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CollabEval slashes evaluation uncertainty, achieving more accurate model assessments with less data by exploiting historical performance correlations.
Language models encode knowledge in a task-specific manner, leading to inconsistent retrieval of facts across different tasks.
Graph transformers can be fundamentally limited by their tokenization strategy, as some tokenizations provably preclude efficient learning of structural representations realizable with other tokenizations.
