Yao Lu

Detecting "Smart" Spammers on Social Network: A Topic Model Approach

2016

Spammer detection on social network is a challenging problem. The rigid anti-spam rules have resulted in emergence of "smart" spammers. They resemble legitimate users who are difficult to identify. In this paper, we present a …

Query expansion for exploratory search with subtopic discovery in Community Question Answering

2016

Exploratory search is cumbersome with today's search engines, where a user aims to better understand complex concepts. Query expansions techniques have been widely used in exploratory search. However, query expansions often recommend queries that differ …

Cryptanalysis of an RSA variant with moduli <i>N</i> = <i> p ^r q ^l </i>

2017 · Journal of Mathematical Cryptology

Abstract In this paper we study an RSA variant with moduli of the form <m:math xmlns:m="http://www.w3.org/1998/Math/MathML"> <m:mrow> <m:mi>N</m:mi> <m:mo>=</m:mo> <m:mrow> <m:msup> <m:mi>p</m:mi> <m:mi>r</m:mi> </m:msup> <m:mo>⁢</m:mo> <m:msup> <m:mi>q</m:mi> <m:mi>l</m:mi> </m:msup> </m:mrow> </m:mrow> </m:math> {N=p^{r}q^{l}} ( <m:math …

A novel nipple detection algorithm on Digital Mammography (DM)

2018

Previous studies found that multiple view techniques improved the accuracy of lesion detection on mammograms. One of the key components in multiple view techniques was the detection of nipple location, which is the only reliable …

Cross-domain Aspect Category Transfer and Detection via Traceable Heterogeneous Graph Representation Learning

2019

Aspect category detection is an essential task for sentiment analysis and opinion mining. However, the cost of categorical data labeling, e.g., label the review aspect information for a large number of product domains, can be …

Distilling Task-Specific Knowledge from BERT into Simple Neural Networks

2019 · arXiv (Cornell University)

In the natural language processing literature, neural networks are becoming increasingly deeper and complex. The recent poster child of this trend is the deep language representation model, which includes BERT, ELMo, and GPT. These developments …

Generative Adversarial Network for Abstractive Text Summarization

2018 · Proceedings of the AAAI Conference on Artificial Intelligence

In this paper, we propose an adversarial process for abstractive text summarization, in which we simultaneously train a generative model G and a discriminative model D. In particular, we build the generator G as an …

Fantastically Ordered Prompts and Where to Find Them: Overcoming Few-Shot Prompt Order Sensitivity

2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

When primed with only a handful of training samples, very large, pretrained language models such as GPT-3 have shown competitive results when compared to fully-supervised, fine-tuned, large, pretrained language models. We demonstrate that the order …

Do As I Can, Not As I Say: Grounding Language in Robotic Affordances

2022 · arXiv (Cornell University)

Large language models can encode a wealth of semantic knowledge about the world. Such knowledge could be extremely useful to robots aiming to act upon high-level, temporally extended instructions expressed in natural language. However, a …

Fantastically Ordered Prompts and Where to Find Them: Overcoming Few-Shot Prompt Order Sensitivity

2021 · arXiv (Cornell University)

When primed with only a handful of training samples, very large, pretrained language models such as GPT-3 have shown competitive results when compared to fully-supervised, fine-tuned, large, pretrained language models. We demonstrate that the order …