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cs.IR2025
Toward Efficient and Scalable Design of In-Memory Graph-Based Vector Search
Ilias Azizi, Karima Echihab, Themis Palpanas +1
Vector data is prevalent across business and scientific applications, and its popularity is growing with the proliferation of learned embeddings. Vector data collections often reac…
cs.LG2025
A Comparative Analysis of Influence Signals for Data Debugging
Nikolaos Myrtakis, Ioannis Tsamardinos, Vassilis Christophides
Improving the quality of training samples is crucial for improving the reliability and performance of ML models. In this paper, we conduct a comparative evaluation of influence-bas…