14 papers
AdaPCLA: Adaptive Prior-Calibrated Logit Adjustment for Long-Tailed Longitudinal EHR Generation
Shuai Cui, Chen Wenxuan, Wenjie Du +3
The paper introduces AdaPCLA, a framework that improves generative models for longitudinal electronic health records by adaptively adjusting logits to better represent rare disease…
Signal-Guided Optimization for Machine Unlearning
Xujia Li, Dan Li, Jian Lou +1
The paper introduces GSUO, a guidance-signal-aware optimization framework that uses fine-grained task-specific signals to improve the effectiveness and efficiency of machine unlear…
Autonomous End-to-End SOH Prediction Services for Battery Systems via Temporal-Contrastive Representation Learning
Junting Wen, Dan Li, Qihao Quan +8
Accurate state of health (SOH) estimation is a critical diagnostic service for lithium-ion battery management. However, reliance on labor-intensive manual feature engineering and o…
Activation Steering Induces Emergent Misalignment: A More Comprehensive Evaluation
Qi Cao, Jian Lou, Meiting Liu +4
Activation steering has emerged as a popular inference-time technique for modulating the behavior of large language models (LLMs). By constructing a steering vector from examples o…
TSQAgent: Rating Time Series Data Quality via Dedicated Agentic Reasoning
Shunyu Wu, Dan Li, Haozheng Ye +6
Assessing the quality of time series (TS) data is fundamental yet inherently challenging due to the multifaceted nature of quality dimensions. Recently, large language models (LLMs…
Exploiting Verification-Generation Gap: Test-Time Reinforcement Learning with Confidence-Conditioned Verification
Jiahui Li, Jianfeng Shan, Wenpei Chen +5
Test-time reinforcement learning has emerged as a promising paradigm for enhancing the complex reasoning abilities of large language models in a completely label-free manner. Despi…