arXiv AI
Call Neighbours Yourself: Graph Walks with Destination-Conditioned On-Policy Self-Distillation
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CoEvoT: Co-Evolving Chain-of-Thought Prompting for Graph-LLM Reasoning
arXiv:2607. 14114v1 Announce Type: cross Abstract: Graph learning under distribution shift presents a persistent challenge, where models adapt to new graphs with limited or even no supervision.
arXiv AI
Aug 19
G-ReAct: Graph-Guided Deep Search via Structure-State Co-Evolution
G-ReAct is a reasoning framework that frames deep search as state evolution over a fixed-topology query graph, enabling explicit tracking of search progress and constraint preservation. It generates high-quality trajectories for fine-tuning and provides structured guidance during inference without extra fine-tuning. Experiments show that with only 1.9K generated trajectories, a Qwen3 model achieves strong accuracy on BrowseComp-ZH and XBench, outperforming larger open-source baselines, and consistently improves existing LLMs on deep-search tasks.
arXiv AI
Aug 6
Topology-Aware Reasoning over Incomplete Knowledge Graph with Graph-Based Soft Prompting
arXiv:2604. 12503v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have shown remarkable capabilities across various tasks but remain prone to hallucinations in knowledge-intensive scenarios.
arXiv Machine Learning
Jul 1
TAG-DLM: Diffusion Language Models for Text-Attributed Graph Learning
arXiv:2606. 31166v1 Announce Type: cross Abstract: Text-attributed graphs (TAGs), where each node carries a natural language description, require models to jointly reason over text and graph topology.
arXiv Machine Learning
Aug 4
Agentic Graph Token Reasoning
arXiv:2608. 00542v1 Announce Type: new Abstract: Graphs model relational data throughout science and industry, from citation networks to product co-purchase graphs.
arXiv AI
Oct 7
Foresight-over-Graph: Reasoning Beyond Local Horizons for Knowledge Base Question Answering
arXiv:2610.08388v1 Announce Type: cross Abstract: Large language models (LLMs) have demonstrated strong capabilities in question answering, yet they still frequently suffer from hallucinations on kno...