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📝 ICV and ontology matchers docs
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HamedBabaei committed Dec 8, 2024
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1 change: 1 addition & 0 deletions docs/source/index.rst
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Expand Up @@ -53,6 +53,7 @@ OntoAligner Documentation

package_reference/base
package_reference/ontology
package_reference/ontolog_matchers
package_reference/encoder
package_reference/postprocess
package_reference/utils
94 changes: 94 additions & 0 deletions docs/source/package_reference/ontolog_matchers.rst
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Ontology Matchers
====================



Lightweight
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.. automodule:: ontoaligner.ontology_matchers.lightweight
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Lightweight Models
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.. automodule:: ontoaligner.ontology_matchers.lightweight.models
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Retrieval
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.. automodule:: ontoaligner.ontology_matchers.retrieval.retrieval
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Retrieval Models
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.. automodule:: ontoaligner.ontology_matchers.retrieval.models
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LLM
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.. automodule:: ontoaligner.ontology_matchers.llm.llm
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LLM Models
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.. automodule:: ontoaligner.ontology_matchers.llm.models
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RAG
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.. automodule:: ontoaligner.ontology_matchers.rag.rag
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RAG Models
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.. automodule:: ontoaligner.ontology_matchers.rag.models
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FewShotRAG
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.. automodule:: ontoaligner.ontology_matchers.fewshot.fewshot
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FewShotRAG Models
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.. automodule:: ontoaligner.ontology_matchers.fewshot.models
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ICV RAG
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.. automodule:: ontoaligner.ontology_matchers.icv.icv
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ICVRAG Models
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.. automodule:: ontoaligner.ontology_matchers.rag.models
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4 changes: 2 additions & 2 deletions docs/source/tutorials/rag.rst
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In-Context Vectors RAG
==================================
This RAG variant performs ontology matching using ``ConceptRAGEncoder`` only. The In-Contect Vectors introduced by `[1]<https://github.com/shengliu66/ICV>`_ tackle in-context learning as in-context vectors (ICV). We used LLMs in this perspective in the RAG module. The workflow is the same as RAG or FewShot RAG with the following differences:
This RAG variant performs ontology matching using ``ConceptRAGEncoder`` only. The In-Contect Vectors introduced by [1](https://github.com/shengliu66/ICV) tackle in-context learning as in-context vectors (ICV). We used LLMs in this perspective in the RAG module. The workflow is the same as RAG or FewShot RAG with the following differences:


1. Incorporate the ``ConceptRAGEncoder`` and also provide reference (or examples to build up the ICV vectors).
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model.load(llm_path="tiiuae/falcon-7b", ir_path="all-MiniLM-L6-v2")
[1] Liu, S., Ye, H., Xing, L., & Zou, J. (2023). `In-context vectors: Making in context learning more effective and controllable through latent space steering<https://arxiv.org/abs/2311.06668>`_. arXiv preprint arXiv:2311.06668.
[1] Liu, S., Ye, H., Xing, L., & Zou, J. (2023). [In-context vectors: Making in context learning more effective and controllable through latent space steering](https://arxiv.org/abs/2311.06668>). arXiv preprint arXiv:2311.06668.

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