Search Results for author: Roi Reichart

Found 83 papers, 34 papers with code

Multi-SimLex: A Large-Scale Evaluation of Multilingual and Crosslingual Lexical Semantic Similarity

no code implementations CL (ACL) 2020 Ivan Vulić, Simon Baker, Edoardo Maria Ponti, Ulla Petti, Ira Leviant, Kelly Wing, Olga Majewska, Eden Bar, Matt Malone, Thierry Poibeau, Roi Reichart, Anna Korhonen

We introduce Multi-SimLex, a large-scale lexical resource and evaluation benchmark covering data sets for 12 typologically diverse languages, including major languages (e. g., Mandarin Chinese, Spanish, Russian) as well as less-resourced ones (e. g., Welsh, Kiswahili).

Semantic Similarity Semantic Textual Similarity +1

DILBERT: Customized Pre-Training for Domain Adaptation with Category Shift, with an Application to Aspect Extraction

1 code implementation EMNLP 2021 Entony Lekhtman, Yftah Ziser, Roi Reichart

We name this scheme DILBERT: Domain Invariant Learning with BERT, and customize it for aspect extraction in the unsupervised domain adaptation setting.

Aspect Extraction Language Modelling +2

On the Robustness of Dialogue History Representation in Conversational Question Answering: A Comprehensive Study and a New Prompt-based Method

1 code implementation29 Jun 2022 Zorik Gekhman, Nadav Oved, Orgad Keller, Idan Szpektor, Roi Reichart

We find that high benchmark scores do not necessarily translate to strong robustness, and that various methods can perform extremely differently under different settings.

Conversational Question Answering

A Functional Information Perspective on Model Interpretation

1 code implementation12 Jun 2022 Itai Gat, Nitay Calderon, Roi Reichart, Tamir Hazan

This work suggests a theoretical framework for model interpretability by measuring the contribution of relevant features to the functional entropy of the network with respect to the input.

In the Eye of the Beholder: Robust Prediction with Causal User Modeling

no code implementations1 Jun 2022 Amir Feder, Guy Horowitz, Yoav Wald, Roi Reichart, Nir Rosenfeld

Accurately predicting the relevance of items to users is crucial to the success of many social platforms.

Recommendation Systems

Learning Discrete Structured Variational Auto-Encoder using Natural Evolution Strategies

1 code implementation ICLR 2022 Alon Berliner, Guy Rotman, Yossi Adi, Roi Reichart, Tamir Hazan

Discrete variational auto-encoders (VAEs) are able to represent semantic latent spaces in generative learning.

Example-based Hypernetworks for Out-of-Distribution Generalization

1 code implementation27 Mar 2022 Tomer Volk, Eyal Ben-David, Ohad Amosy, Gal Chechik, Roi Reichart

While Natural Language Processing (NLP) algorithms keep reaching unprecedented milestones, out-of-distribution generalization is still challenging.

Domain Adaptation Natural Language Inference +3

DoCoGen: Domain Counterfactual Generation for Low Resource Domain Adaptation

1 code implementation ACL 2022 Nitay Calderon, Eyal Ben-David, Amir Feder, Roi Reichart

Natural language processing (NLP) algorithms have become very successful, but they still struggle when applied to out-of-distribution examples.

Domain Adaptation Natural Language Processing

DILBERT: Customized Pre-Training for Domain Adaptation withCategory Shift, with an Application to Aspect Extraction

1 code implementation1 Sep 2021 Entony Lekhtman, Yftah Ziser, Roi Reichart

We name this scheme DILBERT: Domain Invariant Learning with BERT, and customize it for aspect extraction in the unsupervised domain adaptation setting.

Aspect Extraction Language Modelling +2

Towards Zero-shot Language Modeling

no code implementations IJCNLP 2019 Edoardo Maria Ponti, Ivan Vulić, Ryan Cotterell, Roi Reichart, Anna Korhonen

Motivated by this question, we aim at constructing an informative prior over neural weights, in order to adapt quickly to held-out languages in the task of character-level language modeling.

Language Modelling

Are VQA Systems RAD? Measuring Robustness to Augmented Data with Focused Interventions

no code implementations ACL 2021 Daniel Rosenberg, Itai Gat, Amir Feder, Roi Reichart

Deep learning algorithms have shown promising results in visual question answering (VQA) tasks, but a more careful look reveals that they often do not understand the rich signal they are being fed with.

Question Answering Visual Question Answering

Designing an Automatic Agent for Repeated Language based Persuasion Games

no code implementations11 May 2021 Maya Raifer, Guy Rotman, Reut Apel, Moshe Tennenholtz, Roi Reichart

Persuasion games are fundamental in economics and AI research and serve as the basis for important applications.

PADA: Example-based Prompt Learning for on-the-fly Adaptation to Unseen Domains

1 code implementation24 Feb 2021 Eyal Ben-David, Nadav Oved, Roi Reichart

We address a challenging and underexplored version of this domain adaptation problem, where an algorithm is trained on several source domains, and then applied to examples from unseen domains that are unknown at training time.

Domain Adaptation Language Modelling +4

Combining Deep Generative Models and Multi-lingual Pretraining for Semi-supervised Document Classification

1 code implementation EACL 2021 Yi Zhu, Ehsan Shareghi, Yingzhen Li, Roi Reichart, Anna Korhonen

Semi-supervised learning through deep generative models and multi-lingual pretraining techniques have orchestrated tremendous success across different areas of NLP.

Classification Document Classification +1

Model Compression for Domain Adaptation through Causal Effect Estimation

1 code implementation18 Jan 2021 Guy Rotman, Amir Feder, Roi Reichart

Recent improvements in the predictive quality of natural language processing systems are often dependent on a substantial increase in the number of model parameters.

Domain Adaptation Model Compression +3

A Closer Look at Few-Shot Crosslingual Transfer: The Choice of Shots Matters

no code implementations ACL 2021 Mengjie Zhao, Yi Zhu, Ehsan Shareghi, Ivan Vulić, Roi Reichart, Anna Korhonen, Hinrich Schütze

Few-shot crosslingual transfer has been shown to outperform its zero-shot counterpart with pretrained encoders like multilingual BERT.

Few-Shot Learning

Predicting Decisions in Language Based Persuasion Games

1 code implementation17 Dec 2020 Reut Apel, Ido Erev, Roi Reichart, Moshe Tennenholtz

Our results demonstrate that given a prefix of the interaction sequence, our models can predict the future decisions of the decision-maker, particularly when a sequential modeling approach and hand-crafted textual features are applied.

Decision Making

CausaLM: Causal Model Explanation Through Counterfactual Language Models

no code implementations CL (ACL) 2021 Amir Feder, Nadav Oved, Uri Shalit, Roi Reichart

Concretely, we show that by carefully choosing auxiliary adversarial pre-training tasks, language representation models such as BERT can effectively learn a counterfactual representation for a given concept of interest, and be used to estimate its true causal effect on model performance.

Multidirectional Associative Optimization of Function-Specific Word Representations

1 code implementation ACL 2020 Daniela Gerz, Ivan Vulić, Marek Rei, Roi Reichart, Anna Korhonen

We present a neural framework for learning associations between interrelated groups of words such as the ones found in Subject-Verb-Object (SVO) structures.

The Structured Weighted Violations MIRA

1 code implementation9 May 2020 Dor Ringel, Rotem Dror, Roi Reichart

We present the Structured Weighted Violation MIRA (SWVM), a new structured prediction algorithm that is based on an hybridization between MIRA (Crammer and Singer, 2003) and the structured weighted violations perceptron (SWVP) (Dror and Reichart, 2016).

Chunking named-entity-recognition +2

Predicting Strategic Behavior from Free Text

1 code implementation6 Apr 2020 Omer Ben-Porat, Sharon Hirsch, Lital Kuchy, Guy Elad, Roi Reichart, Moshe Tennenholtz

In ablation analysis, we demonstrate the importance of our modeling choices---the representation of the text with the commonsensical personality attributes and our classifier---to the predictive power of our model.

Sentiment Analysis

Multi-SimLex: A Large-Scale Evaluation of Multilingual and Cross-Lingual Lexical Semantic Similarity

no code implementations10 Mar 2020 Ivan Vulić, Simon Baker, Edoardo Maria Ponti, Ulla Petti, Ira Leviant, Kelly Wing, Olga Majewska, Eden Bar, Matt Malone, Thierry Poibeau, Roi Reichart, Anna Korhonen

We introduce Multi-SimLex, a large-scale lexical resource and evaluation benchmark covering datasets for 12 typologically diverse languages, including major languages (e. g., Mandarin Chinese, Spanish, Russian) as well as less-resourced ones (e. g., Welsh, Kiswahili).

Cross-Lingual Word Embeddings Semantic Similarity +2

Geosocial Location Classification: Associating Type to Places Based on Geotagged Social-Media Posts

no code implementations5 Feb 2020 Elad Kravi, Benny Kimelfeld, Yaron Kanza, Roi Reichart

We explore two approaches to the problem: (a) a pipeline approach, where each message is first classified, and then the location associated with the message set is inferred from the individual message labels; and (b) a joint approach where the individual messages are simultaneously processed to yield the desired location type.

General Classification Text Classification

The Secret is in the Spectra: Predicting Cross-lingual Task Performance with Spectral Similarity Measures

no code implementations EMNLP 2020 Haim Dubossarsky, Ivan Vulić, Roi Reichart, Anna Korhonen

Performance in cross-lingual NLP tasks is impacted by the (dis)similarity of languages at hand: e. g., previous work has suggested there is a connection between the expected success of bilingual lexicon induction (BLI) and the assumption of (approximate) isomorphism between monolingual embedding spaces.

Bilingual Lexicon Induction POS

Zero-Shot Semantic Parsing for Instructions

1 code implementation ACL 2019 Ofer Givoli, Roi Reichart

We consider a zero-shot semantic parsing task: parsing instructions into compositional logical forms, in domains that were not seen during training.

Semantic Parsing

Deep Contextualized Self-training for Low Resource Dependency Parsing

1 code implementation TACL 2019 Guy Rotman, Roi Reichart

Neural dependency parsing has proven very effective, achieving state-of-the-art results on numerous domains and languages.

Dependency Parsing

Cross-lingual Semantic Specialization via Lexical Relation Induction

no code implementations IJCNLP 2019 Edoardo Maria Ponti, Ivan Vuli{\'c}, Goran Glava{\v{s}}, Roi Reichart, Anna Korhonen

Semantic specialization integrates structured linguistic knowledge from external resources (such as lexical relations in WordNet) into pretrained distributional vectors in the form of constraints.

Lexical Simplification Semantic Textual Similarity +2

Predicting In-game Actions from Interviews of NBA Players

2 code implementations CL (ACL) 2020 Nadav Oved, Amir Feder, Roi Reichart

We find that our best performing textual model is most associated with topics that are intuitively related to each prediction task and that better models yield higher correlation with more informative topics.

Text Classification

Do We Really Need Fully Unsupervised Cross-Lingual Embeddings?

1 code implementation IJCNLP 2019 Ivan Vulić, Goran Glavaš, Roi Reichart, Anna Korhonen

A series of bilingual lexicon induction (BLI) experiments with 15 diverse languages (210 language pairs) show that fully unsupervised CLWE methods still fail for a large number of language pairs (e. g., they yield zero BLI performance for 87/210 pairs).

Bilingual Lexicon Induction Self-Learning

Task Refinement Learning for Improved Accuracy and Stability of Unsupervised Domain Adaptation

1 code implementation ACL 2019 Yftah Ziser, Roi Reichart

Pivot Based Language Modeling (PBLM) (Ziser and Reichart, 2018a), combining LSTMs with pivot-based methods, has yielded significant progress in unsupervised domain adaptation.

Language Modelling Sentiment Analysis +1

Deep Dominance - How to Properly Compare Deep Neural Models

1 code implementation ACL 2019 Rotem Dror, Segev Shlomov, Roi Reichart

Comparing between Deep Neural Network (DNN) models based on their performance on unseen data is crucial for the progress of the NLP field.

Bayesian Learning for Neural Dependency Parsing

no code implementations NAACL 2019 Ehsan Shareghi, Yingzhen Li, Yi Zhu, Roi Reichart, Anna Korhonen

While neural dependency parsers provide state-of-the-art accuracy for several languages, they still rely on large amounts of costly labeled training data.

Dependency Parsing POS +1

Deep Pivot-Based Modeling for Cross-language Cross-domain Transfer with Minimal Guidance

1 code implementation EMNLP 2018 Yftah Ziser, Roi Reichart

In the full setup the model has access to unlabeled data from both pairs, while in the lazy setup, which is more realistic for truly resource-poor languages, unlabeled data is available for both domains but only for the source language.

Word Embeddings

Neural Transition Based Parsing of Web Queries: An Entity Based Approach

no code implementations EMNLP 2018 Rivka Malca, Roi Reichart

Pinter et al. (2016) has formalized the grammar of these queries and proposed semi-supervised algorithms for the adaptation of parsers originally designed to parse according to the standard dependency grammar, so that they can account for the unique forest grammar of queries.

Community Question Answering

Appendix - Recommended Statistical Significance Tests for NLP Tasks

1 code implementation5 Sep 2018 Rotem Dror, Roi Reichart

Statistical significance testing plays an important role when drawing conclusions from experimental results in NLP papers.

The Hitchhiker's Guide to Testing Statistical Significance in Natural Language Processing

1 code implementation ACL 2018 Rotem Dror, Gili Baumer, Segev Shlomov, Roi Reichart

We establish the fundamental concepts of significance testing and discuss the specific aspects of NLP tasks, experimental setups and evaluation measures that affect the choice of significance tests in NLP research.

Natural Language Processing

Pivot Based Language Modeling for Improved Neural Domain Adaptation

no code implementations NAACL 2018 Yftah Ziser, Roi Reichart

Particularly, our model processes the information in the text with a sequential NN (LSTM) and its output consists of a representation vector for every input word.

Domain Adaptation Language Modelling +3

Replicability Analysis for Natural Language Processing: Testing Significance with Multiple Datasets

1 code implementation TACL 2017 Rotem Dror, Gili Baumer, Marina Bogomolov, Roi Reichart

With the ever-growing amounts of textual data from a large variety of languages, domains, and genres, it has become standard to evaluate NLP algorithms on multiple datasets in order to ensure consistent performance across heterogeneous setups.

Dependency Parsing General Classification +4

Morph-fitting: Fine-Tuning Word Vector Spaces with Simple Language-Specific Rules

no code implementations ACL 2017 Ivan Vulić, Nikola Mrkšić, Roi Reichart, Diarmuid Ó Séaghdha, Steve Young, Anna Korhonen

Morphologically rich languages accentuate two properties of distributional vector space models: 1) the difficulty of inducing accurate representations for low-frequency word forms; and 2) insensitivity to distinct lexical relations that have similar distributional signatures.

Dialogue State Tracking

Sarcasm SIGN: Interpreting Sarcasm with Sentiment Based Monolingual Machine Translation

1 code implementation ACL 2017 Lotem Peled, Roi Reichart

Sarcasm is a form of speech in which speakers say the opposite of what they truly mean in order to convey a strong sentiment.

Machine Translation Translation

Survey on the Use of Typological Information in Natural Language Processing

no code implementations COLING 2016 Helen O'Horan, Yevgeni Berzak, Ivan Vulić, Roi Reichart, Anna Korhonen

In recent years linguistic typology, which classifies the world's languages according to their functional and structural properties, has been widely used to support multilingual NLP.

Multilingual NLP Natural Language Processing

Neural Structural Correspondence Learning for Domain Adaptation

2 code implementations CONLL 2017 Yftah Ziser, Roi Reichart

Particularly, our model is a three-layer neural network that learns to encode the nonpivot features of an input example into a low-dimensional representation, so that the existence of pivot features (features that are prominent in both domains and convey useful information for the NLP task) in the example can be decoded from that representation.

Denoising Domain Adaptation +2

Effective Combination of Language and Vision Through Model Composition and the R-CCA Method

no code implementations28 Sep 2016 Hagar Loeub, Roi Reichart

We address the problem of integrating textual and visual information in vector space models for word meaning representation.

Representation Learning

A Factorized Model for Transitive Verbs in Compositional Distributional Semantics

no code implementations25 Sep 2016 Lilach Edelstein, Roi Reichart

We present a factorized compositional distributional semantics model for the representation of transitive verb constructions.

Automatic Selection of Context Configurations for Improved Class-Specific Word Representations

no code implementations CONLL 2017 Ivan Vulić, Roy Schwartz, Ari Rappoport, Roi Reichart, Anna Korhonen

With our selected context configurations, we train on only 14% (A), 26. 2% (V), and 33. 6% (N) of all dependency-based contexts, resulting in a reduced training time.

Word Similarity

SimVerb-3500: A Large-Scale Evaluation Set of Verb Similarity

1 code implementation EMNLP 2016 Daniela Gerz, Ivan Vulić, Felix Hill, Roi Reichart, Anna Korhonen

Verbs play a critical role in the meaning of sentences, but these ubiquitous words have received little attention in recent distributional semantics research.

Representation Learning

The Yahoo Query Treebank, V. 1.0

no code implementations10 May 2016 Yuval Pinter, Roi Reichart, Idan Szpektor

A description and annotation guidelines for the Yahoo Webscope release of Query Treebank, Version 1. 0, May 2016.

The Structured Weighted Violations Perceptron Algorithm

no code implementations EMNLP 2016 Rotem Dror, Roi Reichart

We present the Structured Weighted Violations Perceptron (SWVP) algorithm, a new structured prediction algorithm that generalizes the Collins Structured Perceptron (CSP).

Dependency Parsing Generalization Bounds +1

Edge-Linear First-Order Dependency Parsing with Undirected Minimum Spanning Tree Inference

no code implementations ACL 2016 Effi Levi, Roi Reichart, Ari Rappoport

The run time complexity of state-of-the-art inference algorithms in graph-based dependency parsing is super-linear in the number of input words (n).

Dependency Parsing

Separated by an Un-common Language: Towards Judgment Language Informed Vector Space Modeling

no code implementations1 Aug 2015 Ira Leviant, Roi Reichart

A common evaluation practice in the vector space models (VSMs) literature is to measure the models' ability to predict human judgments about lexical semantic relations between word pairs.

SimLex-999: Evaluating Semantic Models with (Genuine) Similarity Estimation

3 code implementations CL 2015 Felix Hill, Roi Reichart, Anna Korhonen

We present SimLex-999, a gold standard resource for evaluating distributional semantic models that improves on existing resources in several important ways.

Representation Learning

Reconstructing Native Language Typology from Foreign Language Usage

no code implementations WS 2014 Yevgeni Berzak, Roi Reichart, Boris Katz

Linguists and psychologists have long been studying cross-linguistic transfer, the influence of native language properties on linguistic performance in a foreign language.

Multi-Modal Models for Concrete and Abstract Concept Meaning

no code implementations TACL 2014 Felix Hill, Roi Reichart, Anna Korhonen

Multi-modal models that learn semantic representations from both linguistic and perceptual input outperform language-only models on a range of evaluations, and better reflect human concept acquisition.

Language Acquisition

Cannot find the paper you are looking for? You can Submit a new open access paper.