Zobrazeno 1 - 10
of 2 126
pro vyhledávání: '"Oshri, A."'
The estimation of Conditional Average Treatment Effects (CATE) is crucial for understanding the heterogeneity of treatment effects in clinical trials. We evaluate the performance of common methods, including causal forests and various meta-learners,
Externí odkaz:
http://arxiv.org/abs/2407.03690
We introduce the causal responders detection (CARD), a novel method for responder analysis that identifies treated subjects who significantly respond to a treatment. Leveraging recent advances in conformal prediction, CARD employs machine learning te
Externí odkaz:
http://arxiv.org/abs/2406.17571
Autor:
Naparstek, Oshri, Pony, Roi, Shapira, Inbar, Dahood, Foad Abo, Azulai, Ophir, Yaroker, Yevgeny, Rubinstein, Nadav, Lysak, Maksym, Staar, Peter, Nassar, Ahmed, Livathinos, Nikolaos, Auer, Christoph, Amrani, Elad, Friedman, Idan, Prince, Orit, Burshtein, Yevgeny, Goldfarb, Adi Raz, Barzelay, Udi
In recent years, the challenge of extracting information from business documents has emerged as a critical task, finding applications across numerous domains. This effort has attracted substantial interest from both industry and academy, highlighting
Externí odkaz:
http://arxiv.org/abs/2405.00505
In this work we propose a novel annotation scheme which factors hate speech into five separate discursive categories. To evaluate our scheme, we construct a corpus of over 2.9M Twitter posts containing hateful expressions directed at Jews, and annota
Externí odkaz:
http://arxiv.org/abs/2311.03969
We study the emergence of fluid flow in a closed chamber that is driven by dynamical deformations of an elastic sheet. The sheet is compressed between the sidewalls of the chamber and partitions it into two separate parts, each of which is initially
Externí odkaz:
http://arxiv.org/abs/2307.07186
An important aspect in developing language models that interact with humans is aligning their behavior to be useful and unharmful for their human users. This is usually achieved by tuning the model in a way that enhances desired behaviors and inhibit
Externí odkaz:
http://arxiv.org/abs/2304.11082
Physics-based simulation of mesh based domains remains a challenging task. State-of-the-art techniques can produce realistic results but require expert knowledge. A major bottleneck in many approaches is the step of integrating a potential energy in
Externí odkaz:
http://arxiv.org/abs/2301.11841
Autor:
Alfassy, Amit, Arbelle, Assaf, Halimi, Oshri, Harary, Sivan, Herzig, Roei, Schwartz, Eli, Panda, Rameswar, Dolfi, Michele, Auer, Christoph, Saenko, Kate, Staar, PeterW. J., Feris, Rogerio, Karlinsky, Leonid
Foundation Models (FMs) have demonstrated unprecedented capabilities including zero-shot learning, high fidelity data synthesis, and out of domain generalization. However, as we show in this paper, FMs still have poor out-of-the-box performance on ex
Externí odkaz:
http://arxiv.org/abs/2209.03648
Autor:
Naparstek, Oshri, Azulai, Ophir, Rotman, Daniel, Burshtein, Yevgeny, Staar, Peter, Barzelay, Udi
For digitizing or indexing physical documents, Optical Character Recognition (OCR), the process of extracting textual information from scanned documents, is a vital technology. When a document is visually damaged or contains non-textual elements, exi
Externí odkaz:
http://arxiv.org/abs/2207.01220
Autor:
Halimi, Oshri, Prada, Fabian, Stuyck, Tuur, Xiang, Donglai, Bagautdinov, Timur, Wen, He, Kimmel, Ron, Shiratori, Takaaki, Wu, Chenglei, Sheikh, Yaser
Virtual telepresence is the future of online communication. Clothing is an essential part of a person's identity and self-expression. Yet, ground truth data of registered clothes is currently unavailable in the required resolution and accuracy for tr
Externí odkaz:
http://arxiv.org/abs/2206.03373