20 citations · 31 across the 31 of their papers we have counts for
8 papers · 1 filter
Flat-Consensus Diffusion for Robust Data Reshaping under Noisy Evaluator
Hongyu Cao, Kunpeng Liu, Fei Xie +1
Data shape determines how features are structured, how patterns are separated, and how distributions cover the underlying domain. Poor data shape can make models learn noise rather…
StaRPO: Stability-Augmented Reinforcement Policy Optimization
Jinghan Zhang, Fengran Mo, Tharindu Cyril Weerasooriya +5
Reinforcement learning (RL) is effective in enhancing the accuracy of large language models in complex reasoning tasks. Existing RL policy optimization frameworks rely on final-ans…
Causally-Guided Diffusion for Stable Feature Selection
Arun Vignesh Malarkkan, Xinyuan Wang, Kunpeng Liu +2
Feature selection is fundamental to robust data-centric AI, but most existing methods optimize predictive performance under a single data distribution. This often selects spurious…
Mitigating Shortcut Reasoning in Language Models: A Gradient-Aware Training Approach
Hongyu Cao, Kunpeng Liu, Dongjie Wang +1
Large language models exhibit strong reasoning capabilities, yet often rely on shortcuts such as surface pattern matching and answer memorization rather than genuine logical infere…
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…
Sim2Act: Robust Simulation-to-Decision Learning via Adversarial Calibration and Group-Relative Perturbation
Hongyu Cao, Jinghan Zhang, Kunpeng Liu +5
Simulation-to-decision learning enables safe policy training in digital environments without risking real-world deployment, and has become essential in mission-critical domains suc…
Evolving Demonstration Optimization for Chain-of-Thought Feature Transformation
Xinyuan Wang, Kunpeng Liu, Arun Vignesh Malarkkan +1
Feature Transformation (FT) is a core data-centric AI task that improves feature space quality to advance downstream predictive performance. However, discovering effective transfor…
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…