11 papers
Mitigating Compounding Error via Video Representation Regularization
Taiye Chen, Qi Zhang, Yisen Wang
Video diffusion-based world models enable long autoregressive video generation for robotics, autonomous driving and simulation tasks, yet sliding-window autoregressive inference su…
DWM: Separating World Effects from Actions in Latent World Models
Yi-Ge Zhang, Tianqi Du, Qi Zhang +1
Latent world models underpin much of modern model-based control, yet current action-conditioned formulations supervise the next-latent transition with a single, undifferentiated ta…
SAGE: Subgoal-Conditioned Action Generation for Latent World Model Planning
Letian Cheng, Qi Zhang, Yisen Wang
Latent world models have emerged as a powerful planning paradigm by learning action-conditioned predictive dynamics and using them as internal simulators to imagine and evaluate ca…
A Generalization Theory for JEPA-Based World Models
Jingyi Cui, Qi Zhang, Hongwei Wen +2
Joint Embedding Predictive Architectures (JEPAs) have emerged as a promising paradigm for world modeling by predicting future representations rather than reconstructing observation…
AGORA: An Archive-Grounded Benchmark for Agentic Workplace Document Reasoning
Honglin Guo, Qi Zhang, Yu Zhang +6
Large language models are increasingly deployed as agents that reason over documents rather than answer from parametric knowledge. We study archive-grounded reasoning: locating spa…
Group-Graph Policy Optimization for Long-Horizon Agentic Reinforcement Learning
Yunan Wang, Minghui Song, Zihan Zhang +6
Group-based Reinforcement Learning (RL) has significantly enhanced Large Language Models (LLMs) in agentic scenarios. To achieve finer-grained policy updates, recent agentic RL fra…
Scaling Performance and Low-Resource Annotation with Many-Shot In-Context Learning for Named Entity Recognition
Qi Zhang, Fangping Lan, Cornelia Caragea +2
In-context learning (ICL) with large language models (LLMs) has emerged as a powerful alternative to fine-tuning for Named Entity Recognition (NER), achieving strong performance wi…
Beyond the Next Step: Variable-Length Latent World Models for Long-Horizon Planning
Tianqi Du, Qi Zhang, Yifei Wang +1
Recently, world models have emerged as a promising paradigm for building intelligent agents by learning predictive models that estimate future environment states conditioned on obs…
MemGUI-Agent: An End-to-End Long-Horizon Mobile GUI Agent with Proactive Context Management
Guangyi Liu, Gao Wu, Congxiao Liu +7
MLLM-based mobile GUI agents have made substantial progress on short-horizon tasks, yet remain unreliable on long-horizon tasks that require retaining intermediate facts across man…
Pre-Trained Policy Discriminators are General Reward Models
Shihan Dou, Shichun Liu, Yuming Yang +19
We offer a novel perspective on reward modeling by formulating it as a policy discriminator, which quantifies the difference between two policies to generate a reward signal, guidi…
Capability Salience Vector: Fine-grained Alignment of Loss and Capabilities for Downstream Task Scaling Law
Qiming Ge, Shuhao Xing, Songyang Gao +8
Scaling law builds the relationship between training computation and validation loss, enabling researchers to effectively predict the loss trending of models across different level…