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cs.AI2026

Orchard: An Open-Source Agentic Modeling Framework

Baolin Peng, Wenlin Yao, Qianhui Wu +11

Agentic modeling aims to transform LLMs into autonomous agents capable of solving complex tasks through planning, reasoning, tool use, and multi-turn interaction with external envi…

cs.AI2026

STAR: Failure-Aware Markovian Routing for Multi-Agent Spatiotemporal Reasoning

Ruiyi Yang, Lihuan Li, Hao Xue +1

Compositional spatiotemporal reasoning often requires a system to invoke multiple heterogeneous specialists, such as geometric, temporal, topological, and trajectory agents. A cent…

cs.AI2026

TrajPrism: A Multi-Task Benchmark for Language-Grounded Urban Trajectory Understanding

Lihuan Li, Wilson Wongso, Baiyu Chen +6

Urban mobility is naturally expressed both as trajectories in space and as natural-language descriptions of travel intent, constraints, and preferences. However, prior work rarely…

cs.AI2026

MAGE: Multi-Agent Self-Evolution with Co-Evolutionary Knowledge Graphs

Ruiyi Yang, Zechen Li, Hao Xue +2

Self-evolving language-model agents must decide what to learn next and how to preserve what they have learned across iterations. Existing systems typically carry this cross-iterati…

cs.AI2025

Divide by Question, Conquer by Agent: SPLIT-RAG with Question-Driven Graph Partitioning

Ruiyi Yang, Hao Xue, Imran Razzak +3

Retrieval-Augmented Generation (RAG) systems empower large language models (LLMs) with external knowledge, yet struggle with efficiency-accuracy trade-offs when scaling to large kn…