activity
20192022
most citedAre You Convinced? Choosing the More Convincing Evidence with a Siamese Network

3 citations · 4 across the 2 of their papers we have counts for

collaborators

6 papers

cs.CL20221 cited

Cluster & Tune: Boost Cold Start Performance in Text Classification

Eyal Shnarch, Ariel Gera, Alon Halfon +4

In real-world scenarios, a text classification task often begins with a cold start, when labeled data is scarce. In such cases, the common practice of fine-tuning pre-trained model…

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.CL2019

Corpus Wide Argument Mining -- a Working Solution

Liat Ein-Dor, Eyal Shnarch, Lena Dankin +10

One of the main tasks in argument mining is the retrieval of argumentative content pertaining to a given topic. Most previous work addressed this task by retrieving a relatively sm…

cs.CL2019

A Dataset of General-Purpose Rebuttal

Matan Orbach, Yonatan Bilu, Ariel Gera +8

In Natural Language Understanding, the task of response generation is usually focused on responses to short texts, such as tweets or a turn in a dialog. Here we present a novel tas…

cs.CL2019

Towards Effective Rebuttal: Listening Comprehension using Corpus-Wide Claim Mining

Tamar Lavee, Matan Orbach, Lili Kotlerman +8

Engaging in a live debate requires, among other things, the ability to effectively rebut arguments claimed by your opponent. In particular, this requires identifying these argument…

cs.LG20193 cited

Are You Convinced? Choosing the More Convincing Evidence with a Siamese Network

Martin Gleize, Eyal Shnarch, Leshem Choshen +4

With the advancement in argument detection, we suggest to pay more attention to the challenging task of identifying the more convincing arguments. Machines capable of responding an…