most citedPRoH: Dynamic Planning and Reasoning over Knowledge Hypergraphs for Retrieval-Augmented Generation

1 citations · 1 across the 8 of their papers we have counts for

collaborators

10 papers

cs.CL2026

SkillZip: Contract-Preserving Graph Compression for Scalable Agent Skill Libraries

Xingyu Tan, Xiaoyang Wang, Qing Liu +4

Large Language Models (LLMs) increasingly act as agents whose procedural knowledge is stored in reusable skill packages and loaded at inference time. As skill libraries grow, a cen…

cs.CL2026

Interpretable Column Annotation with LLM-Symbolized Decision Process Materialization

Mengqi Wang, Jianwei Wang, Qing Liu +5

Column annotation (CA), including column type annotation (CTA) and column property annotation (CPA), aims to identify the meanings of table columns and the semantic relationships a…

cs.CL2026

Weaving Multi-Source Evidence for Biomedical Reasoning: The BioMedHop Benchmark and BioWeave Framework

Xingyu Tan, Shiyuan Liu, Xiaoyang Wang +5

Biomedical question answering (QA) increasingly requires reasoning over interacting entities, where supporting evidence is scattered across biomedical knowledge graphs, literature…

cs.CL2026

PrivGemo: Privacy-Preserving Dual-Tower Graph Retrieval for Empowering LLM Reasoning with Memory Augmentation

Xingyu Tan, Xiaoyang Wang, Qing Liu +4

Knowledge graphs (KGs) provide structured evidence that can ground large language model (LLM) reasoning for knowledge-intensive question answering. However, many practical KGs are…

cs.CL2025

Ensembling LLM-Induced Decision Trees for Explainable and Robust Error Detection

Mengqi Wang, Jianwei Wang, Qing Liu +5

Error detection (ED), which aims to identify incorrect or inconsistent cell values in tabular data, is important for ensuring data quality. Recent state-of-the-art ED methods lever…

cs.CL2025

MemoTime: Memory-Augmented Temporal Knowledge Graph Enhanced Large Language Model Reasoning

Xingyu Tan, Xiaoyang Wang, Qing Liu +4

Large Language Models (LLMs) have achieved impressive reasoning abilities, but struggle with temporal understanding, especially when questions involve multiple entities, compound o…

cs.CL2025★ 1 cited

PRoH: Dynamic Planning and Reasoning over Knowledge Hypergraphs for Retrieval-Augmented Generation

Xiangjun Zai, Xingyu Tan, Xiaoyang Wang +3

Knowledge Hypergraphs (KHs) have recently emerged as a knowledge representation for retrieval-augmented generation (RAG), offering a paradigm to model multi-entity relations into a…

cs.AI2025

MMAPG: A Training-Free Framework for Multimodal Multi-hop Question Answering via Adaptive Planning Graphs

Yiheng Hu, Xiaoyang Wang, Qing Liu +4

Multimodal Multi-hop question answering requires integrating information from diverse sources, such as images and texts, to derive answers. Existing methods typically rely on seque…

cs.CL2025

LLM-based HSE Compliance Assessment: Benchmark, Performance, and Advancements

Jianwei Wang, Mengqi Wang, Yinsi Zhou +5

Health, Safety, and Environment (HSE) compliance assessment demands dynamic real-time decision-making under complicated regulations and complex human-machine-environment interactio…

cs.CL2025

HydraRAG: Structured Cross-Source Enhanced Large Language Model Reasoning

Xingyu Tan, Xiaoyang Wang, Qing Liu +4

Retrieval-augmented generation (RAG) enhances large language models (LLMs) by incorporating external knowledge. Current hybrid RAG system retrieves evidence from both knowledge gra…