18 papers
From Neglect to Resignation: Understanding the Evolution of Mobile Privacy
Yibo Meng, Ziqi Liu, Lionel Z. Wang +2
This decade-long longitudinal qualitative study follows 31 smartphone users in China across four interview waves (2014-2023) to examine how mobile privacy understanding evolves alo…
Video-DeepResearch: Towards the Next-Generation Multimodal Deepresearch Agent
Zhen Fang, Yu Zeng, Wenxuan Huang +17
We introduce Video-DeepResearch (Video-DR), extending multimodal agents from static images to continuous video streams, a setting that demands dense spatiotemporal grounding couple…
ExpressionCueLens: A Cross-Cultural Analysis of Human-AI Companion Conversations on Social Media
Lynnette Hui Xian Ng, Yunze Xiao, Lionel Z. Wang +2
LLM-based AI companion agents are increasingly being perceived not only as tools but also as social companions. On social media, people recount conversations where these agents com…
NüshuVoice: Reviving the Voice of Endangered Nüshu with Pitch-Aware Text-to-Speech
Hongkun Yang, Xinhui Yi, Xiyan Zhao +13
Nüshu is an endangered phonetic script historically used by women in Jiangyong County, southern Hunan, China. While existing computational studies of Nüshu mainly focus on textual…
Reasoning as an Attack Surface: Adaptive Evolutionary CoT Jailbreaks for LLMs
Jianan Li, Simeng Qin, Xiaojun Jia +5
Large Reasoning Models (LRMs) have demonstrated remarkable capabilities in reasoning and generation tasks and are increasingly deployed in real-world applications. However, their e…
Contexting as Recommendation: Evolutionary Collaborative Filtering for Context Engineering
Jiachen Zhu, Zhuoying Ou, Congmin Zheng +9
Large Language Models (LLMs) are highly sensitive to their input contexts, motivating the development of automated context engineering. However, existing methods predominantly trea…
SCOPE: Structured Decomposition and Conditional Skill Orchestration for Complex Image Generation
Tianfei Ren, Zhipeng Yan, Yiming Zhao +13
While text-to-image models have made strong progress in visual fidelity, faithfully realizing complex visual intents remains challenging because many requirements must be tracked a…
DeAR: Fine-Grained VLM Adaptation by Decomposing Attention Head Roles
Yiming Ma, Hongkun Yang, Lionel Z. Wang +3
Prompt learning is a dominant paradigm for adapting pre-trained Vision-Language Models (VLMs) to downstream tasks. However, existing methods often rely on a simplistic, layer-centr…
IMMACULATE: A Practical LLM Auditing Framework via Verifiable Computation
Yanpei Guo, Wenjie Qu, Linyu Wu +7
Commercial large language models are typically deployed as black-box API services, requiring users to trust providers to execute inference correctly and report token usage honestly…
How Implicit Bias Accumulates and Propagates in LLM Long-term Memory
Yiming Ma, Lixu Wang, Lionel Z. Wang +6
Long-term memory mechanisms enable Large Language Models (LLMs) to maintain continuity and personalization across extended interaction lifecycles, but they also introduce new and u…
DP-MGTD: Privacy-Preserving Machine-Generated Text Detection via Adaptive Differentially Private Entity Sanitization
Lionel Z. Wang, Yusheng Zhao, Jiabin Luo +6
The deployment of Machine-Generated Text (MGT) detection systems necessitates processing sensitive user data, creating a fundamental conflict between authorship verification and pr…
AppellateGen: A Benchmark for Appellate Legal Judgment Generation
Hongkun Yang, Lionel Z. Wang, Wei Fan +10
Legal judgment generation is a critical task in legal intelligence. However, existing research in legal judgment generation has predominantly focused on first-instance trials, rely…
SugarTextNet: A Transformer-Based Framework for Detecting Sugar Dating-Related Content on Social Media with Context-Aware Focal Loss
Lionel Z. Wang, Shihan Ben, Yulu Huang +1
Sugar dating-related content has rapidly proliferated on mainstream social media platforms, giving rise to serious societal and regulatory concerns, including commercialization of…
RepoMark: A Data-Usage Auditing Framework for Code Large Language Models
Wenjie Qu, Yuguang Zhou, Bo Wang +4
The rapid development of Large Language Models (LLMs) for code generation has transformed software development by automating coding tasks with unprecedented efficiency. However, th…
Sub-Clustering for Class Distance Recalculation in Long-Tailed Drug Classification
Yujia Su, Xinjie Li, Lionel Z. Wang
In the real world, long-tailed data distributions are prevalent, making it challenging for models to effectively learn and classify tail classes. However, we discover that in the f…
JiraiBench: A Bilingual Benchmark for Evaluating Large Language Models' Detection of Human Self-Destructive Behavior Content in Jirai Community
Yunze Xiao, Tingyu He, Lionel Z. Wang +6
This paper introduces JiraiBench, the first bilingual benchmark for evaluating large language models' effectiveness in detecting self-destructive content across Chinese and Japanes…
MegaFake: A Theory-Driven Dataset of Fake News Generated by Large Language Models
Lionel Z. Wang, Ka Chung Ng, Yiming Ma +1
Fake news significantly influences decision-making processes by misleading individuals, organizations, and even governments. Large language models (LLMs), as part of generative AI,…
Modeling Inverse Ellipsometry Problem via Flow Matching with a Large-Scale Dataset
Yiming Ma, Jianzhi Teng, Xinjie Li +5
Inverse ellipsometry, i.e., reconstructing optical constants and film thickness from the measured phase difference and amplitude ratio , is a fundamentally ill-posed problem…