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Leshem Choshen
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2020 – today
- 2024
- [c44]Shir Ashury-Tahan, Ariel Gera, Benjamin Sznajder, Leshem Choshen, Liat Ein-Dor, Eyal Shnarch:
Label-Efficient Model Selection for Text Generation. ACL (1) 2024: 8384-8402 - [c43]Afra Feyza Akyürek, Ekin Akyürek, Leshem Choshen, Derry Wijaya, Jacob Andreas:
Deductive Closure Training of Language Models for Coherence, Accuracy, and Updatability. ACL (Findings) 2024: 9802-9818 - [c42]Alexander Yom Din, Taelin Karidi, Leshem Choshen, Mor Geva:
Jump to Conclusions: Short-Cutting Transformers with Linear Transformations. LREC/COLING 2024: 9615-9625 - [c41]Eli Schwartz, Leshem Choshen, Joseph Shtok, Sivan Doveh, Leonid Karlinsky, Assaf Arbelle:
NumeroLogic: Number Encoding for Enhanced LLMs' Numerical Reasoning. EMNLP 2024: 206-212 - [c40]Kerem Zaman, Leshem Choshen, Shashank Srivastava:
Fuse to Forget: Bias Reduction and Selective Memorization through Model Fusion. EMNLP 2024: 18763-18783 - [c39]Asaf Yehudai, Boaz Carmeli, Yosi Mass, Ofir Arviv, Nathaniel Mills, Eyal Shnarch, Leshem Choshen:
Achieving Human Parity in Content-Grounded Datasets Generation. ICLR 2024 - [c38]Felipe Maia Polo, Lucas Weber, Leshem Choshen, Yuekai Sun, Gongjun Xu, Mikhail Yurochkin:
tinyBenchmarks: evaluating LLMs with fewer examples. ICML 2024 - [c37]Jiacheng Zhu, Kristjan H. Greenewald, Kimia Nadjahi, Haitz Sáez de Ocáriz Borde, Rickard Brüel Gabrielsson, Leshem Choshen, Marzyeh Ghassemi, Mikhail Yurochkin, Justin Solomon:
Asymmetry in Low-Rank Adapters of Foundation Models. ICML 2024 - [c36]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 - [c35]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 - [i63]Afra Feyza Akyürek, Ekin Akyürek, Leshem Choshen, Derry Wijaya
, Jacob Andreas:
Deductive Closure Training of Language Models for Coherence, Accuracy, and Updatability. CoRR abs/2401.08574 (2024) - [i62]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) - [i61]Asaf Yehudai, Boaz Carmeli, Yosi Mass, Ofir Arviv, Nathaniel Mills, Assaf Toledo, Eyal Shnarch, Leshem Choshen:
Genie: Achieving Human Parity in Content-Grounded Datasets Generation. CoRR abs/2401.14367 (2024) - [i60]Shir Ashury-Tahan, Benjamin Sznajder, Leshem Choshen, Liat Ein-Dor, Eyal Shnarch, Ariel Gera:
Label-Efficient Model Selection for Text Generation. CoRR abs/2402.07891 (2024) - [i59]Felipe Maia Polo, Lucas Weber, Leshem Choshen, Yuekai Sun, Gongjun Xu, Mikhail Yurochkin:
tinyBenchmarks: evaluating LLMs with fewer examples. CoRR abs/2402.14992 (2024) - [i58]Jiacheng Zhu, Kristjan H. Greenewald, Kimia Nadjahi, Haitz Sáez de Ocáriz Borde, Rickard Brüel Gabrielsson, Leshem Choshen, Marzyeh Ghassemi, Mikhail Yurochkin, Justin Solomon:
Asymmetry in Low-Rank Adapters of Foundation Models. CoRR abs/2402.16842 (2024) - [i57]Eli Schwartz, Leshem Choshen, Joseph Shtok, Sivan Doveh, Leonid Karlinsky, Assaf Arbelle:
NumeroLogic: Number Encoding for Enhanced LLMs' Numerical Reasoning. CoRR abs/2404.00459 (2024) - [i56]Leshem Choshen, Ryan Cotterell, Michael Y. Hu, Tal Linzen, Aaron Mueller, Candace Ross, Alex Warstadt, Ethan Wilcox, Adina Williams, Chengxu Zhuang:
[Call for Papers] The 2nd BabyLM Challenge: Sample-efficient pretraining on a developmentally plausible corpus. CoRR abs/2404.06214 (2024) - [i55]Moshik Hershcovitch, Leshem Choshen, Andrew Wood, Ilias Enmouri, Peter Chin, Swaminathan Sundararaman, Danny Harnik:
Lossless and Near-Lossless Compression for Foundation Models. CoRR abs/2404.15198 (2024) - [i54]Andreas Waldis, Yotam Perlitz, Leshem Choshen, Yufang Hou, Iryna Gurevych:
Holmes: Benchmark the Linguistic Competence of Language Models. CoRR abs/2404.18923 (2024) - [i53]Anna A. Ivanova, Aalok Sathe, Benjamin Lipkin
Elements of World Knowledge (EWOK): A cognition-inspired framework for evaluating basic world knowledge in language models. CoRR abs/2405.09605 (2024) - [i52]Felipe Maia Polo, Ronald Xu, Lucas Weber, Mírian Silva, Onkar Bhardwaj, Leshem Choshen, Allysson Flavio Melo de Oliveira, Yuekai Sun, Mikhail Yurochkin:
Efficient multi-prompt evaluation of LLMs. CoRR abs/2405.17202 (2024) - [i51]Rickard Brüel Gabrielsson, Jiacheng Zhu, Onkar Bhardwaj, Leshem Choshen, Kristjan H. Greenewald, Mikhail Yurochkin, Justin Solomon:
Compress then Serve: Serving Thousands of LoRA Adapters with Little Overhead. CoRR abs/2407.00066 (2024) - [i50]Shachar Don-Yehiya, Leshem Choshen, Omri Abend:
Learning from Naturally Occurring Feedback. CoRR abs/2407.10944 (2024) - [i49]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) - [i48]Oscar Sainz, Iker García-Ferrero, Alon Jacovi, Jon Ander Campos, Yanai Elazar, Eneko Agirre, Yoav Goldberg, Wei-Lin Chen, Jenny Chim, Leshem Choshen, Luca D'Amico-Wong, Melissa Dell, Run-Ze Fan, Shahriar Golchin, Yucheng Li, Pengfei Liu, Bhavish Pahwa, Ameya Prabhu, Suryansh Sharma, Emily Silcock, Kateryna Solonko, David Stap, Mihai Surdeanu, Yu-Min Tseng, Vishaal Udandarao, Zengzhi Wang, Ruijie Xu, Jinglin Yang:
Data Contamination Report from the 2024 CONDA Shared Task. CoRR abs/2407.21530 (2024) - [i47]Prateek Yadav, Colin Raffel, Mohammed Muqeeth, Lucas Caccia, Haokun Liu, Tianlong Chen, Mohit Bansal, Leshem Choshen, Alessandro Sordoni:
A Survey on Model MoErging: Recycling and Routing Among Specialized Experts for Collaborative Learning. CoRR abs/2408.07057 (2024) - [i46]Shachar Don-Yehiya, Leshem Choshen, Omri Abend:
The ShareLM Collection and Plugin: Contributing Human-Model Chats for the Benefit of the Community. CoRR abs/2408.08291 (2024) - [i45]Maxim Ifergan, Leshem Choshen, Roee Aharoni, Idan Szpektor, Omri Abend:
Beneath the Surface of Consistency: Exploring Cross-lingual Knowledge Representation Sharing in LLMs. CoRR abs/2408.10646 (2024) - [i44]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) - [i43]Shachar Don-Yehiya, Ben Burtenshaw, Ramón Fernandez Astudillo, Cailean Osborne, Mimansa Jaiswal, Tzu-Sheng Kuo, Wenting Zhao, Idan Shenfeld, Andi Peng, Mikhail Yurochkin, Atoosa Kasirzadeh, Yangsibo Huang, Tatsunori Hashimoto, Yacine Jernite, Daniel Vila-Suero, Omri Abend, Jennifer Ding, Sara Hooker, Hannah Rose Kirk, Leshem Choshen:
The Future of Open Human Feedback. CoRR abs/2408.16961 (2024) - [i42]Eric Zhang, Leshem Choshen, Jacob Andreas:
Unforgettable Generalization in Language Models. CoRR abs/2409.02228 (2024) - 2023
- [c34]Shachar Don-Yehiya, Elad Venezian, Colin Raffel, Noam Slonim, Leshem Choshen:
ColD Fusion: Collaborative Descent for Distributed Multitask Finetuning. ACL (1) 2023: 788-806 - [c33]Ella Neeman, Roee Aharoni, Or Honovich, Leshem Choshen, Idan Szpektor, Omri Abend:
DisentQA: Disentangling Parametric and Contextual Knowledge with Counterfactual Question Answering. ACL (1) 2023: 10056-10070 - [c32]Taelin Karidi, Leshem Choshen, Gal Patel, Omri Abend:
MuLER: Detailed and Scalable Reference-based Evaluation. CoNLL 2023: 436-455 - [c31]Almog Gueta, Elad Venezian, Colin Raffel, Noam Slonim, Yoav Katz, Leshem Choshen:
Knowledge is a Region in Weight Space for Fine-tuned Language Models. EMNLP (Findings) 2023: 1350-1370 - [c30]Leshem Choshen, Elad Venezian, Shachar Don-Yehiya, Noam Slonim, Yoav Katz:
Where to start? Analyzing the potential value of intermediate models. EMNLP 2023: 1446-1470 - [c29]Shachar Don-Yehiya, Leshem Choshen, Omri Abend:
Human Learning by Model Feedback: The Dynamics of Iterative Prompting with Midjourney. EMNLP 2023: 4146-4161 - [c28]Prateek Yadav, Derek Tam, Leshem Choshen, Colin A. Raffel, Mohit Bansal:
TIES-Merging: Resolving Interference When Merging Models. NeurIPS 2023 - [i41]Alex Warstadt, Leshem Choshen, Aaron Mueller, Adina Williams, Ethan Wilcox, Chengxu Zhuang:
Call for Papers - The BabyLM Challenge: Sample-efficient pretraining on a developmentally plausible corpus. CoRR abs/2301.11796 (2023) - [i40]Almog Gueta, Elad Venezian, Colin Raffel, Noam Slonim, Yoav Katz, Leshem Choshen:
Knowledge is a Region in Weight Space for Fine-tuned Language Models. CoRR abs/2302.04863 (2023) - [i39]Alexander Yom Din, Taelin Karidi, Leshem Choshen, Mor Geva
Jump to Conclusions: Short-Cutting Transformers With Linear Transformations. CoRR abs/2303.09435 (2023) - [i38]Taelin Karidi, Leshem Choshen, Gal Patel, Omri Abend:
MuLER: Detailed and Scalable Reference-based Evaluation. CoRR abs/2305.14991 (2023) - [i37]Prateek Yadav, Derek Tam, Leshem Choshen, Colin Raffel, Mohit Bansal:
Resolving Interference When Merging Models. CoRR abs/2306.01708 (2023) - [i36]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) - [i35]Kerem Zaman, Leshem Choshen, Shashank Srivastava:
Fuse to Forget: Bias Reduction and Selective Memorization through Model Fusion. CoRR abs/2311.07682 (2023) - [i34]Shachar Don-Yehiya, Leshem Choshen, Omri Abend:
Human Learning by Model Feedback: The Dynamics of Iterative Prompting with Midjourney. CoRR abs/2311.12131 (2023) - [i33]Prateek Yadav, Leshem Choshen, Colin Raffel, Mohit Bansal:
ComPEFT: Compression for Communicating Parameter Efficient Updates via Sparsification and Quantization. CoRR abs/2311.13171 (2023) - 2022
- [c27]Eyal Shnarch, Ariel Gera, Alon Halfon, Lena Dankin, Leshem Choshen, Ranit Aharonov, Noam Slonim:
Cluster & Tune: Boost Cold Start Performance in Text Classification. ACL (1) 2022: 7639-7653 - [c26]Leshem Choshen, Guy Hacohen, Daphna Weinshall, Omri Abend:
The Grammar-Learning Trajectories of Neural Language Models. ACL (1) 2022: 8281-8297 - [c25]Asaf Yehudai, Leshem Choshen, Lior Fox, Omri Abend:
Reinforcement Learning with Large Action Spaces for Neural Machine Translation. COLING 2022: 4544-4556 - [c24]Gal Patel, Leshem Choshen, Omri Abend:
On Neurons Invariant to Sentence Structural Changes in Neural Machine Translation. CoNLL 2022: 194-212 - [c23]Leshem Choshen, Omri Abend:
Enhancing the Transformer Decoder with Transition-based Syntax. CoNLL 2022: 384-404 - [c22]Eyal Shnarch, Alon Halfon, Ariel Gera, Marina Danilevsky, Yannis Katsis, Leshem Choshen, Martín Santillán Cooper, Dina Epelboim, Zheng Zhang, Dakuo Wang:
Label Sleuth: From Unlabeled Text to a Classifier in a Few Hours. EMNLP (Demos) 2022: 159-168 - [c21]Shachar Don-Yehiya, Leshem Choshen, Omri Abend:
PreQuEL: Quality Estimation of Machine Translation Outputs in Advance. EMNLP 2022: 11170-11183 - [c20]Piyawat Lertvittayakumjorn, Leshem Choshen, Eyal Shnarch, Francesca Toni:
GrASP: A Library for Extracting and Exploring Human-Interpretable Textual Patterns. LREC 2022: 6093-6103 - [c19]Aviv Slobodkin, Leshem Choshen, Omri Abend:
Semantics-aware Attention Improves Neural Machine Translation. *SEM@NAACL-HLT 2022: 28-43 - [i32]Eyal Shnarch, Ariel Gera, Alon Halfon, Lena Dankin, Leshem Choshen, Ranit Aharonov, Noam Slonim:
Cluster & Tune: Boost Cold Start Performance in Text Classification. CoRR abs/2203.10581 (2022) - [i31]Leshem Choshen, Elad Venezian, Noam Slonim, Yoav Katz:
Fusing finetuned models for better pretraining. CoRR abs/2204.03044 (2022) - [i30]Leshem Choshen, Ofir Shifman, Omri Abend:
Some Grammatical Errors are Frequent, Others are Important. CoRR abs/2205.05730 (2022) - [i29]Shachar Don-Yehiya, Leshem Choshen, Omri Abend:
PreQuEL: Quality Estimation of Machine Translation Outputs in Advance. CoRR abs/2205.09178 (2022) - [i28]Eyal Shnarch, Alon Halfon, Ariel Gera, Marina Danilevsky, Yannis Katsis, Leshem Choshen, Martín Santillán Cooper, Dina Epelboim, Zheng Zhang, Dakuo Wang, Lucy Yip, Liat Ein-Dor, Lena Dankin, Ilya Shnayderman, Ranit Aharonov, Yunyao Li, Naftali Liberman, Philip Levin Slesarev, Gwilym Newton, Shila Ofek-Koifman, Noam Slonim, Yoav Katz:
Label Sleuth: From Unlabeled Text to a Classifier in a Few Hours. CoRR abs/2208.01483 (2022) - [i27]Asaf Yehudai, Leshem Choshen, Lior Fox, Omri Abend:
Reinforcement Learning with Large Action Spaces for Neural Machine Translation. CoRR abs/2210.03053 (2022) - [i26]Leshem Choshen, Elad Venezian, Shachar Don-Yehiya, Noam Slonim, Yoav Katz:
Where to start? Analyzing the potential value of intermediate models. CoRR abs/2211.00107 (2022) - [i25]Ella Neeman, Roee Aharoni, Or Honovich, Leshem Choshen, Idan Szpektor, Omri Abend:
DisentQA: Disentangling Parametric and Contextual Knowledge with Counterfactual Question Answering. CoRR abs/2211.05655 (2022) - [i24]Shachar Don-Yehiya, Elad Venezian, Colin Raffel, Noam Slonim, Yoav Katz, Leshem Choshen:
ColD Fusion: Collaborative Descent for Distributed Multitask Finetuning. CoRR abs/2212.01378 (2022) - 2021
- [j1]Noam Slonim
An autonomous debating system. Nat. 591(7850): 379-384 (2021) - [c18]Or Honovich, Leshem Choshen, Roee Aharoni, Ella Neeman, Idan Szpektor, Omri Abend:
$Q^2$: Evaluating Factual Consistency in Knowledge-Grounded Dialogues via Question Generation and Question Answering. EMNLP (1) 2021: 7856-7870 - [c17]Aviv Slobodkin, Leshem Choshen, Omri Abend:
Mediators in Determining what Processing BERT Performs First. NAACL-HLT 2021: 86-93 - [i23]Leshem Choshen, Omri Abend:
Transition based Graph Decoder for Neural Machine Translation. CoRR abs/2101.12640 (2021) - [i22]Leshem Choshen, Matanel Oren, Dmitry Nikolaev, Omri Abend:
SERRANT: a syntactic classifier for English Grammatical Error Types. CoRR abs/2104.02310 (2021) - [i21]Piyawat Lertvittayakumjorn, Leshem Choshen, Eyal Shnarch, Francesca Toni:
GrASP: A Library for Extracting and Exploring Human-Interpretable Textual Patterns. CoRR abs/2104.03958 (2021) - [i20]Aviv Slobodkin, Leshem Choshen, Omri Abend:
Mediators in Determining what Processing BERT Performs First. CoRR abs/2104.06400 (2021) - [i19]Or Honovich, Leshem Choshen, Roee Aharoni, Ella Neeman, Idan Szpektor, Omri Abend:
Q2: Evaluating Factual Consistency in Knowledge-Grounded Dialogues via Question Generation and Question Answering. CoRR abs/2104.08202 (2021) - [i18]Ofek Rafaeli, Omri Abend, Leshem Choshen, Dmitry Nikolaev:
Part of Speech and Universal Dependency effects on English Arabic Machine Translation. CoRR abs/2106.00745 (2021) - [i17]Leshem Choshen, Idan Amit:
ComSum: Commit Messages Summarization and Meaning Preservation. CoRR abs/2108.10763 (2021) - [i16]Leshem Choshen, Guy Hacohen, Daphna Weinshall, Omri Abend:
The Grammar-Learning Trajectories of Neural Language Models. CoRR abs/2109.06096 (2021) - [i15]Gal Patel, Leshem Choshen, Omri Abend:
On Neurons Invariant to Sentence Structural Changes in Neural Machine Translation. CoRR abs/2110.03067 (2021) - [i14]Aviv Slobodkin, Leshem Choshen, Omri Abend:
Semantics-aware Attention Improves Neural Machine Translation. CoRR abs/2110.06920 (2021) - 2020
- [c16]Liat Ein-Dor, Eyal Shnarch, Lena Dankin, Alon Halfon, Benjamin Sznajder, Ariel Gera, Carlos Alzate, Martin Gleize, Leshem Choshen, Yufang Hou, Yonatan Bilu, Ranit Aharonov, Noam Slonim:
Corpus Wide Argument Mining - A Working Solution. AAAI 2020: 7683-7691 - [c15]Leshem Choshen, Dmitry Nikolaev, Yevgeni Berzak
Classifying Syntactic Errors in Learner Language. CoNLL 2020: 97-107 - [c14]Eyal Shnarch, Leshem Choshen, Guy Moshkowich, Ranit Aharonov, Noam Slonim:
Unsupervised Expressive Rules Provide Explainability and Assist Human Experts Grasping New Domains. EMNLP (Findings) 2020: 2678-2697 - [c13]Liat Ein-Dor, Alon Halfon, Ariel Gera, Eyal Shnarch, Lena Dankin, Leshem Choshen, Marina Danilevsky, Ranit Aharonov, Yoav Katz, Noam Slonim:
Active Learning for BERT: An Empirical Study. EMNLP (1) 2020: 7949-7962 - [c12]Leshem Choshen, Lior Fox, Zohar Aizenbud, Omri Abend
On the Weaknesses of Reinforcement Learning for Neural Machine Translation. ICLR 2020 - [c11]Guy Hacohen, Leshem Choshen, Daphna Weinshall:
Let's Agree to Agree: Neural Networks Share Classification Order on Real Datasets. ICML 2020: 3950-3960 - [i13]Eyal Shnarch, Leshem Choshen, Guy Moshkowich, Noam Slonim, Ranit Aharonov:
Unsupervised Expressive Rules Provide Explainability and Assist Human Experts Grasping New Domains. CoRR abs/2010.09459 (2020) - [i12]Leshem Choshen, Dmitry Nikolaev, Yevgeni Berzak, Omri Abend:
Classifying Syntactic Errors in Learner Language. CoRR abs/2010.11032 (2020)
2010 – 2019
- 2019
- [c10]Martin Gleize, Eyal Shnarch, Leshem Choshen, Lena Dankin, Guy Moshkowich, Ranit Aharonov, Noam Slonim:
Are You Convinced? Choosing the More Convincing Evidence with a Siamese Network. ACL (1) 2019: 967-976 - [c9]Leshem Choshen, Dan Eldad, Daniel Hershcovich, Elior Sulem, Omri Abend
The Language of Legal and Illegal Activity on the Darknet. ACL (1) 2019: 4271-4279 - [c8]Yoav Kantor, Yoav Katz, Leshem Choshen, Edo Cohen-Karlik, Naftali Liberman, Assaf Toledo, Amir Menczel, Noam Slonim:
Learning to combine Grammatical Error Corrections. BEA@ACL 2019: 139-148 - [c7]Leshem Choshen, Omri Abend
Automatically Extracting Challenge Sets for Non-Local Phenomena in Neural Machine Translation. CoNLL 2019: 291-303 - [c6]Daniel Hershcovich, Zohar Aizenbud, Leshem Choshen, Elior Sulem, Ari Rappoport, Omri Abend
SemEval-2019 Task 1: Cross-lingual Semantic Parsing with UCCA. SemEval@NAACL-HLT 2019: 1-10 - [i11]Daniel Hershcovich, Zohar Aizenbud, Leshem Choshen, Elior Sulem, Ari Rappoport, Omri Abend:
SemEval 2019 Task 1: Cross-lingual Semantic Parsing with UCCA. CoRR abs/1903.02953 (2019) - [i10]Leshem Choshen, Dan Eldad, Daniel Hershcovich, Elior Sulem, Omri Abend:
The Language of Legal and Illegal Activity on the Darknet. CoRR abs/1905.05543 (2019) - [i9]Yoav Kantor, Yoav Katz, Leshem Choshen, Edo Cohen-Karlik, Naftali Liberman, Assaf Toledo, Amir Menczel, Noam Slonim:
Learning to combine Grammatical Error Corrections. CoRR abs/1906.03897 (2019) - [i8]Leshem Choshen, Lior Fox, Zohar Aizenbud, Omri Abend:
On the Weaknesses of Reinforcement Learning for Neural Machine Translation. CoRR abs/1907.01752 (2019) - [i7]Martin Gleize, Eyal Shnarch, Leshem Choshen, Lena Dankin, Guy Moshkowich, Ranit Aharonov, Noam Slonim:
Are You Convinced? Choosing the More Convincing Evidence with a Siamese Network. CoRR abs/1907.08971 (2019) - [i6]Leshem Choshen, Omri Abend:
Automatically Extracting Challenge Sets for Non local Phenomena in Neural Machine Translation. CoRR abs/1909.06814 (2019) - [i5]Liat Ein-Dor, Eyal Shnarch, Lena Dankin, Alon Halfon, Benjamin Sznajder, Ariel Gera, Carlos Alzate, Martin Gleize, Leshem Choshen, Yufang Hou, Yonatan Bilu, Ranit Aharonov, Noam Slonim:
Corpus Wide Argument Mining - a Working Solution. CoRR abs/1911.10763 (2019) - 2018
- [c5]Eyal Shnarch, Carlos Alzate, Lena Dankin, Martin Gleize, Yufang Hou, Leshem Choshen, Ranit Aharonov, Noam Slonim:
Will it Blend? Blending Weak and Strong Labeled Data in a Neural Network for Argumentation Mining. ACL (2) 2018: 599-605 - [c4]Leshem Choshen, Omri Abend
Inherent Biases in Reference-based Evaluation for Grammatical Error Correction. ACL (1) 2018: 632-642 - [c3]Leshem Choshen, Omri Abend
Automatic Metric Validation for Grammatical Error Correction. ACL (1) 2018: 1372-1382 - [c2]Lior Fox, Leshem Choshen, Yonatan Loewenstein:
DORA The Explorer: Directed Outreaching Reinforcement Action-Selection. ICLR (Poster) 2018 - [c1]Leshem Choshen, Omri Abend
Reference-less Measure of Faithfulness for Grammatical Error Correction. NAACL-HLT (2) 2018: 124-129 - [i4]Leshem Choshen, Omri Abend:
Reference-less Measure of Faithfulness for Grammatical Error Correction. CoRR abs/1804.03824 (2018) - [i3]Leshem Choshen, Lior Fox, Yonatan Loewenstein:
DORA The Explorer: Directed Outreaching Reinforcement Action-Selection. CoRR abs/1804.04012 (2018) - [i2]Leshem Choshen, Omri Abend:
Automatic Metric Validation for Grammatical Error Correction. CoRR abs/1804.11225 (2018) - [i1]Leshem Choshen, Omri Abend:
Inherent Biases in Reference-based Evaluation for Grammatical Error Correction and Text Simplification. CoRR abs/1804.11254 (2018)
Coauthor Index
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