12 citations · 15 across the 4 of their papers we have counts for
9 papers · 1 filter
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…
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…
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…
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…
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…
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…