activity
20232026
most citedRAT: Retrieval Augmented Thoughts Elicit Context-Aware Reasoning in Long-Horizon Generation

10 citations · 10 across the 10 of their papers we have counts for

collaborators

29 papers

cs.AI2026

Can Current Agents Close the Discovery-to-Application Gap? A Case Study in Minecraft

Zhou Ziheng, Huacong Tang, Jinyuan Zhang +9

Discovering causal regularities and applying them to build functional systems--the discovery-to-application loop--is a hallmark of general intelligence, yet evaluating this capacit…

cs.AR2026

CREATE: Cross-Layer Resilience Characterization and Optimization for Efficient yet Reliable Embodied AI Systems

Tong Xie, Yijiahao Qi, Jinqi Wen +9

Embodied Artificial Intelligence (AI) has recently attracted significant attention as it bridges AI with the physical world. Modern embodied AI systems often combine a Large Langua…

cs.CL2026

SmartSnap: Proactive Evidence Seeking for Self-Verifying Agents

Shaofei Cai, Yulei Qin, Haojia Lin +10

Agentic reinforcement learning (RL) holds great promise for the development of autonomous agents under complex GUI tasks, but its scalability remains severely hampered by the verif…

cs.LG2025

Training One Model to Master Cross-Level Agentic Actions via Reinforcement Learning

Kaichen He, Zihao Wang, Muyao Li +2

The paradigm of agentic AI is shifting from engineered complex workflows to post-training native models. However, existing agents are typically confined to static, predefined actio…

cs.SE2025

UniCode: Augmenting Evaluation for Code Reasoning

Xinyue Zheng, Haowei Lin, Shaofei Cai +3

Current coding benchmarks often inflate Large Language Model (LLM) capabilities due to static paradigms and data contamination, enabling models to exploit statistical shortcuts rat…

cs.AI2025

OpenHA: A Series of Open-Source Hierarchical Agentic Models in Minecraft

Zihao Wang, Muyao Li, Kaichen He +4

The choice of action spaces is a critical yet unresolved challenge in developing capable, end-to-end trainable agents. This paper first presents a large-scale, systematic compariso…