1 code implementation • 25 Jan 2024 • Elron Bandel, Yotam Perlitz, Elad Venezian, Roni Friedman-Melamed, Ofir Arviv, Matan Orbach, Shachar Don-Yehyia, Dafna Sheinwald, Ariel Gera, Leshem Choshen, Michal Shmueli-Scheuer, Yoav Katz
In the dynamic landscape of generative NLP, traditional text processing pipelines limit research flexibility and reproducibility, as they are tailored to specific dataset, task, and model combinations.
no code implementations • 9 Feb 2023 • Almog Gueta, Elad Venezian, Colin Raffel, Noam Slonim, Yoav Katz, Leshem Choshen
Notably, we show that language models that have been finetuned on the same dataset form a tight cluster in the weight space, while models finetuned on different datasets from the same underlying task form a looser cluster.
no code implementations • 2 Dec 2022 • Shachar Don-Yehiya, Elad Venezian, Colin Raffel, Noam Slonim, Yoav Katz, Leshem Choshen
We propose a new paradigm to continually evolve pretrained models, denoted ColD Fusion.
no code implementations • 31 Oct 2022 • Leshem Choshen, Elad Venezian, Shachar Don-Yehia, Noam Slonim, Yoav Katz
Such a model, finetuned on some source dataset, may provide a better starting point for a new finetuning process on a desired target dataset.
2 code implementations • 6 Apr 2022 • Leshem Choshen, Elad Venezian, Noam Slonim, Yoav Katz
We also show that fusing is often better than intertraining.
no code implementations • EMNLP (ACL) 2021 • Roy Bar-Haim, Yoav Kantor, Elad Venezian, Yoav Katz, Noam Slonim
Engaging in a live debate requires a diverse set of skills, and Project Debater has been developed accordingly as a collection of components, each designed to perform a specific subtask.
no code implementations • ACL 2021 • Roy Bar-Haim, Liat Ein-Dor, Matan Orbach, Elad Venezian, Noam Slonim
We present a complete pipeline of a debating system, and discuss the information flow and the interaction between the various components.
no code implementations • IJCNLP 2019 • Assaf Toledo, Shai Gretz, Edo Cohen-Karlik, Roni Friedman, Elad Venezian, Dan Lahav, Michal Jacovi, Ranit Aharonov, Noam Slonim
In spite of the inherent subjective nature of the task, both annotation schemes led to surprisingly consistent results.
no code implementations • 3 Sep 2019 • Assaf Toledo, Shai Gretz, Edo Cohen-Karlik, Roni Friedman, Elad Venezian, Dan Lahav, Michal Jacovi, Ranit Aharonov, Noam Slonim
In spite of the inherent subjective nature of the task, both annotation schemes led to surprisingly consistent results.
no code implementations • ACL 2018 • Liat Ein Dor, Yosi Mass, Alon Halfon, Elad Venezian, Ilya Shnayderman, Ranit Aharonov, Noam Slonim
We train a triplet network to embed sentences from the same section closer.
no code implementations • 23 Jan 2018 • Yosi Mass, Lili Kotlerman, Shachar Mirkin, Elad Venezian, Gera Witzling, Noam Slonim
We describe a large, high-quality benchmark for the evaluation of Mention Detection tools.
no code implementations • LREC 2018 • Shachar Mirkin, Michal Jacovi, Tamar Lavee, Hong-Kwang Kuo, Samuel Thomas, Leslie Sager, Lili Kotlerman, Elad Venezian, Noam Slonim
This paper describes an English audio and textual dataset of debating speeches, a unique resource for the growing research field of computational argumentation and debating technologies.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +1