Hypergraph as Language

arXiv:2605.21858 · cs.CL · Submitted 2026-08-15 · Read on arXiv

Mengqi Lei, Guohuan Xie, Shihui Ying, Shaoyi Du, Jun-Hai Yong, Chuan Shi, Ling Tian, Siqi Li, Yue Gao

cs.CL

Submitted: 2026-08-15

Updated: 2026-08-18

Code: https://github.com/Mengqi-Lei/Hypergraph-as-Language

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Hypergraph — 256× in this paper · explained in 2 episodes
• Alignment — 33× in this paper · explained in 1 episode
• Benchmark — 11× in this paper · explained in 2 episodes
• Core — 10× in this paper · explained in 2 episodes
• Generalization — 8× in this paper · explained in 13 episodes
• Accuracy — 7× in this paper · explained in 1 episode
• Hypergraph Incidence Projector — 6× in this paper
• Aggregation — 5× in this paper · explained in 1 episode
• Ablation — 4× in this paper · explained in 1 episode
• Adaptation — 4× in this paper · explained in 1 episode
• Decoupling — 4× in this paper · explained in 2 episodes
• Embeddings — 4× in this paper · explained in 2 episodes
• Foundation Model — 4× in this paper · explained in 3 episodes
• Hypergraph Incidence Detail Template — 4× in this paper
• RAG — 4× in this paper · explained in 3 episodes
• Ablation study — 3× in this paper · explained in 1 episode
• Consistency — 3× in this paper · explained in 3 episodes
• Fine-Tuning — 3× in this paper · explained in 5 episodes
• Foundation Models — 3× in this paper · explained in 7 episodes
• Instruction Tuning — 3× in this paper · explained in 2 episodes
• Large Language Models (LLMs) — 3× in this paper · explained in 6 episodes
• Zero-Shot Transfer — 3× in this paper · explained in 4 episodes
• Alignment Methods — 2× in this paper · explained in 1 episode
• In-Context Learning — 2× in this paper · explained in 4 episodes
• Zero-Shot Generalization — 2× in this paper · explained in 5 episodes
• Adam — 1× in this paper · explained in 2 episodes
• Adaptive Sampling — 1× in this paper · explained in 1 episode
• Attention Mechanism — 1× in this paper · explained in 3 episodes
• Clustering — 1× in this paper · explained in 2 episodes
• Hallucination — 1× in this paper · explained in 3 episodes
• Heterogeneous Graph — 1× in this paper · explained in 2 episodes
• Representation Learning — 1× in this paper · explained in 2 episodes
• Retrieval-Augmented Generation (RAG) — 1× in this paper · explained in 16 episodes
• Tokenization — 1× in this paper · explained in 2 episodes

Sources

• Finetuned Language Models Are Zero-Shot Learners
• A Survey of Large Language Models
• Large Language Models and Knowledge Graphs: Opportunities and Challenges
• A Survey of Graph Meets Large Language Model: Progress and Future Directions
• CodeGraph: Enhancing Graph Reasoning of LLMs with Code
• LLM as GNN: Graph Vocabulary Learning for Text-Attributed Graph Foundation Models
• LLM-Guided Multi-View Hypergraph Learning for Human-Centric Explainable Recommendation
• Multi-Modal Hypergraph Enhanced LLM Learning for Recommendation
• Modeling Hypergraph Using Large Language Models
• Llama 2: Open Foundation and Fine-Tuned Chat Models
• The Llama 3 Herd of Models
• Qwen3 Technical Report
• SimTeG: A Frustratingly Simple Approach Improves Textual Graph Learning
• Qwen3 Embedding: Advancing Text Embedding and Reranking Through Foundation Models
• DHG-Bench: A Comprehensive Benchmark for Deep Hypergraph Learning

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