1 citations · 1 across the 8 of their papers we have counts for
10 papers
GameWAM: A World Action Model for Video Games
Yuncheng Guo, Zhanqiu Zhang, Yiwen Guo +1
Modern video games combine first-person perception, rapid visual changes, persistent world state, and heterogeneous native controls. Existing game agents map visual and task contex…
Progressive Agent Skill Generation via Reinforcement Learning
Junhao Shen, Zhanqiu Zhang, Yiwen Guo +1
Recent large language model agents often use external skills as modular procedural units that condition inference and improve complex task solving. Thus, automatically generating h…
CONDUIT: A Unified Residual-Stream Restoration Framework for KV Cache Reuse in Vision-Language Models
Pengan Chen, Kaisheng Zheng, Liang Hong +10
Vision-language models (VLMs) often answer new questions about recurring visual content, where reusing the key-value (KV) cache can avoid re-encoding expensive visual prefixes. Exa…
The Position Curse: LLMs Struggle to Locate the Last Few Items in a List
Zhanqi Zhang, Hua-Dong Xiong, Robert C. Wilson +3
Modern large language models (LLMs) can find a needle in a haystack (locating a single relevant fact buried among hundreds of thousands of irrelevant tokens) with near-saturated ac…
Breaking Contextual Inertia: Reinforcement Learning with Single-Turn Anchors for Stable Multi-Turn Interaction
Xingwu Chen, Zhanqiu Zhang, Yiwen Guo +1
While LLMs demonstrate strong reasoning capabilities when provided with full information in a single turn, they exhibit substantial vulnerability in multi-turn interactions. Specif…
See Once, Then Act: Vision-Language-Action Model with Task Learning from One-Shot Video Demonstrations
Guangyan Chen, Meiling Wang, Qi Shao +10
Developing robust and general-purpose manipulation policies represents a fundamental objective in robotics research. While Vision-Language-Action (VLA) models have demonstrated pro…