2 citations · 2 across the 5 of their papers we have counts for
6 papers
OSCAR: Optimization-Steered Agentic Planning for Composed Image Retrieval
Teng Wang, Rong Shan, Jianghao Lin +8
Composed image retrieval (CIR) requires complex reasoning over heterogeneous visual and textual constraints. Existing approaches largely fall into two paradigms: unified embedding…
Towards Hierarchical Multi-Step Reward Models for Enhanced Reasoning in Large Language Models
Teng Wang, Zhangyi Jiang, Zhenqi He +9
Recent studies show that Large Language Models (LLMs) achieve strong reasoning capabilities through supervised fine-tuning or reinforcement learning. However, a key approach, the P…
Generative Models in Decision Making: A Survey
Xinyu Shao, Jianping Zhang, Haozhi Wang +9
Generative models have fundamentally reshaped the landscape of decision-making, reframing the problem from pure scalar reward maximization to high-fidelity trajectory generation an…
Leveraging Large Language Models for Solving Rare MIP Challenges
Teng Wang, Wing-Yin Yu, Ruifeng She +3
Mixed Integer Programming (MIP) has been extensively applied in areas requiring mathematical solvers to address complex instances within tight time constraints. However, as the pro…
Neural HD Map Generation from Multiple Vectorized Tiles Locally Produced by Autonomous Vehicles
Miao Fan, Yi Yao, Jianping Zhang +2
High-definition (HD) map is a fundamental component of autonomous driving systems, as it can provide precise environmental information about driving scenes. Recent work on vectoriz…
TroubleLLM: Align to Red Team Expert
Zhuoer Xu, Jianping Zhang, Shiwen Cui +2
Large Language Models (LLMs) become the start-of-the-art solutions for a variety of natural language tasks and are integrated into real-world applications. However, LLMs can be pot…