Adhiguna Kuncoro | DeepAI

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Featured Co-authors

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∙ 06/05/2023

On "Scientific Debt" in NLP: A Case for More Rigour in Language Model Pre-Training Research

This evidence-based position paper critiques current research practices ...

0 Made Nindyatama Nityasya, et al. ∙

∙ 12/19/2022

A Natural Bias for Language Generation Models

After just a few hundred training updates, a standard probabilistic mode...

0 Clara Meister, et al. ∙

∙ 03/01/2022

Transformer Grammars: Augmenting Transformer Language Models with Syntactic Inductive Biases at Scale

Transformer language models that are trained on vast amounts of data hav...

0 Laurent Sartran, et al. ∙

∙ 04/16/2021

IndoNLG: Benchmark and Resources for Evaluating Indonesian Natural Language Generation

A benchmark provides an ecosystem to measure the advancement of models w...

6 Samuel Cahyawijaya, et al. ∙

∙ 02/03/2021

Pitfalls of Static Language Modelling

Our world is open-ended, non-stationary and constantly evolving; thus wh...

0 Angeliki Lazaridou, et al. ∙

∙ 05/27/2020

Syntactic Structure Distillation Pretraining For Bidirectional Encoders

Textual representation learners trained on large amounts of data have ac...

0 Adhiguna Kuncoro, et al. ∙

∙ 06/14/2019

Scalable Syntax-Aware Language Models Using Knowledge Distillation

Prior work has shown that, on small amounts of training data, syntactic ...

0 Adhiguna Kuncoro, et al. ∙

∙ 04/07/2019

Unsupervised Recurrent Neural Network Grammars

Recurrent neural network grammars (RNNG) are generative models of langua...

0 Yoon Kim, et al. ∙

∙ 06/11/2018

Finding Syntax in Human Encephalography with Beam Search

Recurrent neural network grammars (RNNGs) are generative models of (tree...

0 John Hale, et al. ∙

∙ 01/15/2017

DyNet: The Dynamic Neural Network Toolkit

We describe DyNet, a toolkit for implementing neural network models base...

0 Graham Neubig, et al. ∙

∙ 11/17/2016

What Do Recurrent Neural Network Grammars Learn About Syntax?

Recurrent neural network grammars (RNNG) are a recently proposed probabi...

0 Adhiguna Kuncoro, et al. ∙

∙ 04/22/2016

Dependency Parsing with LSTMs: An Empirical Evaluation

We propose a transition-based dependency parser using Recurrent Neural N...

0 Adhiguna Kuncoro, et al. ∙

∙ 02/25/2016

Recurrent Neural Network Grammars

We introduce recurrent neural network grammars, probabilistic models of ...

0 Chris Dyer, et al. ∙

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