most citedWhat Makes Entities Similar? A Similarity Flooding Perspective for Multi-sourced Knowledge Graph Embeddings

1 citations · 2 across the 7 of their papers we have counts for

collaborators

7 papers

cs.AI2026

Polished but Unresolved: Identifying Late-Stage Pressure States in Long-Horizon Tool-Use Agents

Haoyang Chen, Yi Liu, Jianzhi Shao +3

Long-horizon tool-use agents need not only to search and plan, but also to decide when to finalize. We study late-stage pressure states, in which an agent is biased toward submitti…

cs.LG2026

CEDAR: Controlled and Event-Driven Demand Forecasting via Residual Decomposition

Junjie Meng, Ranxu Zhang, Zi-an Zhang +6

Forecasting in large-scale e-commerce marketplaces is increasingly required to support planning: merchants need to evaluate sales outcomes under future action sequences such as bud…

cs.LG2026

Agentic Reinforcement Learning with Self-Distilled Reward Shaping

Ranxu Zhang, Guinan Chen, Chenshaodong +5

Agentic reinforcement learning enables LLM agents to learn through interaction, but sparse trajectory-level rewards reveal success without identifying which intermediate decisions…

cs.CL2026

From Correctness to Preference: A Framework for Personalized Agentic Reinforcement Learning

Ranxu zhang, zeyang li, Jiacheng Huang +5

Agentic reinforcement learning (Agentic RL) has achieved strong progress in tasks with clear success signals. However, many real-world agent applications require user-conditioned b…

cs.CL2023

Joint Pre-training and Local Re-training: Transferable Representation Learning on Multi-source Knowledge Graphs

Zequn Sun, Jiacheng Huang, Jinghao Lin +3

In this paper, we present the ``joint pre-training and local re-training'' framework for learning and applying multi-source knowledge graph (KG) embeddings. We are motivated by the…

cs.LG2023★ 1 cited

What Makes Entities Similar? A Similarity Flooding Perspective for Multi-sourced Knowledge Graph Embeddings

Zequn Sun, Jiacheng Huang, Xiaozhou Xu +3

Joint representation learning over multi-sourced knowledge graphs (KGs) yields transferable and expressive embeddings that improve downstream tasks. Entity alignment (EA) is a crit…

cs.DB2023★ 1 cited

Deep Active Alignment of Knowledge Graph Entities and Schemata

Jiacheng Huang, Zequn Sun, Qijin Chen +3

Knowledge graphs (KGs) store rich facts about the real world. In this paper, we study KG alignment, which aims to find alignment between not only entities but also relations and cl…