32 citations · 65 across the 17 of their papers we have counts for
10 papers · 1 filter
Will it Merge? On The Causes of Model Mergeability
Adir Rahamim, Asaf Yehudai, Boaz Carmeli +3
Model merging has emerged as a promising technique for combining multiple fine-tuned models into a single multitask model without retraining. However, the factors that determine wh…
Unsupervised Translation of Emergent Communication
Ido Levy, Orr Paradise, Boaz Carmeli +3
Emergent Communication (EC) provides a unique window into the language systems that emerge autonomously when agents are trained to jointly achieve shared goals. However, it is diff…
Genie: Achieving Human Parity in Content-Grounded Datasets Generation
Asaf Yehudai, Boaz Carmeli, Yosi Mass +5
The lack of high-quality data for content-grounded generation tasks has been identified as a major obstacle to advancing these tasks. To address this gap, we propose Genie, a novel…
QAID: Question Answering Inspired Few-shot Intent Detection
Asaf Yehudai, Matan Vetzler, Yosi Mass +3
Intent detection with semantically similar fine-grained intents is a challenging task. To address it, we reformulate intent detection as a question-answering retrieval task by trea…
Measuring the Measuring Tools: An Automatic Evaluation of Semantic Metrics for Text Corpora
George Kour, Samuel Ackerman, Orna Raz +3
The ability to compare the semantic similarity between text corpora is important in a variety of natural language processing applications. However, standard methods for evaluating…
Exploration of the Usage of Color Terms by Color-blind Participants in Online Discussion Platforms
Ella Rabinovich, Boaz Carmeli
Prominent questions about the role of sensory vs. linguistic input in the way we acquire and use language have been extensively studied in the psycholinguistic literature. However,…
Understanding the Properties of Generated Corpora
Naama Zwerdling, Segev Shlomov, Esther Goldbraich +6
Models for text generation have become focal for many research tasks and especially for the generation of sentence corpora. However, understanding the properties of an automaticall…
A new data augmentation method for intent classification enhancement and its application on spoken conversation datasets
Zvi Kons, Aharon Satt, Hong-Kwang Kuo +4
Intent classifiers are vital to the successful operation of virtual agent systems. This is especially so in voice activated systems where the data can be noisy with many ambiguous…
Improved Goal Oriented Dialogue via Utterance Generation and Look Ahead
Eyal Ben-David, Boaz Carmeli, Ateret Anaby-Tavor
Goal oriented dialogue systems have become a prominent customer-care interaction channel for most businesses. However, not all interactions are smooth, and customer intent misunder…
Not Enough Data? Deep Learning to the Rescue!
Ateret Anaby-Tavor, Boaz Carmeli, Esther Goldbraich +5
Based on recent advances in natural language modeling and those in text generation capabilities, we propose a novel data augmentation method for text classification tasks. We use a…