LLMAR: A Tuning-Free Recommendation Framework for Sparse and Text-Rich Industrial Domains

arXiv:2604.16379 · cs.IR, cs.CL · Submitted 2026-03-25 · Read on arXiv

cs.IR, cs.CL

Submitted: 2026-03-25

Updated: 2026-09-10

Comments: Accepted at PILA '26: Workshop on Personal Intelligence in the Agentic AI Era, co-located with ACM SIGKDD KDD 2026, Jeju, Korea. Non-archival workshop; not included in the KDD 2026 proceedings. Workshop page: https://pila26-workshop.github.io/ 10 pages, 3 figures. Code: https://github.com/hishikawa-hitachi/kdd-pila-2026-submission-code

Code: https://github.com/hishikawa-hitachi/kdd-pila-2026-submission-code

Project page: https://pila26-workshop.github.io

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

Terminology

• Accuracy — 13× in this paper · explained in 1 episode
• Semantic Gap — 12× in this paper · explained in 2 episodes
• Hallucination — 8× in this paper · explained in 3 episodes
• Sparsity — 8× in this paper · explained in 4 episodes
• Verification — 6× in this paper · explained in 2 episodes
• Consistency — 5× in this paper · explained in 3 episodes
• Explainability — 5× in this paper · explained in 3 episodes
• Ablation — 4× in this paper · explained in 1 episode
• Ablation study — 4× in this paper · explained in 1 episode
• Benchmark — 4× in this paper · explained in 2 episodes
• Embeddings — 4× in this paper · explained in 2 episodes
• Fine-Tuning — 4× in this paper · explained in 5 episodes
• RAG — 4× in this paper · explained in 3 episodes
• Core — 3× in this paper · explained in 2 episodes
• Interpretability — 3× in this paper · explained in 15 episodes
• Large Language Models (LLMs) — 3× in this paper · explained in 6 episodes
• Robustness — 3× in this paper · explained in 5 episodes
• Alignment — 2× in this paper · explained in 1 episode
• Emotional Resonance — 2× in this paper · explained in 2 episodes
• Steering — 2× in this paper · explained in 2 episodes
• Adam — 1× in this paper · explained in 2 episodes
• Chain-of-Thought (CoT) — 1× in this paper · explained in 4 episodes
• Chain-of-Thought Prompting — 1× in this paper · explained in 2 episodes
• Clustering — 1× in this paper · explained in 2 episodes
• GNNs — 1× in this paper · explained in 2 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Generative AI — 1× in this paper · explained in 2 episodes
• Grounding — 1× in this paper · explained in 3 episodes
• Industrial Safety Risk — 1× in this paper
• Reciprocal Rank Fusion — 1× in this paper
• Redundancy — 1× in this paper · explained in 2 episodes
• Reinforcement Learning — 1× in this paper · explained in 4 episodes
• Retrieval-Augmented Generation — 1× in this paper
• Retrieval-Augmented Generation (RAG) — 1× in this paper · explained in 16 episodes
• Semantic Alignment — 1× in this paper · explained in 3 episodes
• Semantic Similarity — 1× in this paper · explained in 2 episodes
• Semantic Understanding — 1× in this paper · explained in 2 episodes
• Transformer — 1× in this paper · explained in 2 episodes

Sources

• Self-RAG: Learning to Retrieve, Generate, and Critique through Self-Reflection
• GPT4Rec: A Generative Framework for Personalized Recommendation and User Interests Interpretation
• Qwen3 Technical Report
• Zero-Shot Next-Item Recommendation using Large Pretrained Language Models
• Finetuned Language Models Are Zero-Shot Learners
• ReAct: Synergizing Reasoning and Acting in Language Models

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