Publications (15)
An Image Is Worth 1000 Lies: Adversarial Transferability across Prompts on Vision-Language Models
Haochen Luo, Jindong Gu, Fengyuan Liu +1
Different from traditional task-specific vision models, recent large VLMs can readily adapt to different vision tasks by simply using different textual instructions, i.e., prompts.…
Harness-Aware Self-Evolving: Co-Evolving Model Weights, Harness, and Task Solutions
Haochen Luo, Yi Huang, Sichun Luo +5
Self-evolving frameworks usually optimize task solutions while treating the surrounding harness as fixed. We introduce Harness-Aware Self-Evolving (HASE), an agentic reinforcement-…
Relay, Don't Route: Adaptive Population Handoff for Cost-Efficient LLM-Driven Evolution
Sichun Luo, Yi Huang, Guanzhi Deng +6
Large language model (LLM)-driven evolution has shown promise for program search and algorithm discovery, but relying on strong models throughout long evolutionary runs is costly.…
A Novel Markov Model for Near-Term Railway Delay Prediction
Jin Xu, Weiqi Wang, Zheming Gao +2
Predicting the near-future delay with accuracy for trains is momentous for railway operations and passengers' traveling experience. This work aims to design prediction models for t…
Evolutionary Factor Searching for Sparse Portfolio Optimization Using Large Language Models
Haochen Luo, Jiandong Chen, Yuan Zhang +2
Sparse portfolio optimization is a fundamental yet challenging problem in quantitative finance. Traditional approaches often use static objectives and thus adapt poorly to dynamic…
Differentially Private Neural Network Training Under the Hidden State Assumption
Ding Chen, Chen Liu, Haochen Luo +1
Current differentially private learning paradigms face a severe utility bottleneck: DP-SGD degrades performance through noise accumulation over training steps, while aggregation-ba…