Search Results for author: Omri Abend

Found 62 papers, 35 papers with code

Putting Words in BERT’s Mouth: Navigating Contextualized Vector Spaces with Pseudowords

1 code implementation EMNLP 2021 Taelin Karidi, Yichu Zhou, Nathan Schneider, Omri Abend, Vivek Srikumar

We present a method for exploring regions around individual points in a contextualized vector space (particularly, BERT space), as a way to investigate how these regions correspond to word senses.

Q^{2}: Evaluating Factual Consistency in Knowledge-Grounded Dialogues via Question Generation and Question Answering

no code implementations EMNLP 2021 Or Honovich, Leshem Choshen, Roee Aharoni, Ella Neeman, Idan Szpektor, Omri Abend

Neural knowledge-grounded generative models for dialogue often produce content that is factually inconsistent with the knowledge they rely on, making them unreliable and limiting their applicability.

Abstractive Text Summarization Natural Language Inference +2

PreQuEL: Quality Estimation of Machine Translation Outputs in Advance

no code implementations18 May 2022 Shachar Don-Yehiya, Leshem Choshen, Omri Abend

We show that this augmentation method can improve the performance of the Quality-Estimation task as well.

Data Augmentation Machine Translation +1

A Computational Acquisition Model for Multimodal Word Categorization

1 code implementation12 May 2022 Uri Berger, Gabriel Stanovsky, Omri Abend, Lea Frermann

Recent advances in self-supervised modeling of text and images open new opportunities for computational models of child language acquisition, which is believed to rely heavily on cross-modal signals.

Language Acquisition Object Recognition

Some Grammatical Errors are Frequent, Others are Important

1 code implementation11 May 2022 Leshem Choshen, Ofir Shifman, Omri Abend

In Grammatical Error Correction, systems are evaluated by the number of errors they correct.

Grammatical Error Correction

Semantics-aware Attention Improves Neural Machine Translation

no code implementations13 Oct 2021 Aviv Slobodkin, Leshem Choshen, Omri Abend

We further show an additional gain when using both semantic and syntactic structures in some language pairs.

Machine Translation Translation

On the Relation between Syntactic Divergence and Zero-Shot Performance

1 code implementation EMNLP 2021 Ofir Arviv, Dmitry Nikolaev, Taelin Karidi, Omri Abend

We explore the link between the extent to which syntactic relations are preserved in translation and the ease of correctly constructing a parse tree in a zero-shot setting.

Cross-lingual zero-shot dependency parsing Relation Classification

On Neurons Invariant to Sentence Structural Changes in Neural Machine Translation

1 code implementation6 Oct 2021 Gal Patel, Leshem Choshen, Omri Abend

To gain insight into the role neurons play, we study the activation patterns corresponding to meaning preserving paraphrases (e. g., active-passive).

Machine Translation Translation

Putting Words in BERT's Mouth: Navigating Contextualized Vector Spaces with Pseudowords

no code implementations23 Sep 2021 Taelin Karidi, Yichu Zhou, Nathan Schneider, Omri Abend, Vivek Srikumar

We present a method for exploring regions around individual points in a contextualized vector space (particularly, BERT space), as a way to investigate how these regions correspond to word senses.

The Grammar-Learning Trajectories of Neural Language Models

1 code implementation ACL 2022 Leshem Choshen, Guy Hacohen, Daphna Weinshall, Omri Abend

These findings suggest that there is some mutual inductive bias that underlies these models' learning of linguistic phenomena.

Inductive Bias

Part of Speech and Universal Dependency effects on English Arabic Machine Translation

no code implementations1 Jun 2021 Ofek Rafaeli, Omri Abend, Leshem Choshen, Dmitry Nikolaev

In this research paper, I will elaborate on a method to evaluate machine translation models based on their performance on underlying syntactical phenomena between English and Arabic languages.

Machine Translation Translation

$Q^{2}$: Evaluating Factual Consistency in Knowledge-Grounded Dialogues via Question Generation and Question Answering

1 code implementation16 Apr 2021 Or Honovich, Leshem Choshen, Roee Aharoni, Ella Neeman, Idan Szpektor, Omri Abend

Neural knowledge-grounded generative models for dialogue often produce content that is factually inconsistent with the knowledge they rely on, making them unreliable and limiting their applicability.

Abstractive Text Summarization Dialogue Evaluation +3

Mediators in Determining what Processing BERT Performs First

1 code implementation NAACL 2021 Aviv Slobodkin, Leshem Choshen, Omri Abend

Probing neural models for the ability to perform downstream tasks using their activation patterns is often used to localize what parts of the network specialize in performing what tasks.

SERRANT: a syntactic classifier for English Grammatical Error Types

1 code implementation6 Apr 2021 Leshem Choshen, Matanel Oren, Dmitry Nikolaev, Omri Abend

SERRANT is a system and code for automatic classification of English grammatical errors that combines SErCl and ERRANT.

General Classification

Enhancing the Transformer Decoder with Transition-based Syntax

no code implementations29 Jan 2021 Leshem Choshen, Omri Abend

Notwithstanding recent advances, syntactic generalization remains a challenge for text decoders.

Machine Translation Text Generation +1

UCCA's Foundational Layer: Annotation Guidelines v2.1

1 code implementation31 Dec 2020 Omri Abend, Nathan Schneider, Dotan Dvir, Jakob Prange, Ari Rappoport

This is the annotation manual for Universal Conceptual Cognitive Annotation (UCCA; Abend and Rappoport, 2013), specifically the Foundational Layer.

Cross-lingual Semantic Representation for NLP with UCCA

no code implementations COLING 2020 Omri Abend, Dotan Dvir, Daniel Hershcovich, Jakob Prange, Nathan Schneider

This is an introductory tutorial to UCCA (Universal Conceptual Cognitive Annotation), a cross-linguistically applicable framework for semantic representation, with corpora annotated in English, German and French, and ongoing annotation in Russian and Hebrew.

Natural Language Processing UCCA Parsing

Semantic Structural Decomposition for Neural Machine Translation

1 code implementation Joint Conference on Lexical and Computational Semantics 2020 Elior Sulem, Omri Abend, Ari Rappoport

Building on recent advances in semantic parsing and text simplification, we investigate the use of semantic splitting of the source sentence as preprocessing for machine translation.

Machine Translation Semantic Parsing +2

Comparison by Conversion: Reverse-Engineering UCCA from Syntax and Lexical Semantics

2 code implementations COLING 2020 Daniel Hershcovich, Nathan Schneider, Dotan Dvir, Jakob Prange, Miryam de Lhoneux, Omri Abend

Building robust natural language understanding systems will require a clear characterization of whether and how various linguistic meaning representations complement each other.

Natural Language Understanding

MRP 2020: The Second Shared Task on Cross-Framework and Cross-Lingual Meaning Representation Parsing

no code implementations CONLL 2020 Stephan Oepen, Omri Abend, Lasha Abzianidze, Johan Bos, Jan Hajic, Daniel Hershcovich, Bin Li, Tim O{'}Gorman, Nianwen Xue, Daniel Zeman

Extending a similar setup from the previous year, five distinct approaches to the representation of sentence meaning in the form of directed graphs were represented in the English training and evaluation data for the task, packaged in a uniform graph abstraction and serialization; for four of these representation frameworks, additional training and evaluation data was provided for one additional language per framework.

Classifying Syntactic Errors in Learner Language

1 code implementation CONLL 2020 Leshem Choshen, Dmitry Nikolaev, Yevgeni Berzak, Omri Abend

We present a method for classifying syntactic errors in learner language, namely errors whose correction alters the morphosyntactic structure of a sentence.

Classification General Classification +1

PMI-Masking: Principled masking of correlated spans

no code implementations ICLR 2021 Yoav Levine, Barak Lenz, Opher Lieber, Omri Abend, Kevin Leyton-Brown, Moshe Tennenholtz, Yoav Shoham

Specifically, we show experimentally that PMI-Masking reaches the performance of prior masking approaches in half the training time, and consistently improves performance at the end of training.

Fine-Grained Analysis of Cross-Linguistic Syntactic Divergences

1 code implementation ACL 2020 Dmitry Nikolaev, Ofir Arviv, Taelin Karidi, Neta Kenneth, Veronika Mitnik, Lilja Maria Saeboe, Omri Abend

The patterns in which the syntax of different languages converges and diverges are often used to inform work on cross-lingual transfer.

Cross-Lingual Transfer

Language (Re)modelling: Towards Embodied Language Understanding

no code implementations ACL 2020 Ronen Tamari, Chen Shani, Tom Hope, Miriam R. L. Petruck, Omri Abend, Dafna Shahaf

While natural language understanding (NLU) is advancing rapidly, today's technology differs from human-like language understanding in fundamental ways, notably in its inferior efficiency, interpretability, and generalization.

Natural Language Understanding

MRP 2019: Cross-Framework Meaning Representation Parsing

no code implementations CONLL 2019 Stephan Oepen, Omri Abend, Jan Hajic, Daniel Hershcovich, Marco Kuhlmann, Tim O{'}Gorman, Nianwen Xue, Jayeol Chun, Milan Straka, Zdenka Uresova

The 2019 Shared Task at the Conference for Computational Language Learning (CoNLL) was devoted to Meaning Representation Parsing (MRP) across frameworks.

Automatically Extracting Challenge Sets for Non-Local Phenomena in Neural Machine Translation

no code implementations CONLL 2019 Leshem Choshen, Omri Abend

We show that the state-of-the-art Transformer MT model is not biased towards monotonic reordering (unlike previous recurrent neural network models), but that nevertheless, long-distance dependencies remain a challenge for the model.

Machine Translation Translation

Made for Each Other: Broad-coverage Semantic Structures Meet Preposition Supersenses

1 code implementation CONLL 2019 Jakob Prange, Nathan Schneider, Omri Abend

Universal Conceptual Cognitive Annotation (UCCA; Abend and Rappoport, 2013) is a typologically-informed, broad-coverage semantic annotation scheme that describes coarse-grained predicate-argument structure but currently lacks semantic roles.

Automatically Extracting Challenge Sets for Non local Phenomena in Neural Machine Translation

1 code implementation15 Sep 2019 Leshem Choshen, Omri Abend

We show that the state of the art Transformer Machine Translation (MT) model is not biased towards monotonic reordering (unlike previous recurrent neural network models), but that nevertheless, long-distance dependencies remain a challenge for the model.

Machine Translation Translation

Preparing SNACS for Subjects and Objects

1 code implementation WS 2019 Adi Shalev, Jena D. Hwang, Nathan Schneider, Vivek Srikumar, Omri Abend, Ari Rappoport

Research on adpositions and possessives in multiple languages has led to a small inventory of general-purpose meaning classes that disambiguate tokens.

On the Weaknesses of Reinforcement Learning for Neural Machine Translation

no code implementations ICLR 2020 Leshem Choshen, Lior Fox, Zohar Aizenbud, Omri Abend

Reinforcement learning (RL) is frequently used to increase performance in text generation tasks, including machine translation (MT), notably through the use of Minimum Risk Training (MRT) and Generative Adversarial Networks (GAN).

Machine Translation reinforcement-learning +2

Semantically Constrained Multilayer Annotation: The Case of Coreference

no code implementations WS 2019 Jakob Prange, Nathan Schneider, Omri Abend

We propose a coreference annotation scheme as a layer on top of the Universal Conceptual Cognitive Annotation foundational layer, treating units in predicate-argument structure as a basis for entity and event mentions.

Content Differences in Syntactic and Semantic Representation

2 code implementations NAACL 2019 Daniel Hershcovich, Omri Abend, Ari Rappoport

Syntactic analysis plays an important role in semantic parsing, but the nature of this role remains a topic of ongoing debate.

UCCA Parsing

The Language of Legal and Illegal Activity on the Darknet

1 code implementation ACL 2019 Leshem Choshen, Dan Eldad, Daniel Hershcovich, Elior Sulem, Omri Abend

The non-indexed parts of the Internet (the Darknet) have become a haven for both legal and illegal anonymous activity.

POS

Content Differences in Syntactic and Semantic Representations

1 code implementation15 Mar 2019 Daniel Hershcovich, Omri Abend, Ari Rappoport

Syntactic analysis plays an important role in semantic parsing, but the nature of this role remains a topic of ongoing debate.

UCCA Parsing

SemEval-2019 Task 1: Cross-lingual Semantic Parsing with UCCA

no code implementations SEMEVAL 2019 Daniel Hershcovich, Zohar Aizenbud, Leshem Choshen, Elior Sulem, Ari Rappoport, Omri Abend

We present the SemEval 2019 shared task on UCCA parsing in English, German and French, and discuss the participating systems and results.

UCCA Parsing

BLEU is Not Suitable for the Evaluation of Text Simplification

1 code implementation EMNLP 2018 Elior Sulem, Omri Abend, Ari Rappoport

BLEU is widely considered to be an informative metric for text-to-text generation, including Text Simplification (TS).

Text Generation Text Simplification

Semantic Structural Evaluation for Text Simplification

1 code implementation NAACL 2018 Elior Sulem, Omri Abend, Ari Rappoport

Current measures for evaluating text simplification systems focus on evaluating lexical text aspects, neglecting its structural aspects.

Semantic Parsing Text Simplification

Inherent Biases in Reference-based Evaluation for Grammatical Error Correction

1 code implementation ACL 2018 Leshem Choshen, Omri Abend

The prevalent use of too few references for evaluating text-to-text generation is known to bias estimates of their quality (henceforth, low coverage bias or LCB).

Grammatical Error Correction Text Generation +1

SemEval 2019 Shared Task: Cross-lingual Semantic Parsing with UCCA - Call for Participation

no code implementations31 May 2018 Daniel Hershcovich, Leshem Choshen, Elior Sulem, Zohar Aizenbud, Ari Rappoport, Omri Abend

Given the success of recent semantic parsing shared tasks (on SDP and AMR), we expect the task to have a significant contribution to the advancement of UCCA parsing in particular, and semantic parsing in general.

UCCA Parsing

Comprehensive Supersense Disambiguation of English Prepositions and Possessives

1 code implementation ACL 2018 Nathan Schneider, Jena D. Hwang, Vivek Srikumar, Jakob Prange, Austin Blodgett, Sarah R. Moeller, Aviram Stern, Adi Bitan, Omri Abend

Semantic relations are often signaled with prepositional or possessive marking--but extreme polysemy bedevils their analysis and automatic interpretation.

Multitask Parsing Across Semantic Representations

1 code implementation ACL 2018 Daniel Hershcovich, Omri Abend, Ari Rappoport

The ability to consolidate information of different types is at the core of intelligence, and has tremendous practical value in allowing learning for one task to benefit from generalizations learned for others.

UCCA Parsing

Inherent Biases in Reference based Evaluation for Grammatical Error Correction and Text Simplification

1 code implementation30 Apr 2018 Leshem Choshen, Omri Abend

The prevalent use of too few references for evaluating text-to-text generation is known to bias estimates of their quality ({\it low coverage bias} or LCB).

Grammatical Error Correction Text Generation +1

Automatic Metric Validation for Grammatical Error Correction

1 code implementation ACL 2018 Leshem Choshen, Omri Abend

Metric validation in Grammatical Error Correction (GEC) is currently done by observing the correlation between human and metric-induced rankings.

Grammatical Error Correction

Reference-less Measure of Faithfulness for Grammatical Error Correction

1 code implementation NAACL 2018 Leshem Choshen, Omri Abend

We propose USim, a semantic measure for Grammatical Error Correction (GEC) that measures the semantic faithfulness of the output to the source, thereby complementing existing reference-less measures (RLMs) for measuring the output's grammaticality.

Grammatical Error Correction

The State of the Art in Semantic Representation

no code implementations ACL 2017 Omri Abend, Ari Rappoport

Semantic representation is receiving growing attention in NLP in the past few years, and many proposals for semantic schemes (e. g., AMR, UCCA, GMB, UDS) have been put forth.

Adposition and Case Supersenses v2.6: Guidelines for English

3 code implementations7 Apr 2017 Nathan Schneider, Jena D. Hwang, Vivek Srikumar, Archna Bhatia, Na-Rae Han, Tim O'Gorman, Sarah R. Moeller, Omri Abend, Adi Shalev, Austin Blodgett, Jakob Prange

This document offers a detailed linguistic description of SNACS (Semantic Network of Adposition and Case Supersenses; Schneider et al., 2018), an inventory of 52 semantic labels ("supersenses") that characterize the use of adpositions and case markers at a somewhat coarse level of granularity, as demonstrated in the STREUSLE corpus (https://github. com/nert-nlp/streusle/; version 4. 5 tracks guidelines version 2. 6).

A Transition-Based Directed Acyclic Graph Parser for UCCA

1 code implementation ACL 2017 Daniel Hershcovich, Omri Abend, Ari Rappoport

We present the first parser for UCCA, a cross-linguistically applicable framework for semantic representation, which builds on extensive typological work and supports rapid annotation.

UCCA Parsing

HUME: Human UCCA-Based Evaluation of Machine Translation

1 code implementation EMNLP 2016 Alexandra Birch, Omri Abend, Ondrej Bojar, Barry Haddow

Human evaluation of machine translation normally uses sentence-level measures such as relative ranking or adequacy scales.

Machine Translation Translation

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