A5045924734- Particle physics theoretical and experimental studies
- Advanced Graph Neural Networks
- Quantum Chromodynamics and Particle Interactions
- Natural Language Processing Techniques
- Topic Modeling
- Recommender Systems and Techniques
- Dark Matter and Cosmic Phenomena
- Atomic and Subatomic Physics Research
- Text Readability and Simplification
- Machine Learning in Healthcare
- Environmental and Agricultural Sciences
- Child Therapy and Development
- Plant Ecology and Soil Science
- Diverse Approaches in Healthcare and Education Studies
- Physical Education and Training Studies
- High-Energy Particle Collisions Research
- AI in cancer detection
- Neurobiology of Language and Bilingualism
- Computational Physics and Python Applications
- Reading and Literacy Development
- Forest, Soil, and Plant Ecology in China
Qufu Normal University
2025
Hong Kong Polytechnic University
2025
Yunnan University
2024
Nanjing Forestry University
2024
Hong Kong University of Science and Technology
2019
University of Hong Kong
2019
Georgia Institute of Technology
2019
Aalborg University
2019
The Yixing Yuantianjian small watershed is a provincial soil erosion key management area in the hilly region of southern Jiangsu. It has been implemented national control project for management, which typical and representative region. important to quantitatively evaluate quality under different land use modes then select suitable ecological restoration measures promote economic construction watersheds Used four types (forest land, garden arable abandoned land) as research object, 13...
Abstract The current absence of an eye-tracking database that explores bilingual language control and how intra-sentence code-switching types influence the process limits our deeper understanding mechanisms. To address this issue, we present a containing eye-movement recordings collected during silent reading task combined with switching paradigm. contains typical measures eye movement data 160 Chinese their translation equivalent English words from 40 high-proficient low-proficient...
Recent years have witnessed rapid advancements in the safety alignments of large language models (LLMs). Methods such as supervised instruction fine-tuning (SFT) and reinforcement learning with human feedback (RLHF) thus emerged vital components constructing LLMs. While these methods achieve robust fine-grained alignment to values, their practical application is still hindered by high annotation costs incomplete alignments. Besides, intrinsic values within training corpora not been fully...
The role of sports games in the research and application children's intellectual development is very important, but there a problem inaccurate evaluation results. Multi-marker learning cannot solve games, unreasonable. Therefore, this paper proposes multi-example multi-marker for analysis development. First all, mathematical theory used to apply indicators are divided reduced according requirements Interference factors early childhood intelligence Then, educational forms program development,...
The rapid expansion of multimedia contents has led to the emergence multimodal recommendation systems. It attracted increasing attention in systems because its full utilization data from different modalities alleviates persistent sparsity problem. As such, models can learn personalized information about nodes terms visual and textual. To further alleviate problem, some previous works have introduced graph convolutional networks (GCNs) for systems, enhance semantic representation users items...
Model extraction attacks (MEAs) on large language models (LLMs) have received increasing research attention lately. Existing attack methods LLMs inherit the strategies from those designed for deep neural networks (DNNs) yet neglect inconsistency of training tasks between MEA and LLMs' alignments. As such, they result in poor performances. To tackle this issue, we present Locality Reinforced Distillation (LoRD), a novel model algorithm specifically LLMs. In particular, design...
The drastic increase of large language models' (LLMs) parameters has led to a new research direction fine-tuning-free downstream customization by prompts, i.e., task descriptions. While these prompt-based services (e.g. OpenAI's GPTs) play an important role in many businesses, there emerged growing concerns about the prompt leakage, which undermines intellectual properties and causes attacks. In this paper, we analyze underlying mechanism refer as memorization, develop corresponding...
Welcome to MDM 2019, the 20th IEEE International Conference on Mobile Data Management