1 citations · 1 across the 7 of their papers we have counts for
9 papers
Explore with Memory, Learn without It: In-Context Exploration and Self-Distillation for LLM Reasoning
Yutong Chen, Zhichao Xu, Rui Liu +1
Exploration bounds learning efficiency in reinforcement learning with verifiable rewards (RLVR). Current methods explore mostly through independent sampling, without fully using th…
Hierarchical and Permutation-Invariant Feature Transformation Learning via Policy-Guided Embedding Search
Rui Liu, Tao Zhe, Yanyong Huang +5
Feature transformation improves predictive performance on tabular data by constructing informative abstractions from raw features. Recent generative approaches encode transformatio…
Visual Representation and History Modeling for Navigation World Models
Guangfu Guo, Xiaoqian Lu, Rui Liu +3
Navigation World Models (NWMs) predict action-conditioned visual futures for planning. Two practical challenges are central to their design: selecting a suitable visual representat…
AgentOS: From Application Silos to a Natural Language-Driven Data Ecosystem
Rui Liu, Tao Zhe, Dongjie Wang +5
The rapid emergence of open-source, locally hosted intelligent agents marks a critical inflection point in human-computer interaction. Systems such as OpenClaw demonstrate that Lar…
City Editing: Hierarchical Agentic Execution for Dependency-Aware Urban Geospatial Modification
Rui Liu, Steven Jige Quan, Zhong-Ren Peng +6
Urban renewal requires incremental modifications to existing geospatial plans, yet manually updating complex layouts under spatial constraints is labor-intensive and error-prone. T…
Constraint-Aware Route Recommendation from Natural Language via Hierarchical LLM Agents
Tao Zhe, Rui Liu, Fateme Memar +5
Route recommendation aims to provide users with optimal travel plans that satisfy diverse and complex requirements. Classical routing algorithms (e.g., shortest-path and constraint…
Permutation-Invariant Representation Learning for Robust and Privacy-Preserving Feature Selection
Rui Liu, Tao Zhe, Yanjie Fu +3
Feature selection eliminates redundancy among features to improve downstream task performance while reducing computational overhead. Existing methods often struggle to capture intr…
Towards Urban Planing AI Agent in the Age of Agentic AI
Rui Liu, Tao Zhe, Zhong-Ren Peng +4
Generative AI, large language models, and agentic AI have emerged separately of urban planning. However, the convergence between AI and urban planning presents an interesting oppor…
Continuous Optimization for Feature Selection with Permutation-Invariant Embedding and Policy-Guided Search
Rui Liu, Rui Xie, Zijun Yao +2
Feature selection removes redundant features to enhanc performance and computational efficiency in downstream tasks. Existing works often struggle to capture complex feature intera…