Itzik Malkiel

Unsupervised Topic-Conditional Extractive Summarization

Itzik Malkiel, Yakir Yehuda, Jonathan Ephrath, Ori Kats et autres

Summarization techniques strive to create a concise summary that conveys the essential information from a given document. However, these techniques are often inadequate for summarizing longer documents containing multiple pages of semantically complex content with various topics. Hence, in this work, we …

gb, il (code pays fourni par la source)

SEGLLM: Topic-Oriented Call Segmentation Via LLM-Based Conversation Synthesis

Itzik Malkiel, Uri Alon, Yakir Yehuda, Shahar Keren et autres

Transcriptions of phone calls are of significant value across diverse fields, such as sales, customer service, healthcare, and law enforcement. Nevertheless, the analysis of these recorded conversations can be an arduous and time-intensive process, especially when dealing with long and multifaceted dialogues. …

gb, il (code pays fourni par la source)

InterrogateLLM: Zero-Resource Hallucination Detection in LLM-Generated Answers

Yakir Yehuda, Itzik Malkiel, Oren Barkan, Jonathan Weill et autres

Despite the many advances of Large Language Models (LLMs) and their unprecedented rapid evolution, their impact and integration into every facet of our daily lives is limited due to various reasons. One critical factor hindering their widespread adoption is the occurrence of …

InterrogateLLM: Zero-Resource Hallucination Detection in LLM-Generated Answers

Yakir Yehuda, Itzik Malkiel, Oren Barkan, Jonathan Weill et autres

Yakir Yehuda, Itzik Malkiel, Oren Barkan, Jonathan Weill, Royi Ronen, Noam Koenigstein. Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). 2024.

textual item similarty (video games and wines datasets)

Itzik Malkiel

textual item similarty (video games and wines datasets)

Itzik Malkiel

Harnessing GPT for Topic-Based Call Segmentation in Microsoft Dynamics 365 Sales

Itzik Malkiel, Uri Alon, Yakir Yehuda, Shahar Keren et autres

Transcriptions of phone calls hold significant value in sales, customer service, healthcare, law enforcement, and more. However, analyzing recorded conversations can be a time-consuming process, especially for complex dialogues. In Microsoft Dynamics 365 Sales, a novel system, named GPT-Calls, is applied for …

il (code pays fourni par la source)

Efficient Discovery and Effective Evaluation of Visual Perceptual Similarity: A Benchmark and Beyond

Oren Barkan, Tal Reiss, Jonathan Weill, Ori Katz et autres

Visual similarity discovery (VSD) is an important task with broad e-commerce applications. Given an image of a certain object, the goal of VSD is to retrieve images of different objects with high perceptual visual similarity. Although being a highly addressed problem, the …

gb, il (code pays fourni par la source)

Efficient Discovery and Effective Evaluation of Visual Perceptual Similarity: A Benchmark and Beyond

Oren Barkan, Tal Reiss, Jonathan Weill, Ori Katz et autres

Visual similarities discovery (VSD) is an important task with broad e-commerce applications. Given an image of a certain object, the goal of VSD is to retrieve images of different objects with high perceptual visual similarity. Although being a highly addressed problem, the …

Representation Learning via Variational Bayesian Networks

Oren Barkan, Avi Caciularu, Idan Rejwan, Ori Katz et autres

We present Variational Bayesian Network (VBN) - a novel Bayesian entity representation learning model that utilizes hierarchical and relational side information and is particularly useful for modeling entities in the ``long-tail'', where the data is scarce. VBN provides better modeling for long-tail …

GPT-Calls: Enhancing Call Segmentation and Tagging by Generating Synthetic Conversations via Large Language Models

Itzik Malkiel, Uri Alon, Yakir Yehuda, Shahar Keren et autres

Transcriptions of phone calls are of significant value across diverse fields, such as sales, customer service, healthcare, and law enforcement. Nevertheless, the analysis of these recorded conversations can be an arduous and time-intensive process, especially when dealing with extended or multifaceted dialogues. …

MetricBERT: Text Representation Learning via Self-Supervised Triplet Training

Itzik Malkiel, Dvir Ginzburg, Oren Barkan, Avi Caciularu et autres

We present MetricBERT, a BERT-based model that learns to embed text under a well-defined similarity metric while simultaneously adhering to the ``traditional'' masked-language task. We focus on downstream tasks of learning similarities for recommendations where we show that MetricBERT outperforms state-of-the-art alternatives, …