Xiang Zhou

Agent-Aware Dropout DQN for Safe and Efficient On-line Dialogue Policy Learning

2017

Hand-crafted rules and reinforcement learning (RL) are two popular choices to obtain dialogue policy. The rule-based policy is often reliable within predefined scope but not self-adaptable, whereas RL is evolvable with data but often suffers …

Masked Part-Of-Speech Model: Does Modeling Long Context Help Unsupervised POS-tagging?

2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies

Previous Part-Of-Speech (POS) induction models usually assume certain independence assumptions (e.g., Markov, unidirectional, local dependency) that do not hold in real languages. For example, the subject-verb agreement can be both long-term and bidirectional. To facilitate …

Lightwave Fabrics: At-Scale Optical Circuit Switching for Datacenter and Machine Learning Systems

2024

We describe our experience developing what we believe to be the world’s first large-scale production deployments of lightwave fabrics used for both datacenter networking and machine-learning (ML) applications [1],[2],[3],[4]. Using optical circuit switches (OCSes) and …

Semantics-Aware BERT for Language Understanding

2020 · Proceedings of the AAAI Conference on Artificial Intelligence

The latest work on language representations carefully integrates contextualized features into language model training, which enables a series of success especially in various machine reading comprehension and natural language inference tasks. However, the existing language …

What Can We Learn from Collective Human Opinions on Natural Language Inference Data?

2020

Despite the subjective nature of many NLP tasks, most NLU evaluations have focused on using the majority label with presumably high agreement as the ground truth. Less attention has been paid to the distribution of …