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Leshem Choshen
Leshem Choshen
MIT, IBM AI research
Zweryfikowany adres z mail.huji.ac.il - Strona główna
Tytuł
Cytowane przez
Cytowane przez
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Ties-merging: Resolving interference when merging models
P Yadav, D Tam, L Choshen, CA Raffel, M Bansal
Advances in Neural Information Processing Systems 36, 2024
260*2024
Active learning for BERT: an empirical study
LE Dor, A Halfon, A Gera, E Shnarch, L Dankin, L Choshen, M Danilevsky, ...
Proceedings of the 2020 conference on empirical methods in natural language …, 2020
2542020
An autonomous debating system
N Slonim, Y Bilu, C Alzate, R Bar-Haim, B Bogin, F Bonin, L Choshen, ...
Nature 591 (7850), 379-384, 2021
2482021
: Evaluating Factual Consistency in Knowledge-Grounded Dialogues via Question Generation and Question Answering
O Honovich, L Choshen, R Aharoni, E Neeman, I Szpektor, O Abend
arXiv preprint arXiv:2104.08202, 2021
1892021
Findings of the BabyLM Challenge: Sample-efficient pretraining on developmentally plausible corpora
A Warstadt, A Mueller, L Choshen, E Wilcox, C Zhuang, J Ciro, ...
Proceedings of the BabyLM Challenge at the 27th Conference on Computational …, 2023
139*2023
On the weaknesses of reinforcement learning for neural machine translation
L Choshen, L Fox, Z Aizenbud, O Abend
arXiv preprint arXiv:1907.01752, 2019
942019
Are you convinced? choosing the more convincing evidence with a Siamese network
M Gleize, E Shnarch, L Choshen, L Dankin, G Moshkowich, R Aharonov, ...
arXiv preprint arXiv:1907.08971, 2019
902019
Will it blend? blending weak and strong labeled data in a neural network for argumentation mining
E Shnarch, C Alzate, L Dankin, M Gleize, Y Hou, L Choshen, R Aharonov, ...
Proceedings of the 56th Annual Meeting of the Association for Computational …, 2018
842018
Corpus wide argument mining—a working solution
L Ein-Dor, E Shnarch, L Dankin, A Halfon, B Sznajder, A Gera, C Alzate, ...
Proceedings of the AAAI Conference on Artificial Intelligence 34 (05), 7683-7691, 2020
812020
Dora the explorer: Directed outreaching reinforcement action-selection
L Choshen, L Fox, Y Loewenstein
arXiv preprint arXiv:1804.04012, 2018
762018
Fusing finetuned models for better pretraining
L Choshen, E Venezian, N Slonim, Y Katz
arXiv preprint arXiv:2204.03044, 2022
662022
Let’s agree to agree: Neural networks share classification order on real datasets
G Hacohen, L Choshen, D Weinshall
International Conference on Machine Learning, 3950-3960, 2020
602020
Cold fusion: Collaborative descent for distributed multitask finetuning
S Don-Yehiya, E Venezian, C Raffel, N Slonim, Y Katz, L Choshen
arXiv preprint arXiv:2212.01378, 2022
562022
Disentqa: Disentangling parametric and contextual knowledge with counterfactual question answering
E Neeman, R Aharoni, O Honovich, L Choshen, I Szpektor, O Abend
arXiv preprint arXiv:2211.05655, 2022
552022
Knowledge is a region in weight space for fine-tuned language models
A Gueta, E Venezian, C Raffel, N Slonim, Y Katz, L Choshen
arXiv preprint arXiv:2302.04863, 2023
472023
Jump to Conclusions: Short-Cutting Transformers With Linear Transformations
A Yom Din, T Karidi, L Choshen, M Geva
arXiv e-prints, arXiv: 2303.09435, 2023
45*2023
Learning to combine grammatical error corrections
Y Kantor, Y Katz, L Choshen, E Cohen-Karlik, N Liberman, A Toledo, ...
arXiv preprint arXiv:1906.03897, 2019
442019
SemEval-2019 task 1: Cross-lingual semantic parsing with UCCA
D Hershcovich, Z Aizenbud, L Choshen, E Sulem, A Rappoport, O Abend
arXiv preprint arXiv:1903.02953, 2019
432019
The grammar-learning trajectories of neural language models
L Choshen, G Hacohen, D Weinshall, O Abend
arXiv preprint arXiv:2109.06096, 2021
412021
Inherent Biases in Reference based Evaluation for Grammatical Error Correction and Text Simplification
L Choshen, O Abend
Proceedings of the 56th Annual Meeting of the Association for Computational …, 2018
402018
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