6 papers
CARE: Context-Aware Ranking Evolution with Executable Scoring Programs for Budgeted Reaction Optimization
Guanyu Liu, Weiyi Kong, Chao Tang +5
High-throughput experimentation can evaluate many reaction conditions, yet combinatorial condition spaces still exceed the available experiment budget. This makes experiment select…
See, Infer, Intervene: Proactive World Modeling for Goal-Oriented Social Intelligence
Honghui Zhang, Chenmeinian Guo, Yichen Yu +7
Multimodal retail agents should not only recognize what a customer is doing, but also decide whether and how to assist before an explicit request is made. We study this setting thr…
Symphony-Coord: Adaptive Routing for Multi-Agent LLM Systems
Zhaoyang Guan, Huixi Cao, Ming Zhong +6
Multi-agent large language model systems can tackle complex multi-step tasks by decomposing work and coordinating specialized behaviors. However, current coordination mechanisms ty…
MAPGD: Multi-Agent Prompt Gradient Descent for Collaborative Prompt Optimization
Yichen Han, Yuhang Han, Siteng Huang +7
Prompt engineering is crucial for fully leveraging large language models (LLMs), yet most existing optimization methods follow a single trajectory, resulting in limited adaptabilit…
Meta-Learning Reinforcement Learning for Crypto-Return Prediction
Junqiao Wang, Zhaoyang Guan, Guanyu Liu +7
Predicting cryptocurrency returns is notoriously difficult: price movements are driven by a fast-shifting blend of on-chain activity, news flow, and social sentiment, while labeled…
Adaptive Detector-Verifier Framework for Zero-Shot Polyp Detection in Open-World Settings
Shengkai Xu, Hsiang Lun Kao, Tianxiang Xu +9
Polyp detectors trained on clean datasets often underperform in real-world endoscopy, where illumination changes, motion blur, and occlusions degrade image quality. Existing approa…