Zobrazeno 1 - 10
of 10 598
pro vyhledávání: '"A. NIMROD"'
Autor:
Doveh, Sivan, Shabtay, Nimrod, Lin, Wei, Schwartz, Eli, Kuehne, Hilde, Giryes, Raja, Feris, Rogerio, Karlinsky, Leonid, Glass, James, Arbelle, Assaf, Ullman, Shimon, Mirza, M. Jehanzeb
Vision-Language Models (VLMs) have shown remarkable capabilities across diverse visual tasks, including image recognition, video understanding, and Visual Question Answering (VQA) when explicitly trained for these tasks. Despite these advances, we fi
Externí odkaz:
http://arxiv.org/abs/2411.13317
Compared to rigid hands, underactuated compliant hands offer greater adaptability to object shapes, provide stable grasps, and are often more cost-effective. However, they introduce uncertainties in hand-object interactions due to their inherent comp
Externí odkaz:
http://arxiv.org/abs/2411.06408
Lately, there has been a surge in interest surrounding generative modeling of time series data. Most existing approaches are designed either to process short sequences or to handle long-range sequences. This dichotomy can be attributed to gradient is
Externí odkaz:
http://arxiv.org/abs/2410.19538
Autor:
Turetzky, Arnon, Shabtay, Nimrod, Shechtman, Slava, Aronowitz, Hagai, Haws, David, Hoory, Ron, Dekel, Avihu
The success of autoregressive transformer models with discrete tokens has inspired quantization-based approaches for continuous modalities, though these often limit reconstruction quality. We therefore introduce SALAD, a per-token latent diffusion mo
Externí odkaz:
http://arxiv.org/abs/2410.16048
Autor:
Shabtay, Nimrod, Polo, Felipe Maia, Doveh, Sivan, Lin, Wei, Mirza, M. Jehanzeb, Chosen, Leshem, Yurochkin, Mikhail, Sun, Yuekai, Arbelle, Assaf, Karlinsky, Leonid, Giryes, Raja
The large-scale training of multi-modal models on data scraped from the web has shown outstanding utility in infusing these models with the required world knowledge to perform effectively on multiple downstream tasks. However, one downside of scrapin
Externí odkaz:
http://arxiv.org/abs/2410.10783
This study investigates the impact of increased debt servicing costs on household consumption resulting from monetary policy tightening. It utilizes observational panel microdata on all mortgage holders in Israel and leverages quasi-exogenous variati
Externí odkaz:
http://arxiv.org/abs/2410.02445
Autor:
Bauza, Maria, Chen, Jose Enrique, Dalibard, Valentin, Gileadi, Nimrod, Hafner, Roland, Martins, Murilo F., Moore, Joss, Pevceviciute, Rugile, Laurens, Antoine, Rao, Dushyant, Zambelli, Martina, Riedmiller, Martin, Scholz, Jon, Bousmalis, Konstantinos, Nori, Francesco, Heess, Nicolas
We present DemoStart, a novel auto-curriculum reinforcement learning method capable of learning complex manipulation behaviors on an arm equipped with a three-fingered robotic hand, from only a sparse reward and a handful of demonstrations in simulat
Externí odkaz:
http://arxiv.org/abs/2409.06613
Autor:
Dvir, Nimrod
This study explores the relationship between textual features and Information Engagement (IE) on digital platforms. It highlights the impact of computational linguistics and analytics on user interaction. The READ model is introduced to quantify key
Externí odkaz:
http://arxiv.org/abs/2409.00064
Autor:
Panda, Kartik, Potashnikov, Daniel, Pesach, Asaf, Barbier, Maxime, Eyal, Anna, Ouisse, Thierry, Keren, Amit, Bachar, Nimrod
We report the investigation of electronic collective modes in rare-earth-based magnets (Mo$_{2/3}$RE$_{1/3}$)$_2$AlC (also known as RE-$i$-MAX phases), where RE=Gd, Yb, and Dy, using single crystal samples. A detailed investigation of the Raman spect
Externí odkaz:
http://arxiv.org/abs/2408.02436
One of the fundamental representation learning tasks is unsupervised sequential disentanglement, where latent codes of inputs are decomposed to a single static factor and a sequence of dynamic factors. To extract this latent information, existing met
Externí odkaz:
http://arxiv.org/abs/2406.18131