Generalization in large language models (LLMs) is the ability to produce consistent and semantically stable outputs when the same input is expressed in different ways. Existing work typically evaluates generalization through aggregate accuracy on a single prompt format, task, or set of variations, which conflates robus...
Nagham Omar, Mahmoud Jabarin, M. Rozenshteĭn et al.· 0 citations
MIST, the Misleading-Image Stress Test: 200 English sentences, each built around a phrase readable either figuratively or literally and shown with an aligned image depicting its reading, a misleading image depicting the opposite, or no image at all is introduced.
Nagham Omar, Mahmoud Jabarin, Kinan Ibraheem et al.· 0 citations
Training strategy, namely whether to retrain from scratch or fine-tune from the previous checkpoint, is an overlooked decision variable in active learning. We show that this choice has exploitable structure: retraining is most useful in early rounds, when each batch can substantially reshape the labeled distribution, w...
Nagham Omar, M. Rozenshteĭn, Evgeny Mishlyakov et al.· 0 citations
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