Measuring the Robustness of NLP Models to Domain Shifts

2 code implementations • 31 May 2023 • Nitay Calderon, Naveh Porat, Eyal Ben-David, Alexander Chapanin, Zorik Gekhman, Nadav Oved, Vitaly Shalumov, Roi Reichart

We then conducted a comprehensive large-scale DR study involving over 14, 000 domain shifts across 21 fine-tuned models and few-shot LLMs.

Few-Shot Learning In-Context Learning +2

HeRo: RoBERTa and Longformer Hebrew Language Models

no code implementations • 18 Apr 2023 • Vitaly Shalumov, Harel Haskey

In this paper, we fill in an existing gap in resources available to the Hebrew NLP community by providing it with the largest so far pre-train dataset HeDC4, a state-of-the-art pre-trained language model HeRo for standard length inputs and an efficient transformer LongHeRo for long input sequences.

Document Classification Language Modelling +4

Transformer Based Geocoding

no code implementations • 2 Jan 2023 • Yuval Solaz, Vitaly Shalumov

In this paper, we formulate the problem of predicting a geolocation from free text as a sequence-to-sequence problem.

Decoder

Deep Learning based Estimation of Weaving Target Maneuvers

no code implementations • 13 Jun 2018 • Vitaly Shalumov, Itzik Klein

The objective of this paper is to examine the potential of using neural networks in target tracking applications.