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Found 13 papers, 1 papers with code
Automatic Unit Test Data Generation and Actor-Critic Reinforcement Learning for Code Synthesis
The advent of large pre-trained language models in the domain of Code Synthesis has shown remarkable performance on various benchmarks, treating the problem of Code Generation in a fashion similar to Natural Language Generation, trained with a Language Modelling (LM) objective.
The Regular Expression Inference Challenge
We propose \emph{regular expression inference (REI)} as a challenge for code/language modelling, and the wider machine learning community.
Graph Attention with Hierarchies for Multi-hop Question Answering
Multi-hop QA (Question Answering) is the task of finding the answer to a question across multiple documents.
Relational Graph Convolutional Neural Networks for Multihop Reasoning: A Comparative Study
Multihop Question Answering is a complex Natural Language Processing task that requires multiple steps of reasoning to find the correct answer to a given question.
Structured Q-learning For Antibody Design
Optimizing combinatorial structures is core to many real-world problems, such as those encountered in life sciences.
Improving Commonsense Causal Reasoning by Adversarial Training and Data Augmentation
Determining the plausibility of causal relations between clauses is a commonsense reasoning task that requires complex inference ability.
$\alpha$VIL: Learning to Leverage Auxiliary Tasks for Multitask Learning
In such settings, it becomes important to estimate the positive or negative influence auxiliary tasks will have on the target.
Improving End-to-End Speech-to-Intent Classification with Reptile
In this paper, we suggest improving the generalization performance of SLU models with a non-standard learning algorithm, Reptile.
Ranked #12 on
Spoken Language Understanding
on Fluent Speech Commands
(using extra training data)
Learning Dialog Policies from Weak Demonstrations
Deep reinforcement learning is a promising approach to training a dialog manager, but current methods struggle with the large state and action spaces of multi-domain dialog systems.
Show Us the Way: Learning to Manage Dialog from Demonstrations
We present our submission to the End-to-End Multi-Domain Dialog Challenge Track of the Eighth Dialog System Technology Challenge.
Named Entity Recognition for Electronic Health Records: A Comparison of Rule-based and Machine Learning Approaches
This work investigates multiple approaches to Named Entity Recognition (NER) for text in Electronic Health Record (EHR) data.
What's This Movie About? A Joint Neural Network Architecture for Movie Content Analysis
This work takes a first step toward movie content analysis by tackling the novel task of movie overview generation.
