AnalogRetriever: Learning Cross-Modal Representations for Analog Circuit Retrieval
📰 ArXiv cs.AI
Learn how AnalogRetriever enables cross-modal retrieval for analog circuit design using a unified tri-modal framework
Action Steps
- Build a tri-modal retrieval framework using AnalogRetriever to capture cross-modal semantic relationships
- Run experiments to evaluate the effectiveness of AnalogRetriever in retrieving analog circuits across different modalities
- Configure the framework to learn cross-modal representations from SPICE netlists, schematics, and functional descriptions
- Test the retrieval performance of AnalogRetriever using a dataset of analog circuits
- Apply AnalogRetriever to real-world analog circuit design tasks to improve search efficiency and reuse of existing IP
Who Needs to Know This
This benefits electronics engineers and researchers working on analog circuit design, as it allows for more efficient searching and reusing of existing intellectual property across different representations
Key Insight
💡 AnalogRetriever enables cross-modal retrieval for analog circuit design by learning unified representations across different modalities
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Key Takeaways
Learn how AnalogRetriever enables cross-modal retrieval for analog circuit design using a unified tri-modal framework
Full Article
Title: AnalogRetriever: Learning Cross-Modal Representations for Analog Circuit Retrieval
Abstract:
arXiv:2604.23195v1 Announce Type: cross Abstract: Analog circuit design relies heavily on reusing existing intellectual property (IP), yet searching across heterogeneous representations such as SPICE netlists, schematics, and functional descriptions remains challenging. Existing methods are largely limited to exact matching within a single modality, failing to capture cross-modal semantic relationships. To bridge this gap, we present AnalogRetriever, a unified tri-modal retrieval framework for a
Abstract:
arXiv:2604.23195v1 Announce Type: cross Abstract: Analog circuit design relies heavily on reusing existing intellectual property (IP), yet searching across heterogeneous representations such as SPICE netlists, schematics, and functional descriptions remains challenging. Existing methods are largely limited to exact matching within a single modality, failing to capture cross-modal semantic relationships. To bridge this gap, we present AnalogRetriever, a unified tri-modal retrieval framework for a
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