1 citations · 3 across the 38 of their papers we have counts for
15 papers · 1 filter
Alaya-EVOKE: From Linear-Scaling Supervision to Endless World
Yuanyang Yin, Gongxuan Wang, Yifan Zhan +3
Interactive world models must support persistent memory, responsive interaction, and long-horizon generation, yet these requirements place conflicting demands on the model. Maintai…
Marionette: Predicting World States, Rendering Geometry, Painting Appearance
Zian Meng, Zhen Li, Chuanhao Li +2
Interactive game world models typically autoregress visual observations directly in pixel or latent space, forcing structured properties such as pose, geometry, and occlusion to be…
AlayaWorld: Interactive Long-Horizon World Modeling - Full Technical Report (v1.1)
AlayaWorld Team, Kaipeng Zhang, Chuanhao Li +15
This report presents an improved version of AlayaWorld. While the backbone architecture, chunk-wise autoregressive generation scheme, and training data remain unchanged from the pr…
Beyond the Capability Boundary: Zeroth-Order Optimization for Self-Evolving LLM Agents
Bingzhen Liu, Xiaomeng Fan, Yuwei Wu +4
Self-evolving methods improve the capabilities of LLM agents by sampling trajectories from the underlying LLMs and learning from these trajectories. However, these methods struggle…
Surprise Forcing: What to Remember, When to Skip in Long Video Generation
Shuwei Shi, Zhen Li, Muyao Niu +4
Streaming autoregressive diffusion makes minute-scale video synthesis practical, but its bounded context and fixed denoising schedule allocate resources uniformly across a highly n…
AlayaWorld: Interactive Long-Horizon World Modeling -- Full Technical Report
AlayaWorld Team, Kaipeng Zhang, Chuanhao Li +15
Unlike conventional video game development, which relies on labor-intensive pipelines for asset production, animation, physics, and programming, video world models generate interac…
From Pixels to States: Rethinking Interactive World Models as Game Engines
Zhen Li, Zian Meng, Shuwei Shi +4
Building interactive worlds that respond coherently to player actions has long been a shared goal of computer graphics, games, and artificial intelligence. Recent video generative…
AlayaWorld: Long-Horizon and Playable Video World Generation
AlayaWorld Team, Kaipeng Zhang, Chuanhao Li +14
Game worlds have traditionally been built through labor-intensive production pipelines, making them costly to develop, difficult to customization, and expensive to modify after dep…
AgenticSTS: A Bounded-Memory Testbed for Long-Horizon LLM Agents
Xiangchen Cheng, Yunwei Jiang, Jianwen Sun +7
Memory for a long-horizon LLM agent is a contract about what each future decision is allowed to see. The simplest contract appends past observations, tool calls, and reflections to…
JAMER: Project-Level Code Framework Dataset and Benchmark on Professional Game Engines
Jianwen Sun, Chuanhao Li, Zizhen Li +5
Current AI-driven game development has made substantial progress in asset generation, gameplay design, and web-based game coding, yet project-level code engineering on professional…
CoBG: Learning from Player Reviews to Design, Critique, and Revise Board Game Rulebooks
Zizhen Li, Chuanhao Li, Yibin Wang +6
Board game design alternates between thinking as a designer and experiencing as a player, over repeated cycles of prototyping, critique, and revision. This loop is cognitively dema…
PixelSmile: Toward Fine-Grained Facial Expression Editing
Jiabin Hua, Hengyuan Xu, Aojie Li +4
Fine-grained facial expression editing has long been limited by intrinsic semantic overlap. To address this, we construct the Flex Facial Expression (FFE) dataset with continuous a…
WildWorld: A Large-Scale Dataset for Dynamic World Modeling with Actions and Explicit State toward Generative ARPG
Zhen Li, Zian Meng, Shuwei Shi +5
Dynamical systems theory and reinforcement learning view world evolution as latent-state dynamics driven by actions, with visual observations providing partial information about th…
World Craft: Agentic Framework to Create Visualizable Worlds via Text
Jianwen Sun, Yukang Feng, Kaining Ying +8
Large Language Models (LLMs) motivate generative agent simulation (e.g., AI Town) to create a ``dynamic world'', holding immense value across entertainment and research. However, f…
MeepleLM: A Virtual Playtester Simulating Diverse Subjective Experiences
Zizhen Li, Chuanhao Li, Yibin Wang +7
Recent advancements have expanded the role of Large Language Models in board games from playing agents to creative co-designers. However, a critical gap remains: current systems la…