activity
20192023
most citedFast End-to-End Wikification

13 citations · 33 across the 11 of their papers we have counts for

collaborators

14 papers

cs.LG2023★ 1 cited

Knowledge is a Region in Weight Space for Fine-tuned Language Models

Almog Gueta, Elad Venezian, Colin Raffel +3

Research on neural networks has focused on understanding a single model trained on a single dataset. However, relatively little is known about the relationships between different m…

cs.CL2022

SimpleStyle: An Adaptable Style Transfer Approach

Elron Bandel, Yoav Katz, Noam Slonim +1

Attribute-controlled text rewriting, also known as text style-transfer, has a crucial role in regulating attributes and biases of textual training data and a machine generated text…

cs.LG2022

ColD Fusion: Collaborative Descent for Distributed Multitask Finetuning

Shachar Don-Yehiya, Elad Venezian, Colin Raffel +3

We propose a new paradigm to continually evolve pretrained models, denoted ColD Fusion. It provides the benefits of multitask learning but leverages distributed computation with li…

cs.CL2022★ 2 cited

Where to start? Analyzing the potential value of intermediate models

Leshem Choshen, Elad Venezian, Shachar Don-Yehia +2

Previous studies observed that finetuned models may be better base models than the vanilla pretrained model. Such a model, finetuned on some source dataset, may provide a better st…

cs.CL2022★ 2 cited

Label Sleuth: From Unlabeled Text to a Classifier in a Few Hours

Eyal Shnarch, Alon Halfon, Ariel Gera +19

Text classification can be useful in many real-world scenarios, saving a lot of time for end users. However, building a custom classifier typically requires coding skills and ML kn…

cs.CL2022★ 1 cited

VIRATrustData: A Trust-Annotated Corpus of Human-Chatbot Conversations About COVID-19 Vaccines

Roni Friedman, João Sedoc, Shai Gretz +5

Public trust in medical information is crucial for successful application of public health policies such as vaccine uptake. This is especially true when the information is offered…

cs.CL2022

Multi-Domain Targeted Sentiment Analysis

Orith Toledo-Ronen, Matan Orbach, Yoav Katz +1

Targeted Sentiment Analysis (TSA) is a central task for generating insights from consumer reviews. Such content is extremely diverse, with sites like Amazon or Yelp containing revi…

cs.CL2022★ 2 cited

Benchmark Data and Evaluation Framework for Intent Discovery Around COVID-19 Vaccine Hesitancy

Shai Gretz, Assaf Toledo, Roni Friedman +7

The COVID-19 pandemic has made a huge global impact and cost millions of lives. As COVID-19 vaccines were rolled out, they were quickly met with widespread hesitancy. To address th…

cs.CL2022★ 12 cited

Fusing finetuned models for better pretraining

Leshem Choshen, Elad Venezian, Noam Slonim +1

Pretrained models are the standard starting point for training. This approach consistently outperforms the use of a random initialization. However, pretraining is a costly endeavou…

cs.CL2021

Overview of the 2021 Key Point Analysis Shared Task

Roni Friedman, Lena Dankin, Yufang Hou +3

We describe the 2021 Key Point Analysis (KPA-2021) shared task on key point analysis that we organized as a part of the 8th Workshop on Argument Mining (ArgMining 2021) at EMNLP 20…

cs.CL2021

Project Debater APIs: Decomposing the AI Grand Challenge

Roy Bar-Haim, Yoav Kantor, Elad Venezian +2

Project Debater was revealed in 2019 as the first AI system that can debate human experts on complex topics. Engaging in a live debate requires a diverse set of skills, and Project…

cs.CL2020

YASO: A Targeted Sentiment Analysis Evaluation Dataset for Open-Domain Reviews

Matan Orbach, Orith Toledo-Ronen, Artem Spector +3

Current TSA evaluation in a cross-domain setup is restricted to the small set of review domains available in existing datasets. Such an evaluation is limited, and may not reflect t…

cs.CL2019★ 13 cited

Fast End-to-End Wikification

Ilya Shnayderman, Liat Ein-Dor, Yosi Mass +7

Wikification of large corpora is beneficial for various NLP applications. Existing methods focus on quality performance rather than run-time, and are therefore non-feasible for lar…

cs.CL2019

Learning to combine Grammatical Error Corrections

Yoav Kantor, Yoav Katz, Leshem Choshen +5

The field of Grammatical Error Correction (GEC) has produced various systems to deal with focused phenomena or general text editing. We propose an automatic way to combine black-bo…