papers

Publications (15)

cs.CV2023

Tri-MipRF: Tri-Mip Representation for Efficient Anti-Aliasing Neural Radiance Fields

Wenbo Hu, Yuling Wang, Lin Ma +4

Despite the tremendous progress in neural radiance fields (NeRF), we still face a dilemma of the trade-off between quality and efficiency, e.g., MipNeRF presents fine-detailed and…

cs.AI2025

LightPROF: A Lightweight Reasoning Framework for Large Language Model on Knowledge Graph

Tu Ao, Yanhua Yu, Yuling Wang +7

Large Language Models (LLMs) have impressive capabilities in text understanding and zero-shot reasoning. However, delays in knowledge updates may cause them to reason incorrectly o…

cs.LG2025

GraphEdit: Large Language Models for Graph Structure Learning

Zirui Guo, Lianghao Xia, Yanhua Yu +4

Graph Structure Learning (GSL) focuses on capturing intrinsic dependencies and interactions among nodes in graph-structured data by generating novel graph structures. Graph Neural…

math.AP2019

Existence of solutions for critical Choquard problem with singular coefficients

Yang Yang, Yuling Wang, Yong Wang

In this paper, we investigate the following fractional Choquard type equation: \[ (- Δ)_p^s\, u = λ\frac{|u|^{r-2}u}{|x|^α}\,+γ\big(\int_Ω\frac{|u|^q}{|x-y|^μ}dy\big) |u|^{q-…

cs.AI2025

HeTa: Relation-wise Heterogeneous Graph Foundation Attack Model

Yuling Wang, Zihui Chen, Pengfei Jiao +1

Heterogeneous Graph Neural Networks (HGNNs) are vulnerable, highlighting the need for tailored attacks to assess their robustness and ensure security. However, existing HGNN attack…

cs.LG2025

Addressing Graph Heterogeneity and Heterophily from A Spectral Perspective

Kangkang Lu, Yanhua Yu, Zhiyong Huang +6

Graph neural networks (GNNs) have demonstrated excellent performance in semi-supervised node classification tasks. Despite this, two primary challenges persist: heterogeneity and h…

cs.AI2026

Can LLMs Fool Graph Learning? Exploring Universal Adversarial Attacks on Text-Attributed Graphs

Zihui Chen, Yuling Wang, Pengfei Jiao +4

Text-attributed graphs (TAGs) enhance graph learning by integrating rich textual semantics and topological context for each node. While boosting expressiveness, they also expose ne…

cs.IT2009

Hybrid Decoding of Finite Geometry LDPC Codes

Guangwen Li, Dashe Li, Yuling Wang +1

For finite geometry low-density parity-check codes, heavy row and column weights in their parity check matrix make the decoding with even Min-Sum (MS) variants computationally expe…

eess.IV2025

Automatic nodule identification and differentiation in ultrasound videos to facilitate per-nodule examination

Siyuan Jiang, Yan Ding, Yuling Wang +9

Ultrasound is a vital diagnostic technique in health screening, with the advantages of non-invasive, cost-effective, and radiation free, and therefore is widely applied in the diag…

cs.LG2026

Reflex: Reinforcement Learning with Reflection Symmetry Exploitation in State-Based Continuous Control

Shuai Zhen, Yifan Zhang, Yuling Wang +1

Reinforcement learning has long struggled with poor sample efficiency. One promising approach to mitigate this problem is leveraging group-invariant Markov Decision Processes (-…

cs.IR2024

Can Small Language Models be Good Reasoners for Sequential Recommendation?

Yuling Wang, Changxin Tian, Binbin Hu +6

Large language models (LLMs) open up new horizons for sequential recommendations, owing to their remarkable language comprehension and generation capabilities. However, there are s…

cs.IR2024

Intent-aware Recommendation via Disentangled Graph Contrastive Learning

Yuling Wang, Xiao Wang, Xiangzhou Huang +5

Graph neural network (GNN) based recommender systems have become one of the mainstream trends due to the powerful learning ability from user behavior data. Understanding the user i…

cs.LG2022

Ensemble Multi-Relational Graph Neural Networks

Yuling Wang, Hao Xu, Yanhua Yu +4

It is well established that graph neural networks (GNNs) can be interpreted and designed from the perspective of optimization objective. With this clear optimization objective, the…

cs.AI2025

Communicative Agents for Slideshow Storytelling Video Generation based on LLMs

Jingxing Fan, Jinrong Shen, Yusheng Yao +3

With the rapid advancement of artificial intelligence (AI), the proliferation of AI-generated content (AIGC) tasks has significantly accelerated developments in text-to-video gener…

cs.CY2025

The Third Moment of AI Ethics: Developing Relatable and Contextualized Tools

Sarah Hladikova, Yuling Wang, Andreia Martinho

Artificial intelligence (AI) ethics has gained significant momentum, evidenced by the growing body of published literature, policy guidelines, and public discourse. However, the pr…