Mind the Gap: A Dual Knowledge Graph Framework for Unified Multi-task User Intent Inference

arXiv:2608.06752 · cs.AI, cs.CL · Submitted 2026-08-07 · Read on arXiv

Tzu-Cheng Peng, Chien Chin Chen, Chih-Hao Ku, Yung-Chun Chang

National Taiwan University · National Taiwan University · University of North Texas · Taipei Medical University

cs.AI, cs.CL

Submitted: 2026-08-07

Updated: 2026-08-10

Comments: Published in the PACIS 2026 Proceedings as a Completed Research Paper. AIS eLibrary: https://aisel.aisnet.org/pacis2026/ai_ml/ai_ml/12/ 17 pages, 5 figures

Journal ref: Proceedings of the Pacific Asia Conference on Information Systems (PACIS 2026), Paper 12, 2026

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

Terminology

• Knowledge Graph — 21× in this paper · explained in 8 episodes
• RAG — 14× in this paper · explained in 3 episodes
• Core — 12× in this paper · explained in 2 episodes
• Large Language Model — 12× in this paper
• Ablation — 9× in this paper · explained in 1 episode
• Fine-Tuning — 9× in this paper · explained in 5 episodes
• Augmentation — 8× in this paper · explained in 2 episodes
• Grounding — 7× in this paper · explained in 3 episodes
• Knowledge graphs — 7× in this paper · explained in 2 episodes
• LLM-as-a-Judge — 7× in this paper · explained in 4 episodes
• Accuracy — 6× in this paper · explained in 1 episode
• Embeddings — 6× in this paper · explained in 2 episodes
• Semantic Alignment — 6× in this paper · explained in 6 episodes
• Transformer — 5× in this paper · explained in 2 episodes
• Ablation Studies — 4× in this paper · explained in 1 episode
• Ablation Study — 4× in this paper · explained in 3 episodes
• Consistency — 4× in this paper · explained in 3 episodes
• Graph Construction — 4× in this paper · explained in 3 episodes
• Semantic Gap — 4× in this paper · explained in 2 episodes
• Approximate Nearest Neighbor — 3× in this paper
• Benchmark — 3× in this paper · explained in 2 episodes
• Latent Dirichlet Allocation — 3× in this paper
• Ontology — 3× in this paper · explained in 2 episodes
• Robustness — 3× in this paper · explained in 6 episodes
• Hallucination — 2× in this paper · explained in 4 episodes
• Papers — 2× in this paper · explained in 3 episodes
• Parameter-Efficient Fine-Tuning — 2× in this paper · explained in 3 episodes
• Parameter-Efficient Fine-Tuning (PEFT) — 2× in this paper · explained in 5 episodes
• Personalization — 2× in this paper · explained in 2 episodes
• Retrieval-Augmented Generation — 2× in this paper
• Transformer Model — 2× in this paper · explained in 2 episodes
• Transformers — 2× in this paper · explained in 2 episodes
• Absorb — 1× in this paper · explained in 1 episode
• Attention Mechanism — 1× in this paper · explained in 3 episodes
• Coherence — 1× in this paper · explained in 2 episodes
• Commentary — 1× in this paper · explained in 2 episodes
• Explainability — 1× in this paper · explained in 4 episodes
• Feature Engineering — 1× in this paper · explained in 3 episodes
• Generalization — 1× in this paper · explained in 14 episodes
• Generalization Capabilities — 1× in this paper · explained in 2 episodes
• Generative Model — 1× in this paper · explained in 2 episodes
• Generative Models — 1× in this paper · explained in 3 episodes
• Generator — 1× in this paper · explained in 2 episodes
• Hybrid Approach — 1× in this paper · explained in 4 episodes
• Hyperparameters — 1× in this paper · explained in 2 episodes
• Interpretability — 1× in this paper · explained in 15 episodes
• Iterative Refinement — 1× in this paper · explained in 5 episodes
• LLM Integration — 1× in this paper · explained in 2 episodes
• Language Models (LLMs) — 1× in this paper · explained in 2 episodes
• Large Language Model (LLM) — 1× in this paper · explained in 3 episodes
• Large Language Models (LLMs) — 1× in this paper · explained in 9 episodes
• Lexical Diversity — 1× in this paper · explained in 2 episodes
• Long Short-Term Memory (LSTM) — 1× in this paper · explained in 2 episodes
• Multi-hop Reasoning — 1× in this paper · explained in 3 episodes
• Natural Language Understanding — 1× in this paper
• Representation Learning — 1× in this paper · explained in 3 episodes
• Retrieval-Augmented Generation (RAG) — 1× in this paper · explained in 21 episodes
• Semantic Correctness — 1× in this paper · explained in 2 episodes
• Semantic Similarity — 1× in this paper · explained in 2 episodes
• Topic Modeling — 1× in this paper · explained in 2 episodes
• Transformer Architecture — 1× in this paper · explained in 4 episodes
• Verification — 1× in this paper · explained in 2 episodes

Sources

• Intention Knowledge Graph Construction for User Intention Relation Modeling
• From Local to Global: A Graph RAG Approach to Query-Focused Summarization
• Retrieval-Augmented Generation for Large Language Models: A Survey
• The Llama 3 Herd of Models
• Mistral 7B
• Recurrent Neural Network for Text Classification with Multi-Task Learning

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