http://nlp.unibo.it/tag/interlocking/InterlockingHugo Blox Builder (https://hugoblox.com)en-usMon, 02 Mar 2026 00:00:00 +0000http://nlp.unibo.it/media/icon_hu_7613a4a452ac7087.pnghttp://nlp.unibo.it/tag/interlocking/http://nlp.unibo.it/proposals_interpretability/mixture/Mon, 02 Mar 2026 00:00:00 +0000http://nlp.unibo.it/proposals_interpretability/mixture/<p><strong>Description:</strong><br> Mixture of Experts (MoE) is a technique whereby several models are trained on the same data, each specializing in a certain subset. MoE have been shown to be successful in a variety of applications and their original formulation dates back early 2000s. The idea is to understand whether we can develop a MoE model for selective rationalization to address interlocking.</p> <p><strong>Contact:</strong> <a href="mailto:federico.ruggeri6@unibo.it">Federico Ruggeri</a></p> <p><strong>References:</strong></p> <p><strong>A Survey on Mixture of Experts in Large Language Models</strong><br> W. Cai, J. Jiang, F. Wang, J. Tang, S. Kim and J. Huang.<br> In IEEE Transactions on Knowledge and Data Engineering, vol. 37, no. 7, pp. 3896-3915, July 2025.<br> <a href="https://doi.org/10.1109/TKDE.2025.3554028" target="_blank" rel="noopener">DOI</a></p>