Zobrazeno 1 - 10
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pro vyhledávání: '"Oved, Nadav"'
Autor:
Calderon, Nitay, Porat, Naveh, Ben-David, Eyal, Chapanin, Alexander, Gekhman, Zorik, Oved, Nadav, Shalumov, Vitaly, Reichart, Roi
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, the common practice of measuring DR might not be fully accurate. Cur
Externí odkaz:
http://arxiv.org/abs/2306.00168
Most works on modeling the conversation history in Conversational Question Answering (CQA) report a single main result on a common CQA benchmark. While existing models show impressive results on CQA leaderboards, it remains unclear whether they are r
Externí odkaz:
http://arxiv.org/abs/2206.14796
Natural Language Processing algorithms have made incredible progress, but they still struggle when applied to out-of-distribution examples. We address a challenging and underexplored version of this domain adaptation problem, where an algorithm is tr
Externí odkaz:
http://arxiv.org/abs/2102.12206
Understanding predictions made by deep neural networks is notoriously difficult, but also crucial to their dissemination. As all machine learning based methods, they are as good as their training data, and can also capture unwanted biases. While ther
Externí odkaz:
http://arxiv.org/abs/2005.13407
We present a Spades bidding algorithm that is superior to recreational human players and to publicly available bots. Like in Bridge, the game of Spades is composed of two independent phases, \textit{bidding} and \textit{playing}. This paper focuses o
Externí odkaz:
http://arxiv.org/abs/1912.11323
Sports competitions are widely researched in computer and social science, with the goal of understanding how players act under uncertainty. While there is an abundance of computational work on player metrics prediction based on past performance, very
Externí odkaz:
http://arxiv.org/abs/1910.11292
Akademický článek
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Existing research on Domain Robustness (DR) suffers from disparate setups, lack of evaluation task variety, and reliance on challenge sets. In this paper, we pose a fundamental question: What is the state of affairs of the DR challenge in the era of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6ff0490308185922815476432cf2906c
http://arxiv.org/abs/2306.00168
http://arxiv.org/abs/2306.00168
Autor:
Feder, Amir1 (AUTHOR) feder@campus.technion.ac.il, Oved, Nadav1 (AUTHOR) nadavo@campus.technion.ac.il, Shalit, Uri1 (AUTHOR) urishalit@technion.ac.il, Reichart, Roi1 (AUTHOR) roiri@technion.ac.il
Publikováno v:
Computational Linguistics. 2021, Vol. 47 Issue 2, p333-386. 54p.
Autor:
Oved, Nadav1 (AUTHOR) nadavo@campus.technion.ac.il, Feder, Amir1 (AUTHOR) feder@campus.technion.ac.il, Reichart, Roi1 (AUTHOR) roiri@ie.technion.ac.il
Publikováno v:
Computational Linguistics. Sep2020, Vol. 46 Issue 3, p667-712. 46p.