Qian Yang

Learning Compressed Sentence Representations for On-Device Text Processing

2019 · arXiv (Cornell University)

Vector representations of sentences, trained on massive text corpora, are widely used as generic sentence embeddings across a variety of NLP problems. The learned representations are generally assumed to be continuous and real-valued, giving rise …

Faster On-Device Training Using New Federated Momentum Algorithm

2020 · arXiv (Cornell University)

Mobile crowdsensing has gained significant attention in recent years and has become a critical paradigm for emerging Internet of Things applications. The sensing devices continuously generate a significant quantity of data, which provide tremendous opportunities …

Beyond Code Generation: LLM-supported Exploration of the Program Design Space

2025

In this work, we explore explicit Large Language Model (LLM)powered support for the iterative design of computer programs.Program design, like other design activity, is characterized by navigating a space of alternative problem formulations and associated …

Attention: What prevents young adults from speaking up against cyberbullying in an LLM-powered social media simulation

2026 · Design and Artificial Intelligence

Interactive, multi-agent social simulation systems have shown promise for helping users practice navigating various complex social situations across domains. This paper asks: To what extent can such systems help young adult (YA) bystanders speak up …

Adaptive encrypted traffic classification via online hash center evolution

2026 · Journal of King Saud University - Computer and Information Sciences

With the widespread adoption of network encryption protocols, encrypted traffic enhances communication privacy while posing new challenges for threat detection. Although deep learning based encrypted traffic classification has achieved notable progress in recent years, most …