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20232026
most citedInterpretable Imitation Learning with Dynamic Causal Relations

3 citations · 17 across the 20 of their papers we have counts for

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6 papers · 1 filter

cs.CV2026

Knossos and Ariadne: Benchmarking and Learning Complete Diagram Topology Extraction with Vision-Language Models

Bangwei Guo, Xujiang Zhao, Shengyu Chen +6

Structural diagrams are widely used to represent complex systems and relational information across scientific, engineering, procedural, and spatial domains. Recent vision-language…

cs.CV2026

TopoAgent: A Structure-Aware Perception-to-Reasoning Framework for Diagram-to-Graph Topology Extraction with Large Vision-Language Models

Bangwei Guo, Xujiang Zhao, Yanchi Liu +7

Diagram-to-graph topology extraction aims to extract a graph of entities and their connections from a structural diagram. This task remains challenging for current vision-language…

cs.IR2026

HARP: Hierarchical Adaptive Ranking with Preference-Adaptive Fusion for Query-Based CVE Prioritization

Haochen Liu, Zhengzhang Chen, Haoyu Wang +3

Vulnerability prioritization is inherently preference dependent, since the same CVE can receive different remediation priority under different operational preference scenarios. Exi…

cs.AI2026

MIITA: Memory-Induced Inference-Time Adaptation for Continual Learning with Small Language Models

Dong Li, Yanchi Liu, Xujiang Zhao +6

Continual learning (CL) is essential for small language models (SLMs) to adapt to evolving real-world needs in resource-constrained deployments. However, directly updating their li…

cs.AI2026

Coupled Hierarchical Search over Topology and Execution for Agentic Workflow Synthesis

Dong Li, Yanchi Liu, Xujiang Zhao +6

Although structured workflows empower Large Language Models (LLMs) to tackle complex problems, automating their creation is severely hindered by a vast combinatorial search space,…

cs.AI2026

Multi-Agent Procedural Graph Extraction with Structural and Logical Refinement

Wangyang Ying, Yanchi Liu, Xujiang Zhao +5

Automatically extracting workflows as procedural graphs from natural language is promising yet underexplored, demanding both structural validity and logical alignment. While recent…