Zobrazeno 1 - 10
of 47 786
pro vyhledávání: '"Cobb, BE"'
Autor:
Kaur, Ramneet, Samplawski, Colin, Cobb, Adam D., Roy, Anirban, Matejek, Brian, Acharya, Manoj, Elenius, Daniel, Berenbeim, Alexander M., Pavlik, John A., Bastian, Nathaniel D., Jha, Susmit
In this paper, we present a dynamic semantic clustering approach inspired by the Chinese Restaurant Process, aimed at addressing uncertainty in the inference of Large Language Models (LLMs). We quantify uncertainty of an LLM on a given query by calcu
Externí odkaz:
http://arxiv.org/abs/2411.02381
We propose a resource-constrained heuristic for instances of Max-SAT that iteratively decomposes a larger problem into smaller subcomponents that can be solved by optimized solvers and hardware. The unconstrained outer loop maintains the state space
Externí odkaz:
http://arxiv.org/abs/2410.09173
Autor:
Cobb, Dimitri, Koch, Herbert
In this article, we will study unbounded solutions of the 2D incompressible Euler equations. One of the motivating factors for this is that the usual functional framework for the Euler equations (e.g. based on finite energy conditions, such as $L^2$)
Externí odkaz:
http://arxiv.org/abs/2410.05054
This paper introduces a second-order hyperplane search, a novel optimization step that generalizes a second-order line search from a line to a $k$-dimensional hyperplane. This, combined with the forward-mode stochastic gradient method, yields a secon
Externí odkaz:
http://arxiv.org/abs/2408.10419
We resolve Stillman's conjecture for families of polynomial rings that are graded by any abelian group under mild conditions. Conversely, we show that these conditions are necessary for the existence of a Stillman bound. This has applications even fo
Externí odkaz:
http://arxiv.org/abs/2406.09593
In applications such as personal assistants, large language models (LLMs) must consider the user's personal information and preferences. However, LLMs lack the inherent ability to learn from user interactions. This paper explores capturing personal i
Externí odkaz:
http://arxiv.org/abs/2405.14012
Autor:
Çöplü, Tolga, Bendiken, Arto, Skomorokhov, Andrii, Bateiko, Eduard, Cobb, Stephen, Bouw, Joshua J.
Augmenting large language models (LLMs) with user-specific knowledge is crucial for real-world applications, such as personal AI assistants. However, LLMs inherently lack mechanisms for prompt-driven knowledge capture. This paper investigates utilizi
Externí odkaz:
http://arxiv.org/abs/2402.00414
In this paper, a deep learning method for solving an improved one-dimensional Poisson-Nernst-Planck ion channel (PNPic) model, called the PNPic deep learning solver, is presented. In particular, it combines a novel local neural network scheme with an
Externí odkaz:
http://arxiv.org/abs/2401.17513
This article studies the vortex-wave system for the Surface Quasi-Geostrophic equation with parameter 0 < s < 1. We obtained local existence of classical solutions in H^4 under the standard "plateau hypothesis", H^2-stability of the solutions, and a
Externí odkaz:
http://arxiv.org/abs/2401.02728
Autor:
Cobb, Dimitri, Lacour, Geoffrey
In this article, we study a non-Newtonian Stokes-Transport system. This set of PDEs was introduced as a model for describing the behavior of a cloud of particles in suspension in a Stokes fluid, and is a nonlinear coupling between a hyperbolic equati
Externí odkaz:
http://arxiv.org/abs/2401.02599