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2020 – today
- 2024
[c6]Elron Bandel, Yotam Perlitz, Elad Venezian, Roni Friedman, Ofir Arviv, Matan Orbach, Shachar Don-Yehiya, Dafna Sheinwald, Ariel Gera, Leshem Choshen, Michal Shmueli-Scheuer, Yoav Katz:
Unitxt: Flexible, Shareable and Reusable Data Preparation and Evaluation for Generative AI. NAACL (Demonstrations) 2024: 207-215- [c5]Yotam Perlitz, Elron Bandel, Ariel Gera, Ofir Arviv, Liat Ein-Dor, Eyal Shnarch, Noam Slonim, Michal Shmueli-Scheuer, Leshem Choshen:
Efficient Benchmarking (of Language Models). NAACL-HLT 2024: 2519-2536 - [i10]Elron Bandel, Yotam Perlitz, Elad Venezian, Roni Friedman-Melamed, Ofir Arviv, Matan Orbach, Shachar Don-Yehiya, Dafna Sheinwald, Ariel Gera, Leshem Choshen, Michal Shmueli-Scheuer, Yoav Katz:
Unitxt: Flexible, Shareable and Reusable Data Preparation and Evaluation for Generative AI. CoRR abs/2401.14019 (2024) - [i9]Andreas Waldis, Yotam Perlitz, Leshem Choshen, Yufang Hou, Iryna Gurevych:
Holmes: Benchmark the Linguistic Competence of Language Models. CoRR abs/2404.18923 (2024) - [i8]Yotam Perlitz, Ariel Gera, Ofir Arviv, Asaf Yehudai, Elron Bandel, Eyal Shnarch, Michal Shmueli-Scheuer, Leshem Choshen:
Benchmark Agreement Testing Done Right: A Guide for LLM Benchmark Evaluation. CoRR abs/2407.13696 (2024) - [i7]Ora Nova Fandina, Leshem Choshen, Eitan Farchi, George Kour, Yotam Perlitz, Orna Raz:
Can You Trust Your Metric? Automatic Concatenation-Based Tests for Metric Validity. CoRR abs/2408.12259 (2024) - 2023
- [c4]Yotam Perlitz, Dafna Sheinwald, Noam Slonim, Michal Shmueli-Scheuer:
nBIIG: A Neural BI Insights Generation System for Table Reporting. AAAI 2023: 16470-16472 - [c3]Yotam Perlitz, Ariel Gera, Michal Shmueli-Scheuer, Dafna Sheinwald, Noam Slonim, Liat Ein-Dor:
Active Learning for Natural Language Generation. EMNLP 2023: 9862-9877 - [i6]Yotam Perlitz, Ariel Gera, Michal Shmueli-Scheuer, Dafna Sheinwald, Noam Slonim, Liat Ein-Dor:
Active Learning for Natural Language Generation. CoRR abs/2305.15040 (2023) - [i5]Yotam Perlitz, Elron Bandel, Ariel Gera, Ofir Arviv, Liat Ein-Dor, Eyal Shnarch, Noam Slonim, Michal Shmueli-Scheuer, Leshem Choshen:
Efficient Benchmarking (of Language Models). CoRR abs/2308.11696 (2023) - 2022
- [c2]Ariel Gera, Alon Halfon, Eyal Shnarch, Yotam Perlitz, Liat Ein-Dor, Noam Slonim:
Zero-Shot Text Classification with Self-Training. EMNLP 2022: 1107-1119 - [i4]Yotam Perlitz, Liat Ein-Dor, Dafna Sheinwald, Noam Slonim, Michal Shmueli-Scheuer:
Diversity Enhanced Table-to-Text Generation via Type Control. CoRR abs/2205.10938 (2022) - [i3]Ariel Gera, Alon Halfon, Eyal Shnarch, Yotam Perlitz, Liat Ein-Dor, Noam Slonim:
Zero-Shot Text Classification with Self-Training. CoRR abs/2210.17541 (2022) - [i2]Yotam Perlitz, Dafna Sheinwald, Noam Slonim, Michal Shmueli-Scheuer:
nBIIG: A Neural BI Insights Generation System for Table Reporting. CoRR abs/2211.04417 (2022) - 2021
- [c1]Alexandra Dana, Maor Shutman, Yotam Perlitz, Ran Vitek, Tomer Peleg, Roy J. Jevnisek:
You Better Look Twice: a new perspective for designing accurate detectors with reduced computations. BMVC 2021: 257 - [i1]Alexandra Dana, Maor Shutman, Yotam Perlitz, Ran Vitek, Tomer Peleg, Roy J. Jevnisek:
You Better Look Twice: a new perspective for designing accurate detectors with reduced computations. CoRR abs/2107.10050 (2021)
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