EvoOntology: A Self-Evolving Ontology Layer for Data Agents

arXiv:2609.15779 · cs.AI, cs.CL, cs.DB · Submitted 2026-09-14 · Read on arXiv

cs.AI, cs.CL, cs.DB

Submitted: 2026-09-14

Updated: 2026-09-14

Comments: Code: https://github.com/ruc-datalab/EvoOntology

Code: https://github.com/ruc-datalab/EvoOntology

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

Terminology

• Ontology — 116× in this paper · explained in 2 episodes
• Benchmark — 17× in this paper · explained in 2 episodes
• Text-to-SQL — 15× in this paper · explained in 3 episodes
• Ablation — 5× in this paper · explained in 1 episode
• Grounding — 5× in this paper · explained in 3 episodes
• Accuracy — 4× in this paper · explained in 1 episode
• Adaptation — 4× in this paper · explained in 1 episode
• Trace — 3× in this paper · explained in 2 episodes
• Ablation study — 2× in this paper · explained in 1 episode
• Consistency — 2× in this paper · explained in 3 episodes
• Semantic Gap — 2× in this paper · explained in 2 episodes
• Verification — 2× in this paper · explained in 2 episodes
• Clustering — 1× in this paper · explained in 2 episodes
• Foundation Model — 1× in this paper · explained in 3 episodes
• Foundation Models — 1× in this paper · explained in 7 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Iterative Refinement — 1× in this paper · explained in 3 episodes
• Multi-agent Collaborative Framework — 1× in this paper · explained in 2 episodes
• RAG — 1× in this paper · explained in 3 episodes
• Reinforcement Learning — 1× in this paper · explained in 4 episodes
• Standardized Benchmarks — 1× in this paper · explained in 2 episodes

Sources

• E-SQL: Direct Schema Linking via Question Enrichment in Text-to-SQL
• RSL-SQL: Robust Schema Linking in Text-to-SQL Generation
• How to Prompt LLMs for Text-to-SQL: A Study in Zero-shot, Single-domain, and Cross-domain Settings
• DSPy: Compiling Declarative Language Model Calls into Self-Improving Pipelines
• PET-SQL: A Prompt-Enhanced Two-Round Refinement of Text-to-SQL with Cross-consistency
• Hunt Instead of Wait: Evaluating Deep Data Research on Large Language Models
• CHESS: Contextual Harnessing for Efficient SQL Synthesis
• Voyager: An Open-Ended Embodied Agent with Large Language Models
• Adapting the Interface, Not the Model: Runtime Harness Adaptation for Deterministic LLM Agents
• Data-Copilot: Bridging Billions of Data and Humans with Autonomous Workflow
• BASEN: Time-Domain Brain-Assisted Speech Enhancement Network with Convolutional Cross Attention in Multi-talker Conditions

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