research
∙
09/28/2022
Improving alignment of dialogue agents via targeted human judgements
We present Sparrow, an information-seeking dialogue agent trained to be ...
share
research
∙
06/16/2022
Characteristics of Harmful Text: Towards Rigorous Benchmarking of Language Models
Large language models produce human-like text that drive a growing numbe...
research
∙
02/08/2022
Competition-Level Code Generation with AlphaCode
Programming is a powerful and ubiquitous problem-solving tool. Developin...
research
∙
12/08/2021
Ethical and social risks of harm from Language Models
This paper aims to help structure the risk landscape associated with lar...
research
∙
09/15/2021
Challenges in Detoxifying Language Models
Large language models (LM) generate remarkably fluent text and can be ef...
research
∙
12/06/2019
Achieving Robustness in the Wild via Adversarial Mixing with Disentangled Representations
Recent research has made the surprising finding that state-of-the-art de...
research
∙
12/04/2019
Towards Robust Image Classification Using Sequential Attention Models
In this paper we propose to augment a modern neural-network architecture...
research
∙
11/08/2019
Reducing Sentiment Bias in Language Models via Counterfactual Evaluation
Recent improvements in large-scale language models have driven progress ...
research
∙
10/28/2019
Learning Transferable Graph Exploration
This paper considers the problem of efficient exploration of unseen envi...
research
∙
10/21/2019
An Alternative Surrogate Loss for PGD-based Adversarial Testing
Adversarial testing methods based on Projected Gradient Descent (PGD) ar...
research
∙
09/03/2019
Achieving Verified Robustness to Symbol Substitutions via Interval Bound Propagation
Neural networks are part of many contemporary NLP systems, yet their emp...
research
∙
05/31/2019
Are Labels Required for Improving Adversarial Robustness?
Recent work has uncovered the interesting (and somewhat surprising) find...
research
∙
04/26/2019
Knowing When to Stop: Evaluation and Verification of Conformity to Output-size Specifications
Models such as Sequence-to-Sequence and Image-to-Sequence are widely use...
research
∙
11/06/2018
Neural Phrase-to-Phrase Machine Translation
In this paper, we propose Neural Phrase-to-Phrase Machine Translation (N...
research
∙
07/09/2018
Robust Text-to-SQL Generation with Execution-Guided Decoding
We consider the problem of neural semantic parsing, which translates nat...
research
∙
07/09/2018
Execution-Guided Neural Program Decoding
We present a neural semantic parser that translatesnatural language ques...
research
∙
05/10/2018
Discourse-Aware Neural Rewards for Coherent Text Generation
In this paper, we investigate the use of discourse-aware rewards with re...
research
∙
03/02/2018
Natural Language to Structured Query Generation via Meta-Learning
In conventional supervised training, a model is trained to fit all the t...
research
∙
02/12/2018
ReinforceWalk: Learning to Walk in Graph with Monte Carlo Tree Search
Learning to walk over a graph towards a target node for a given input qu...
research
∙
06/29/2017
Two-Stage Synthesis Networks for Transfer Learning in Machine Comprehension
We develop a technique for transfer learning in machine comprehension (M...
research
∙
06/17/2017
Towards Neural Phrase-based Machine Translation
In this paper, we present Neural Phrase-based Machine Translation (NPMT)...
research
∙
02/24/2017
Sequence Modeling via Segmentations
Segmental structure is a common pattern in many types of sequences such ...
research
∙
11/14/2016
Traversing Knowledge Graph in Vector Space without Symbolic Space Guidance
Recent studies on knowledge base completion, the task of recovering miss...
research
∙
09/17/2016
ReasoNet: Learning to Stop Reading in Machine Comprehension
Teaching a computer to read and answer general questions pertaining to a...
research
∙
02/13/2015
