Zobrazeno 1 - 10
of 2 208
pro vyhledávání: '"Bethge, P"'
Autor:
Ghosh, Adhiraj, Dziadzio, Sebastian, Prabhu, Ameya, Udandarao, Vishaal, Albanie, Samuel, Bethge, Matthias
Traditional fixed test sets fall short in evaluating open-ended capabilities of foundation models. To address this, we propose ONEBench(OpeN-Ended Benchmarking), a new testing paradigm that consolidates individual evaluation datasets into a unified,
Externí odkaz:
http://arxiv.org/abs/2412.06745
Autor:
Dziadzio, Sebastian, Udandarao, Vishaal, Roth, Karsten, Prabhu, Ameya, Akata, Zeynep, Albanie, Samuel, Bethge, Matthias
Model merging combines multiple expert models - finetuned from a base foundation model on diverse tasks and domains - into a single, more capable model. However, most existing model merging approaches assume that all experts are available simultaneou
Externí odkaz:
http://arxiv.org/abs/2412.06712
Humans excel at detecting and segmenting moving objects according to the Gestalt principle of "common fate". Remarkably, previous works have shown that human perception generalizes this principle in a zero-shot fashion to unseen textures or random do
Externí odkaz:
http://arxiv.org/abs/2411.01505
Autor:
Binz, Marcel, Akata, Elif, Bethge, Matthias, Brändle, Franziska, Callaway, Fred, Coda-Forno, Julian, Dayan, Peter, Demircan, Can, Eckstein, Maria K., Éltető, Noémi, Griffiths, Thomas L., Haridi, Susanne, Jagadish, Akshay K., Ji-An, Li, Kipnis, Alexander, Kumar, Sreejan, Ludwig, Tobias, Mathony, Marvin, Mattar, Marcelo, Modirshanechi, Alireza, Nath, Surabhi S., Peterson, Joshua C., Rmus, Milena, Russek, Evan M., Saanum, Tankred, Scharfenberg, Natalia, Schubert, Johannes A., Buschoff, Luca M. Schulze, Singhi, Nishad, Sui, Xin, Thalmann, Mirko, Theis, Fabian, Truong, Vuong, Udandarao, Vishaal, Voudouris, Konstantinos, Wilson, Robert, Witte, Kristin, Wu, Shuchen, Wulff, Dirk, Xiong, Huadong, Schulz, Eric
Establishing a unified theory of cognition has been a major goal of psychology. While there have been previous attempts to instantiate such theories by building computational models, we currently do not have one model that captures the human mind in
Externí odkaz:
http://arxiv.org/abs/2410.20268
Autor:
Mayilvahanan, Prasanna, Zimmermann, Roland S., Wiedemer, Thaddäus, Rusak, Evgenia, Juhos, Attila, Bethge, Matthias, Brendel, Wieland
Out-of-Domain (OOD) generalization is the ability of a model trained on one or more domains to generalize to unseen domains. In the ImageNet era of computer vision, evaluation sets for measuring a model's OOD performance were designed to be strictly
Externí odkaz:
http://arxiv.org/abs/2410.08258
Autor:
Öncel, Fırat, Bethge, Matthias, Ermis, Beyza, Ravanelli, Mirco, Subakan, Cem, Yıldız, Çağatay
In the last decade, the generalization and adaptation abilities of deep learning models were typically evaluated on fixed training and test distributions. Contrary to traditional deep learning, large language models (LLMs) are (i) even more overparam
Externí odkaz:
http://arxiv.org/abs/2410.05581
Autor:
Roth, Karsten, Udandarao, Vishaal, Dziadzio, Sebastian, Prabhu, Ameya, Cherti, Mehdi, Vinyals, Oriol, Hénaff, Olivier, Albanie, Samuel, Bethge, Matthias, Akata, Zeynep
Multimodal foundation models serve numerous applications at the intersection of vision and language. Still, despite being pretrained on extensive data, they become outdated over time. To keep models updated, research into continual pretraining mainly
Externí odkaz:
http://arxiv.org/abs/2408.14471
Autor:
Li, Hao, Alemán, Tanausú del Pino, Bueno, Javier Trujillo, Ishikawa, Ryohko, Ballester, Ernest Alsina, McKenzie, David E., Belluzzi, Luca, Song, Donguk, Okamoto, Takenori J., Kobayashi, Ken, Rachmeler, Laurel A., Bethge, Christian, Auchère, Frédéric
We apply the HanleRT Tenerife Inversion Code to the spectro-polarimetric observations obtained by the Chromospheric LAyer SpectroPolarimeter. This suborbital space experiment measured the variation with wavelength of the four Stokes parameters in the
Externí odkaz:
http://arxiv.org/abs/2408.06094
Autor:
Press, Ori, Hochlehnert, Andreas, Prabhu, Ameya, Udandarao, Vishaal, Press, Ofir, Bethge, Matthias
Thousands of new scientific papers are published each month. Such information overload complicates researcher efforts to stay current with the state-of-the-art as well as to verify and correctly attribute claims. We pose the following research questi
Externí odkaz:
http://arxiv.org/abs/2407.12861
With the advent and recent ubiquity of foundation models, continual learning (CL) has recently shifted from continual training from scratch to the continual adaptation of pretrained models, seeing particular success on rehearsal-free CL benchmarks (R
Externí odkaz:
http://arxiv.org/abs/2406.09384