6 papers
TransXion: A High-Fidelity Graph Benchmark for Realistic Anti-Money Laundering
Keyang Chen, Mingxuan Jiang, Yongsheng Zhao +9
Money laundering poses severe risks to global financial systems, driving the widespread adoption of machine learning for transaction monitoring. However, progress remains stifled b…
From Text to Talk: Audio-Language Model Needs Non-Autoregressive Joint Training
Tianqiao Liu, Xueyi Li, Hao Wang +4
Recent advances in large language models (LLMs) have attracted significant interest in extending their capabilities to multimodal scenarios, particularly for speech-to-speech conve…
P-MIA: A Profiled-Based Membership Inference Attack on Cognitive Diagnosis Models
Mingliang Hou, Yinuo Wang, Teng Guo +6
Cognitive diagnosis models (CDMs) are pivotal for creating fine-grained learner profiles in modern intelligent education platforms. However, these models are trained on sensitive s…
PrivacyCD: Hierarchical Unlearning for Protecting Student Privacy in Cognitive Diagnosis
Mingliang Hou, Yinuo Wang, Teng Guo +6
The need to remove specific student data from cognitive diagnosis (CD) models has become a pressing requirement, driven by users' growing assertion of their "right to be forgotten"…
Advancing Mathematical Reasoning in Language Models: The Impact of Problem-Solving Data, Data Synthesis Methods, and Training Stages
Zui Chen, Tianqiao Liu, Mi Tian +3
Mathematical reasoning remains a challenging area for large language models (LLMs), prompting the development of math-specific LLMs such as LLEMMA, DeepSeekMath, and Qwen2-Math, am…
What Are Step-Level Reward Models Rewarding? Counterintuitive Findings from MCTS-Boosted Mathematical Reasoning
Yiran Ma, Zui Chen, Tianqiao Liu +4
Step-level reward models (SRMs) can significantly enhance mathematical reasoning performance through process supervision or step-level preference alignment based on reinforcement l…