96 citations · 104 across the 10 of their papers we have counts for
20 papers · 1 filter
"Covid vaccine is against Covid but Oxford vaccine is made at Oxford!" Semantic Interpretation of Proper Noun Compounds
Keshav Kolluru, Gabriel Stanovsky, Mausam
Proper noun compounds, e.g., "Covid vaccine", convey information in a succinct manner (a "Covid vaccine" is a "vaccine that immunizes against the Covid disease"). These are commonl…
A Computational Acquisition Model for Multimodal Word Categorization
Uri Berger, Gabriel Stanovsky, Omri Abend +1
Recent advances in self-supervised modeling of text and images open new opportunities for computational models of child language acquisition, which is believed to rely heavily on c…
On the Limitations of Dataset Balancing: The Lost Battle Against Spurious Correlations
Roy Schwartz, Gabriel Stanovsky
Recent work has shown that deep learning models in NLP are highly sensitive to low-level correlations between simple features and specific output labels, leading to overfitting and…
Data Efficient Masked Language Modeling for Vision and Language
Yonatan Bitton, Gabriel Stanovsky, Michael Elhadad +1
Masked language modeling (MLM) is one of the key sub-tasks in vision-language pretraining. In the cross-modal setting, tokens in the sentence are masked at random, and the model pr…
Realistic Evaluation Principles for Cross-document Coreference Resolution
Arie Cattan, Alon Eirew, Gabriel Stanovsky +2
We point out that common evaluation practices for cross-document coreference resolution have been unrealistically permissive in their assumed settings, yielding inflated results. W…
Cross-document Coreference Resolution over Predicted Mentions
Arie Cattan, Alon Eirew, Gabriel Stanovsky +2
Coreference resolution has been mostly investigated within a single document scope, showing impressive progress in recent years based on end-to-end models. However, the more challe…