances in NLP demonstrate the effectiveness of training large-s...
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03/03/2020
Hybrid Generative-Retrieval Transformers for Dialogue Domain Adaptation
Domain adaptation has recently become a key problem in dialogue systems ...
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12/20/2019
Report on the First HIPstIR Workshop on the Future of Information Retrieval
The vision of HIPstIR is that early stage information retrieval (IR) res...
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11/10/2019
Robust Natural Language Inference Models with Example Forgetting
We investigate whether example forgetting, a recently introduced measure...
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10/29/2019
Ordered Memory
Stack-augmented recurrent neural networks (RNNs) have been of interest t...
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07/23/2019
Metalearned Neural Memory
We augment recurrent neural networks with an external memory mechanism t...
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12/12/2018
An Empirical Study of Example Forgetting during Deep Neural Network Learning
Inspired by the phenomenon of catastrophic forgetting, we investigate th...
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10/22/2018
Ordered Neurons: Integrating Tree Structures into Recurrent Neural Networks
Recurrent neural network (RNN) models are widely used for processing seq...
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07/11/2018
VFunc: a Deep Generative Model for Functions
We introduce a deep generative model for functions. Our model provides a...
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06/29/2018
Counting to Explore and Generalize in Text-based Games
We propose a recurrent RL agent with an episodic exploration mechanism t...
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06/12/2018
Focused Hierarchical RNNs for Conditional Sequence Processing
Recurrent Neural Networks (RNNs) with attention mechanisms have obtained...
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06/11/2018
Straight to the Tree: Constituency Parsing with Neural Syntactic Distance
In this work, we propose a novel constituency parsing scheme. The model ...
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02/27/2018
Augmented CycleGAN: Learning Many-to-Many Mappings from Unpaired Data
Learning inter-domain mappings from unpaired data can improve performanc...
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11/15/2017
Z-Forcing: Training Stochastic Recurrent Networks
Many efforts have been devoted to training generative latent variable mo...
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08/22/2017
Twin Networks: Using the Future as a Regularizer
Being able to model long-term dependencies in sequential data, such as t...
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05/04/2017
Machine Comprehension by Text-to-Text Neural Question Generation
We propose a recurrent neural model that generates natural-language ques...
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11/29/2016
NewsQA: A Machine Comprehension Dataset
We present NewsQA, a challenging machine comprehension dataset of over 1...
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06/07/2016
Iterative Alternating Neural Attention for Machine Reading
We propose a novel neural attention architecture to tackle machine compr...
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05/19/2016
A Hierarchical Latent Variable Encoder-Decoder Model for Generating Dialogues
Sequential data often possesses a hierarchical structure with complex de...
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07/17/2015
Building End-To-End Dialogue Systems Using Generative Hierarchical Neural Network Models
We investigate the task of building open domain, conversational dialogue...
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07/08/2015
A Hierarchical Recurrent Encoder-Decoder For Generative Context-Aware Query Suggestion
Users may strive to formulate an adequate textual query for their inform...
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06/23/2015
deltaBLEU: A Discriminative Metric for Generation Tasks with Intrinsically Diverse Targets
We introduce Discriminative BLEU (deltaBLEU), a novel metric for intrins...
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06/22/2015