66 citations · 162 across the 35 of their papers we have counts for
35 papers
User Representation via Cross Multi-source Behavior Pre-training for Mobile Games
Chengqi Yang, Yiran Qiao, Feng Liu +7
User representation pre-training has become a fundamental paradigm for alleviating data sparsity in downstream personalization tasks. However, existing studies predominantly focus…
LiveSim: Simulating Environment-Shaped Users in Multi-Agent Live-Stream Ecosystems
Jiaqi Xu, Yiran Qiao, Jing Chen +3
User behavior simulation with large language models~(LLMs) is increasingly used to support multi-agent ecosystem simulation. Existing simulators typically rely on static user profi…
ZenGen: Social Mind for LLMs
ZenGen Team, Ao Xiang, Bi Jingping +57
As large language models move from isolated task solving toward long-term service in human environments, they require social intelligence: the ability to infer mental states, track…
Outsmarting the Chameleon: Counterfactual Decoupling for Tactical OOD Shifts in Live Streaming Risk Assessment
Yiran Qiao, Jing Chen, Jiaqi Xu +3
Live streaming has emerged as a primary medium for social interaction and digital commerce, yet it is increasingly plagued by sophisticated risks. A fundamental challenge in this d…
BadSKP: Backdoor Attacks on Knowledge Graph-Enhanced LLMs with Soft Prompts
Xiaoting Lyu, Yufei Han, Hangwei Qian +6
Recent knowledge graph (KG)-enhanced large language models (LLMs) move beyond purely textual knowledge augmentation by encoding retrieved subgraphs into continuous soft prompts via…
Follow the TRACE: Exploiting Post-Click Trajectories for Online Delayed Conversion Rate Prediction
Xinyue Zhang, Yuanhao Ding, Xiang Ao
Delayed feedback poses a core challenge for online CVR prediction, forcing a trade-off between label accuracy and data freshness. Existing methods address this through delay modeli…
TriTS: Time Series Forecasting from a Multimodal Perspective
Xiang Ao
Time series forecasting plays a pivotal role in critical sectors such as finance, energy, transportation, and meteorology. However, Long-term Time Series Forecasting (LTSF) remains…
AWPD: Frequency Shield Network for Agnostic Watermark Presence Detection
Xiang Ao, Yilin Du, Zidan Wang +2
Invisible watermarks, as an essential technology for image copyright protection, have been widely deployed with the rapid development of social media and AIGC. However, existing in…
Judge Like Human Examiners: A Weighted Importance Multi-Point Evaluation Framework for Generative Tasks with Long-form Answers
Guoxin Yu, Chulun Zhou, Lemao Liu +7
Evaluating the quality of model responses remains challenging in generative tasks with long-form answers, as the expected answers usually contain multiple semantically distinct yet…
DySCo: Dynamic Semantic Compression for Effective Long-term Time Series Forecasting
Xiang Ao, Yinyu Tan, Mengru Chen
Time series forecasting (TSF) is critical across domains such as finance, meteorology, and energy. While extending the lookback window theoretically provides richer historical cont…
Dynamic Forecasting and Temporal Feature Evolution of Stock Repurchases in Listed Companies Using Attention-Based Deep Temporal Networks
Xiang Ao, Jingxuan Zhang, Xinyu Zhao
Accurately predicting stock repurchases is crucial for quantitative investment and risk management, yet traditional static models fail to capture the complex temporal dependencies…
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…
XLinear: Frequency-Enhanced MLP with CrossFilter for Robust Long-Range Forecasting
Xiang Ao
Time series forecasters are widely used across various domains. Among them, MLP (multi-layer perceptron)-based forecasters have been proven to be more robust to noise compared to T…
SDMixer: Sparse Dual-Mixer for Time Series Forecasting
Xiang Ao
Multivariate time series forecasting is widely applied in fields such as transportation, energy, and finance. However, the data commonly suffers from issues of multi-scale characte…
Live or Lie: Action-Aware Capsule Multiple Instance Learning for Risk Assessment in Live Streaming Platforms
Yiran Qiao, Jing Chen, Xiang Ao +3
Live streaming has become a cornerstone of today's internet, enabling massive real-time social interactions. However, it faces severe risks arising from sparse, coordinated malicio…
Adaptive Dual-Weighting Framework for Federated Learning via Out-of-Distribution Detection
Zhiwei Ling, Hailiang Zhao, Chao Zhang +8
Federated Learning (FL) enables collaborative model training across large-scale distributed service nodes while preserving data privacy, making it a cornerstone of intelligent serv…
GDCNet: Generative Discrepancy Comparison Network for Multimodal Sarcasm Detection
Shuguang Zhang, Junhong Lian, Guoxin Yu +2
Multimodal sarcasm detection (MSD) aims to identify sarcasm within image-text pairs by modeling semantic incongruities across modalities. Existing methods often exploit cross-modal…
Deja Vu in Plots: Leveraging Cross-Session Evidence with Retrieval-Augmented LLMs for Live Streaming Risk Assessment
Yiran Qiao, Xiang Ao, Jing Chen +3
The rise of live streaming has transformed online interaction, enabling massive real-time engagement but also exposing platforms to complex risks such as scams and coordinated mali…
Beyond the Pre-Service Horizon: Infusing In-Service Behavior for Improved Financial Risk Forecasting
Senhao Liu, Zhiyu Guo, Zhiyuan Ji +5
Typical financial risk management involves distinct phases for pre-service risk assessment and in-service default detection, often modeled separately. This paper proposes a novel f…
Improved Personalized Headline Generation via Denoising Fake Interests from Implicit Feedback
Kejin Liu, Junhong Lian, Xiang Ao +5
Accurate personalized headline generation hinges on precisely capturing user interests from historical behaviors. However, existing methods neglect personalized-irrelevant click no…
Gradient-Adaptive Policy Optimization: Towards Multi-Objective Alignment of Large Language Models
Chengao Li, Hanyu Zhang, Yunkun Xu +3
Reinforcement Learning from Human Feedback (RLHF) has emerged as a powerful technique for aligning large language models (LLMs) with human preferences. However, effectively alignin…
Panoramic Interests: Stylistic-Content Aware Personalized Headline Generation
Junhong Lian, Xiang Ao, Xinyu Liu +2
Personalized news headline generation aims to provide users with attention-grabbing headlines that are tailored to their preferences. Prevailing methods focus on user-oriented cont…
Fact-Preserved Personalized News Headline Generation
Zhao Yang, Junhong Lian, Xiang Ao
Personalized news headline generation, aiming at generating user-specific headlines based on readers' preferences, burgeons a recent flourishing research direction. Existing studie…
Controlling Large Language Models Through Concept Activation Vectors
Hanyu Zhang, Xiting Wang, Chengao Li +2
As large language models (LLMs) are widely deployed across various domains, the ability to control their generated outputs has become more critical. This control involves aligning…