Dong Li

The Trends of Studies on the Chinese Cultural Industry - Focused on Chinese Academic Essays Published between 2009 and 2013

2015 · The Journal of the Humanities for Unification

중국에서는 2009년 국제금융위기를 통해, 문화산업은 국가차원의 전략적인 산업으로 부상하게 되었다. 이 중요한 전환시점에 부응하여 문화산업을 연구하는 학자들도 많아졌다. 필자는 중국최대의 논문사이트인 지망(知網, http://www.cnki.net/)을 이용해 문화산업, 중국문화산업 등 주요 키워드를 입력하여 2009년부터 2013년까지 모든 중국문화산업 관련 …

QoS-Based Service Selection Method for Big Data Service Composition

2017

Different from the traditional web services, the big data services' execution duration vary from the input data volume, so the traditional Quality of Service (QoS) analysis model for traditional web services cannot be directly applied …

Phase estimation of phase shifts in two arms for an SU(1,1) interferometer with coherent and squeezed vacuum states

2017 · Chinese Physics B

We theoretically present the quantum Cram\'{e}r-Rao bounds (QCRB) of an SU(1,1) interferometer for Gaussian states input with and without the internal photonic losses. The phase shifts in the single arm and in the double arms …

K-anonymity model for privacy-preserving soccer fitness data publishing

2018 · MATEC Web of Conferences

With the development of data mining technology, more and more researchers use the soccer fitness data to analyse the ranking of soccer athletes' and professional training. However, the direct release of soccer fitness data may …

Spam Review Detection with Graph Convolutional Networks

2019

Reviews on online shopping websites affect the buying decisions of customers, meanwhile, attract lots of spammers aiming at misleading buyers. Xianyu, the largest second-hand goods app in China, suffering from spam reviews. The anti-spam system …

On Sampling Top-K Recommendation Evaluation

2020

Recently, Rendle has warned that the use of sampling-based top-k metrics might not suffice. This throws a number of recent studies on deep learning-based recommendation algorithms, and classic non-deep-learning algorithms using such a metric, into …

An Efficient Transfer Learning Framework for Multiagent Reinforcement Learning

2020 · arXiv (Cornell University)

Transfer Learning has shown great potential to enhance single-agent Reinforcement Learning (RL) efficiency. Similarly, Multiagent RL (MARL) can also be accelerated if agents can share knowledge with each other. However, it remains a problem of …

Controllable Natural Language Generation with Contrastive Prefixes

2022 · Findings of the Association for Computational Linguistics: ACL 2022

To guide the generation of large pretrained language models (LM), previous work has focused on directly fine-tuning the language model or utilizing an attribute discriminator. In this work, we propose a novel lightweight framework for …

Rethinking Reinforcement Learning based Logic Synthesis

2022 · arXiv (Cornell University)

Recently, reinforcement learning has been used to address logic synthesis by formulating the operator sequence optimization problem as a Markov decision process. However, through extensive experiments, we find out that the learned policy makes decisions …

Scaling Laws for Linear Complexity Language Models

2024 · arXiv (Cornell University)

The interest in linear complexity models for large language models is on the rise, although their scaling capacity remains uncertain. In this study, we present the scaling laws for linear complexity language models to establish …

FADE: Towards Fairness-aware Data Generation for Domain Generalization via Classifier-Guided Score-based Diffusion Models

2024

Fairness-aware domain generalization (FairDG) has emerged as a critical challenge for deploying trustworthy AI systems, particularly in scenarios involving distribution shifts. Traditional methods for addressing fairness have failed in domain generalization due to their lack …

GDDA: Semantic OOD Detection on Graphs under Covariate Shift via Score-Based Diffusion Models

2024 · arXiv (Cornell University)

Out-of-distribution (OOD) detection poses a significant challenge for Graph Neural Networks (GNNs), particularly in open-world scenarios with varying distribution shifts. Most existing OOD detection methods on graphs primarily focus on identifying instances in test data …

Graph Counselor: Adaptive Graph Exploration via Multi-Agent Synergy to Enhance LLM Reasoning

2025 · arXiv (Cornell University)

Graph Retrieval Augmented Generation (GraphRAG) effectively enhances external knowledge integration capabilities by explicitly modeling knowledge relationships, thereby improving the factual accuracy and generation quality of Large Language Models (LLMs) in specialized domains. However, existing methods …