Zobrazeno 1 - 10
of 778 719
pro vyhledávání: '"COHEN, A."'
Publikováno v:
EMNLP 2024
While coreference resolution is traditionally used as a component in individual document understanding, in this work we take a more global view and explore what can we learn about a domain from the set of all document-level coreference relations that
Externí odkaz:
http://arxiv.org/abs/2410.17051
Autor:
Ran-Milo, Yuval, Lumbroso, Eden, Cohen-Karlik, Edo, Giryes, Raja, Globerson, Amir, Cohen, Nadav
Structured state space models (SSMs), the core engine behind prominent neural networks such as S4 and Mamba, are linear dynamical systems adhering to a specified structure, most notably diagonal. In contrast to typical neural network modules, whose p
Externí odkaz:
http://arxiv.org/abs/2410.14067
Autor:
Reuben, Maor, Slobodin, Ortal, Elyshar, Aviad, Cohen, Idan-Chaim, Braun-Lewensohn, Orna, Cohen, Odeya, Puzis, Rami
Human-like personality traits have recently been discovered in large language models, raising the hypothesis that their (known and as yet undiscovered) biases conform with human latent psychological constructs. While large conversational models may b
Externí odkaz:
http://arxiv.org/abs/2409.19655
Autor:
Cohen, Cassandra A., Cohen, William W.
We propose a variant of chain of thought (CoT) prompting called Program Trace Prompting that makes explanations more observable while preserving the power, generality and flexibility of CoT. In our approach, few-shot CoT demonstrations are wrapped in
Externí odkaz:
http://arxiv.org/abs/2409.15359
Fokker-Planck equations (forward Kolmogorov equations) evolve probability densities in time from an initial condition. For distributions over the real line, these evolution equations can sometimes be transformed into dynamics over the incomplete zero
Externí odkaz:
http://arxiv.org/abs/2411.00700
Autor:
Campbell, Declan, Rane, Sunayana, Giallanza, Tyler, De Sabbata, Nicolò, Ghods, Kia, Joshi, Amogh, Ku, Alexander, Frankland, Steven M., Griffiths, Thomas L., Cohen, Jonathan D., Webb, Taylor W.
Recent work has documented striking heterogeneity in the performance of state-of-the-art vision language models (VLMs), including both multimodal language models and text-to-image models. These models are able to describe and generate a diverse array
Externí odkaz:
http://arxiv.org/abs/2411.00238
Autor:
Chang, Hsien-Chih, Cohen-Addad, Vincent, Conroy, Jonathan, Le, Hung, Pilipczuk, Marcin, Pilipczuk, Michał
Cohen-Addad, Le, Pilipczuk, and Pilipczuk [CLPP23] recently constructed a stochastic embedding with expected $1+\varepsilon$ distortion of $n$-vertex planar graphs (with polynomial aspect ratio) into graphs of treewidth $O(\varepsilon^{-1}\log^{13} n
Externí odkaz:
http://arxiv.org/abs/2411.00216
Optimization in deep learning remains poorly understood, even in the simple setting of deterministic (i.e. full-batch) training. A key difficulty is that much of an optimizer's behavior is implicitly determined by complex oscillatory dynamics, referr
Externí odkaz:
http://arxiv.org/abs/2410.24206
Autor:
Souverin, Thierry, Neveu, Jérémy, Betoule, Marc, Bongard, Sébastien, Stubbs, Christopher W., Urbach, Elana, Brownsberger, Sasha, Blanc, Pierre Éric, Tanugi, Johann Cohen, Dagoret-Campagne, Sylvie, Feinstein, Fabrice, Hardin, Delphine, Juramy, Claire, Guillou, Laurent Le, Van Suu, Auguste Le, Moniez, Marc, Plez, Bertrand, Regnault, Nicolas, Sepulveda, Eduardo, Sommer, Kélian
The measurement of type Ia supernovae magnitudes provides cosmological distances, which can be used to constrain dark energy parameters. Large photometric surveys require a substantial improvement in the calibration precision of their photometry to r
Externí odkaz:
http://arxiv.org/abs/2410.24173
Given large data sets and sufficient compute, is it beneficial to design neural architectures for the structure and symmetries of each problem? Or is it more efficient to learn them from data? We study empirically how equivariant and non-equivariant
Externí odkaz:
http://arxiv.org/abs/2410.23179