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20162024
most citedSERRANT: a syntactic classifier for English Grammatical Error Types

8 citations · 21 across the 9 of their papers we have counts for

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cs.CL20244 cited

Jamba-1.5: Hybrid Transformer-Mamba Models at Scale

Jamba Team, Barak Lenz, Alan Arazi +58

We present Jamba-1.5, new instruction-tuned large language models based on our Jamba architecture. Jamba is a hybrid Transformer-Mamba mixture of experts architecture, providing hi…

cs.CL20241 cited

A Language-agnostic Model of Child Language Acquisition

Louis Mahon, Omri Abend, Uri Berger +3

This work reimplements a recent semantic bootstrapping child-language acquisition model, which was originally designed for English, and trains it to learn a new language: Hebrew. T…

cs.CL2024

Beneath the Surface of Consistency: Exploring Cross-lingual Knowledge Representation Sharing in LLMs

Maxim Ifergan, Leshem Choshen, Roee Aharoni +2

The veracity of a factoid is largely independent of the language it is written in. However, language models are inconsistent in their ability to answer the same factual question ac…

cs.CL2024

Assessing the Role of Lexical Semantics in Cross-lingual Transfer through Controlled Manipulations

Roy Ilani, Taelin Karidi, Omri Abend

While cross-linguistic model transfer is effective in many settings, there is still limited understanding of the conditions under which it works. In this paper, we focus on assessi…

cs.CL2023

Improving Cross-Lingual Transfer through Subtree-Aware Word Reordering

Ofir Arviv, Dmitry Nikolaev, Taelin Karidi +1

Despite the impressive growth of the abilities of multilingual language models, such as XLM-R and mT5, it has been shown that they still face difficulties when tackling typological…

cs.CL2023

Evaluating and Improving the Coreference Capabilities of Machine Translation Models

Asaf Yehudai, Arie Cattan, Omri Abend +1

Machine translation (MT) requires a wide range of linguistic capabilities, which current end-to-end models are expected to learn implicitly by observing aligned sentences in biling…