Zobrazeno 1 - 10
of 12 011
pro vyhledávání: '"P. Mor"'
Autor:
Nacson, Mor Shpigel, Aberdam, Aviad, Ganz, Roy, Avraham, Elad Ben, Golts, Alona, Kittenplon, Yair, Mazor, Shai, Litman, Ron
Vision-Language Models (VLMs) excel in diverse visual tasks but face challenges in document understanding, which requires fine-grained text processing. While typical visual tasks perform well with low-resolution inputs, reading-intensive applications
Externí odkaz:
http://arxiv.org/abs/2412.08746
Spatiotemporal dynamics pervade the natural sciences, from the morphogen dynamics underlying patterning in animal pigmentation to the protein waves controlling cell division. A central challenge lies in understanding how controllable parameters induc
Externí odkaz:
http://arxiv.org/abs/2412.03496
Autor:
Gosetti, Valentina, Cervantes-Villanueva, Jorge, Mor, Selene, Sangalli, Davide, García-Cristóbal, Alberto, Molina-Sánchez, Alejandro, Agekyan, Vadim F., Tuniz, Manuel, Puntel, Denny, Bronsch, Wibke, Cilento, Federico, Pagliara, Stefania
Resolving the early-stage dynamics of exciton formation following non-resonant photoexcitation in time, energy, and momentum is quite challenging due to their inherently fast timescales and the proximity of the excitonic state to the bottom of the co
Externí odkaz:
http://arxiv.org/abs/2412.02507
Autor:
Bercovich, Akhiad, Ronen, Tomer, Abramovich, Talor, Ailon, Nir, Assaf, Nave, Dabbah, Mohammad, Galil, Ido, Geifman, Amnon, Geifman, Yonatan, Golan, Izhak, Haber, Netanel, Karpas, Ehud, Koren, Roi, Levy, Itay, Molchanov, Pavlo, Mor, Shahar, Moshe, Zach, Nabwani, Najeeb, Puny, Omri, Rubin, Ran, Schen, Itamar, Shahaf, Ido, Tropp, Oren, Argov, Omer Ullman, Zilberstein, Ran, El-Yaniv, Ran
Large language models (LLMs) have demonstrated remarkable capabilities, but their adoption is limited by high computational costs during inference. While increasing parameter counts enhances accuracy, it also widens the gap between state-of-the-art c
Externí odkaz:
http://arxiv.org/abs/2411.19146
We evaluate how well Large Language Models (LLMs) latently recall and compose facts to answer multi-hop queries like "In the year Scarlett Johansson was born, the Summer Olympics were hosted in the country of". One major challenge in evaluating this
Externí odkaz:
http://arxiv.org/abs/2411.16679
This paper examines how large language models (LLMs) can help people write constructive comments in online debates on divisive social issues and whether the notions of constructiveness vary across cultures. Through controlled experiments with 600 par
Externí odkaz:
http://arxiv.org/abs/2411.03295
Autor:
Levy, Amit Arnold, Geva, Mor
Large language models (LLMs) frequently make errors when handling even simple numerical problems, such as comparing two small numbers. A natural hypothesis is that these errors stem from how LLMs represent numbers, and specifically, whether their rep
Externí odkaz:
http://arxiv.org/abs/2410.11781
How are Reddit communities responding to AI-generated content? We explored this question through a large-scale analysis of subreddit community rules and their change over time. We collected the metadata and community rules for over 300,000 public sub
Externí odkaz:
http://arxiv.org/abs/2410.11698
Continuous prompts, or "soft prompts", are a widely-adopted parameter-efficient tuning strategy for large language models, but are often less favorable due to their opaque nature. Prior attempts to interpret continuous prompts relied on projecting in
Externí odkaz:
http://arxiv.org/abs/2410.11660
Facial expression recognition (FER) has emerged as a promising approach to the development of emotion-aware intelligent systems. The performance of FER in multiple domains is continuously being improved, especially through advancements in data-driven
Externí odkaz:
http://arxiv.org/abs/2410.09743