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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 - [i66]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) - [i65]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) - [i64]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) - [i63]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) - [i62]Felipe Maia Polo, Lucas Weber, Leshem Choshen, Yuekai Sun, Gongjun Xu, Mikhail Yurochkin:
tinyBenchmarks: evaluating LLMs with fewer examples. CoRR abs/2402.14992 (2024) - [i61]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) - [i60]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) - [i59]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) - [i58]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) - [i57]Andreas Waldis, Yotam Perlitz, Leshem Choshen, Yufang Hou, Iryna Gurevych:
Holmes: Benchmark the Linguistic Competence of Language Models. CoRR abs/2404.18923 (2024) - [i56]Anna A. Ivanova, Aalok Sathe, Benjamin Lipkin, Unnathi Kumar, Setayesh Radkani, Thomas Hikaru Clark, Carina Kauf, Jennifer Hu, R. T. Pramod, Gabriel Grand, Vivian C. Paulun, Maria Ryskina, Ekin Akyürek, Ethan Wilcox, Nafisa Rashid, Leshem Choshen, Roger Levy, Evelina Fedorenko, Joshua B. Tenenbaum, Jacob Andreas:
Elements of World Knowledge (EWOK): A cognition-inspired framework for evaluating basic world knowledge in language models. CoRR abs/2405.09605 (2024) - [i55]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) - [i54]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) - [i53]Shachar Don-Yehiya, Leshem Choshen, Omri Abend:
Learning from Naturally Occurring Feedback. CoRR abs/2407.10944 (2024) - [i52]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) - [i51]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) - [i50]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) - [i49]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) - [i48]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) - [i47]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) - [i46]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) - [i45]Eric Zhang, Leshem Choshen, Jacob Andreas:
Unforgettable Generalization in Language Models. CoRR abs/2409.02228 (2024) - [i44]Nimrod Shabtay, Felipe Maia Polo, Sivan Doveh, Wei Lin, M. Jehanzeb Mirza, Leshem Choshen, Mikhail Yurochkin, Yuekai Sun, Assaf Arbelle, Leonid Karlinsky, Raja Giryes:
LiveXiv - A Multi-Modal Live Benchmark Based on Arxiv Papers Content. CoRR abs/2410.10783 (2024) - [i43]Leshem Choshen, Yang Zhang, Jacob Andreas:
A Hitchhiker's Guide to Scaling Law Estimation. CoRR abs/2410.11840 (2024) - [i42]George Stoica, Pratik Ramesh, Boglarka Ecsedi, Leshem Choshen, Judy Hoffman:
Model merging with SVD to tie the Knots. CoRR abs/2410.19735 (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, Yonatan Bilu, Carlos Alzate, Roy Bar-Haim, Ben Bogin, Francesca Bonin, Leshem Choshen, Edo Cohen-Karlik, Lena Dankin, Lilach Edelstein, Liat Ein-Dor, Roni Friedman-Melamed, Assaf Gavron, Ariel Gera, Martin Gleize, Shai Gretz, Dan Gutfreund, Alon Halfon, Daniel Hershcovich, Ron Hoory, Yufang Hou, Shay Hummel, Michal Jacovi, Charles Jochim, Yoav Kantor, Yoav Katz, David Konopnicki, Zvi Kons, Lili Kotlerman, Dalia Krieger, Dan Lahav, Tamar Lavee, Ran Levy, Naftali Liberman, Yosi Mass, Amir Menczel, Shachar Mirkin, Guy Moshkowich, Shila Ofek-Koifman, Matan Orbach, Ella Rabinovich, Ruty Rinott, Slava Shechtman, Dafna Sheinwald, Eyal Shnarch, Ilya Shnayderman, Aya Soffer, Artem Spector, Benjamin Sznajder, Assaf Toledo, Orith Toledo-Ronen, Elad Venezian, Ranit Aharonov:
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, Omri Abend:
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)