38 citations · 40 across the 3 of their papers we have counts for
3 papers · 1 filter
Inside-Out: Hidden Factual Knowledge in LLMs
Zorik Gekhman, Eyal Ben David, Hadas Orgad +5
This work presents a framework for assessing whether large language models (LLMs) encode more factual knowledge in their parameters than what they express in their outputs. While a…
Measuring the Robustness of NLP Models to Domain Shifts
Nitay Calderon, Naveh Porat, Eyal Ben-David +5
Existing research on Domain Robustness (DR) suffers from disparate setups, limited task variety, and scarce research on recent capabilities such as in-context learning. Furthermore…
SimLex-999: Evaluating Semantic Models with (Genuine) Similarity Estimation
Felix Hill, Roi Reichart, Anna Korhonen
We present SimLex-999, a gold standard resource for evaluating distributional semantic models that improves on existing resources in several important ways. First, in contrast to g…