4 citations · 9 across the 4 of their papers we have counts for
6 papers
Zero-Shot Text Classification with Self-Training
Ariel Gera, Alon Halfon, Eyal Shnarch +3
Recent advances in large pretrained language models have increased attention to zero-shot text classification. In particular, models finetuned on natural language inference dataset…
Heuristic-based Inter-training to Improve Few-shot Multi-perspective Dialog Summarization
Benjamin Sznajder, Chulaka Gunasekara, Guy Lev +3
Many organizations require their customer-care agents to manually summarize their conversations with customers. These summaries are vital for decision making purposes of the organi…
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…
Unsupervised Expressive Rules Provide Explainability and Assist Human Experts Grasping New Domains
Eyal Shnarch, Leshem Choshen, Guy Moshkowich +2
Approaching new data can be quite deterrent; you do not know how your categories of interest are realized in it, commonly, there is no labeled data at hand, and the performance of…
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…
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…