activity
20182022
most citedFusing finetuned models for better pretraining

12 citations · 19 across the 3 of their papers we have counts for

collaborators

5 papers

cs.CL20222 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.CL202212 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

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.CL2019

Automatic Argument Quality Assessment -- New Datasets and Methods

Assaf Toledo, Shai Gretz, Edo Cohen-Karlik +6

We explore the task of automatic assessment of argument quality. To that end, we actively collected 6.3k arguments, more than a factor of five compared to previously examined data.…

cs.CL20185 cited

What did you Mention? A Large Scale Mention Detection Benchmark for Spoken and Written Text

Yosi Mass, Lili Kotlerman, Shachar Mirkin +3

We describe a large, high-quality benchmark for the evaluation of Mention Detection tools. The benchmark contains annotations of both named entities as well as other types of entit…