1 citations · 1 across the 12 of their papers we have counts for
13 papers
RSIGame: Autonomous Agentic Game Development with Recursive Self-improvement
Wenyi Wu, Minghao Fu, Jieyu You +10
Recent advances in large language models have made automatic game generation increasingly feasible, yet reliably improving generated games beyond a playable version remains challen…
CausalWM: Causal Chain-of-Thought Reasoning for Embodied World Model
Ziming Xu, Shuang Liang, Ruobing Han +10
Embodied world models learn to predict future physical dynamics from visual observations and control signals, where physical knowledge is implicitly entangled within latent represe…
StructAgent: Harness Long-horizon Digital Agents with Unified Causal Structure
Wenyi Wu, Sibo Zhu, Kun Zhou +3
Recent advances in large language models (LLMs) and vision-language models (VLMs) have enabled increasingly capable digital agents for computer use. However, real-world tasks are o…
Hybrid Self-evolving Structured Memory for GUI Agents
Sibo Zhu, Wenyi Wu, Kun Zhou +2
The remarkable progress of vision-language models (VLMs) has enabled GUI agents to interact with computers in a human-like manner. Yet real-world computer-use tasks remain difficul…
Learning Modal-Mixed Chain-of-Thought Reasoning with Latent Embeddings
Yifei Shao, Kun Zhou, Ziming Xu +5
We study how to extend chain-of-thought (CoT) beyond language to better handle multimodal reasoning. While CoT helps LLMs and VLMs articulate intermediate steps, its text-only form…
Ability Transfer and Recovery via Modularized Parameters Localization
Songyao Jin, Kun Zhou, Wenqi Li +2
Large language models can be continually pre-trained or fine-tuned to improve performance in specific domains, languages, or skills, but this specialization often degrades other ca…
C-World: A Computer Use Agent Environment Creator
Ziqiao Xi, Shuang Liang, Qi Liu +9
To close the gap between LLM-based agents and humans in planning and reasoning, agents need large-scale, diverse environments for continuous learning -- yet building such environme…
Learning Plug-and-play Memory for Guiding Video Diffusion Models
Selena Song, Ziming Xu, Zijun Zhang +4
Diffusion Transformer(DiT) based video generation models have recently achieved impressive visual quality and temporal coherence, but they still frequently violate basic physical l…
Auto-scaling Continuous Memory for GUI Agent
Wenyi Wu, Kun Zhou, Ruoxin Yuan +4
We study how to endow GUI agents with scalable memory that help generalize across unfamiliar interfaces and long-horizon tasks. Prior GUI agents compress past trajectories into tex…
Backdoor Attribution: Elucidating and Controlling Backdoor in Language Models
Miao Yu, Zhenhong Zhou, Moayad Aloqaily +5
Fine-tuned Large Language Models (LLMs) are vulnerable to backdoor attacks through data poisoning, yet the internal mechanisms governing these attacks remain a black box. Previous…
Causal Structure Learning in Hawkes Processes with Complex Latent Confounder Networks
Songyao Jin, Biwei Huang
Multivariate Hawkes process provides a powerful framework for modeling temporal dependencies and event-driven interactions in complex systems. While existing methods primarily focu…
Activation Control for Efficiently Eliciting Long Chain-of-thought Ability of Language Models
Zekai Zhao, Qi Liu, Kun Zhou +4
Despite the remarkable reasoning performance, eliciting the long chain-of-thought (CoT) ability in large language models (LLMs) typically requires costly reinforcement learning or…
Towards General Continuous Memory for Vision-Language Models
Wenyi Wu, Zixuan Song, Kun Zhou +3
Language models (LMs) and their extension, vision-language models (VLMs), have achieved remarkable performance across various tasks. However, they still struggle with complex reaso…