74 citations · 87 across the 14 of their papers we have counts for
7 papers · 1 filter
SpecForge: Recursive Self-Improvement for Coding Agents via Behavioral Specifications
Yutong Cheng, Haifeng Chen, Peng Gao +1
Coding agents based on frozen language models can improve their performance by refining the external context they rely on, without updating model weights. We study recursive self-i…
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…
Pay for the Fault, Not the Flow: Label-Free In-Flow Multi-Agent Workflow Optimization
Xuehang Guo, Haoyu Wang, Shengyu Chen +4
Large language models (LLMs) increasingly construct multi-agent workflows that decompose a complex task and assign specialist agents from a pool. However, building such a workflow…
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…
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…
SkillRL: Evolving Agents via Recursive Skill-Augmented Reinforcement Learning
Peng Xia, Jianwen Chen, Hanyang Wang +10
Large Language Model (LLM) agents have shown stunning results in complex tasks, yet they often operate in isolation, failing to learn from past experiences. Existing memory-based m…
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…