1 citations · 1 across the 18 of their papers we have counts for
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Hopfield-Fenchel-Young Networks: A Unified Framework for Associative Memory Retrieval
Saul Santos, Vlad Niculae, Daniel McNamee +1
Associative memory models, such as Hopfield networks and their modern variants, have garnered renewed interest due to advancements in memory capacity and connections with self-atte…
kNN For Whisper And Its Effect On Bias And Speaker Adaptation
Maya K. Nachesa, Vlad Niculae
Speech recognition performance varies by language, domain, and speaker characteristics such as accent, but fine-tuning a model on any of these categories may lead to catastrophic f…
Context-Aware or Context-Insensitive? Assessing LLMs' Performance in Document-Level Translation
Wafaa Mohammed, Vlad Niculae
Large language models (LLMs) are increasingly strong contenders in machine translation. In this work, we focus on document-level translation, where some words cannot be translated…
On the Low-Rank Parametrization of Reward Models for Controlled Language Generation
Sergey Troshin, Vlad Niculae, Antske Fokkens
Language models trained on large amounts of data are known to produce inappropriate content in some cases and require careful tuning to be used in the real world. We revisit an eff…
On Measuring Context Utilization in Document-Level MT Systems
Wafaa Mohammed, Vlad Niculae
Document-level translation models are usually evaluated using general metrics such as BLEU, which are not informative about the benefits of context. Current work on context-aware e…
Sparse and Structured Hopfield Networks
Saul Santos, Vlad Niculae, Daniel McNamee +1
Modern Hopfield networks have enjoyed recent interest due to their connection to attention in transformers. Our paper provides a unified framework for sparse Hopfield networks by e…