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Related papers: Is it possible to know cosmological fine-tuning?

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Uncertainty quantification is a set of techniques that measure confidence in language models. They can be used, for example, to detect hallucinations or alert users to review uncertain predictions. To be useful, these confidence scores must…

Computation and Language · Computer Science 2026-04-13 Lorenzo Jaime Yu Flores , Cesare Spinoso di-Piano , Jackie Chi Kit Cheung

Parameter estimates in misspecified models converge to pseudo-true parameter values, which minimize a population objective function. Pseudo-true values often differ from quantities of economic interest, raising questions of how, if at all,…

Econometrics · Economics 2026-04-20 Isaiah Andrews , Harvey Barnhard , Jacob Carlson

Representation learning has been widely studied in the context of meta-learning, enabling rapid learning of new tasks through shared representations. Recent works such as MAML have explored using fine-tuning-based metrics, which measure the…

Machine Learning · Computer Science 2021-05-06 Kurtland Chua , Qi Lei , Jason D. Lee

The possibility of determining cosmological parameters on the basis of a wide set of observational data including the Abell-ACO cluster power spectrum and mass function, peculiar velocities of galaxies, the distribution of Ly-$\alpha$…

Astrophysics · Physics 2007-05-23 B. Novosyadlyj , R. Durrer , S. Gottloeber , V. N. Lukash , S. Apunevych

We critically analyze the rationale of arguments from finetuning and naturalness in particle physics and cosmology. Some other numerological coincidences are also discussed.

History and Philosophy of Physics · Physics 2019-12-02 S. Hossenfelder

The majority of present efforts to constrain cosmological parameters with cosmic microwave background (CMB) anisotropy data employ approximate likelihood functions, the time consuming nature of a complete analysis being a major obstacle. We…

Astrophysics · Physics 2007-05-23 M. Douspis , J. G. Bartlett , A. Blanchard , M. Le Dour

Model selection aims to determine which theoretical models are most plausible given some data, without necessarily asking about the preferred values of the model parameters. A common model selection question is to ask when new data require…

Astrophysics · Physics 2008-11-26 Andrew R. Liddle , Pia Mukherjee , David Parkinson

We discuss the constraints one can place on cosmological parameters using current cosmic microwave background data. A standard $\chi^2$--minimization over band--power estimates is first presented, followed by a discussion of the more…

Astrophysics · Physics 2007-05-23 J. G. Bartlett , A. Blanchard , M. Douspis , M. Le Dour

In recent years, by theory and observation cosmology has advanced substantially. Parameters of the concordance or $\Lambda$CDM cosmological model are given with unprecedented precision ("precision cosmology"). On the other side, 95% of the…

General Relativity and Quantum Cosmology · Physics 2012-04-17 Hubert F. Goenner

Modern scientific cosmology pushes the boundaries of knowledge and the knowable. This is prompting questions on the nature of scientific knowledge. A central issue is what defines a 'good' model. When addressing global properties of the…

History and Philosophy of Physics · Physics 2018-12-12 Martin Sahlén

We study a fundamental issue in cosmology: Whether we can rely on a cosmological model to understand the real history of the Universe. This fundamental, still unresolved issue is often called the ``model-fitting problem (or averaging…

General Relativity and Quantum Cosmology · Physics 2009-11-07 Masafumi Seriu

The quality of CMB observations has improved dramatically in the last few years, and will continue to do so in the coming decade. Over a wide range of angular scales, the uncertainty due to instrumental noise is now small compared to the…

It is well known that observations of the cosmic microwave background (CMB) are highly sensitive to the spatial curvature of the Universe, k. Here we find that what is in fact being tightly constrained by small angle fluctuations is spatial…

Cosmology and Nongalactic Astrophysics · Physics 2011-07-25 Timothy Clifton , Pedro G. Ferreira , Joe Zuntz

Although the broad outlines of the appropriate pipeline for cosmological likelihood analysis with CMB data has been known for several years, only recently have we had to contend with the full, large-scale, computationally challenging…

Astrophysics · Physics 2009-11-10 Andrew H. Jaffe , J. R. Bond , P. G. Ferreira , L. E. Knox

One aim shared by multiple settings, such as continual learning or transfer learning, is to leverage previously acquired knowledge to converge faster on the current task. Usually this is done through fine-tuning, where an implicit…

Machine Learning · Computer Science 2023-10-17 Tudor Berariu , Wojciech Czarnecki , Soham De , Jorg Bornschein , Samuel Smith , Razvan Pascanu , Claudia Clopath

The recent high-quality measurements of the Cosmic Microwave Background anisotropies have presented cosmologists with the possibility of studying the large scale properties of our universe with unprecedented precision. Here I review the…

High Energy Physics - Phenomenology · Physics 2007-05-23 Alessandro Melchiorri

Our research demonstrates the significant benefits of using fine-tuning with explanations to enhance the performance of language models. Unlike prompting, which maintains the model's parameters, fine-tuning allows the model to learn and…

Computation and Language · Computer Science 2024-02-13 Mohamad Ballout , Ulf Krumnack , Gunther Heidemann , Kai-Uwe Kuehnberger

A nontrivial topology of the spatial section of the universe is an observable, which can be probed for all locally homogeneous and isotropic universes, without any assumption on the cosmological density parameters. We discuss how one can…

Astrophysics · Physics 2008-11-26 M. J. Reboucas

There is growing interest in using 3-dimensional neutral hydrogen mapping with the redshifted 21 cm line as a cosmological probe, as it has been argued to have a greater long-term potential than the cosmic microwave background. However, its…

Astrophysics · Physics 2008-11-26 Yi Mao , Max Tegmark , Matthew McQuinn , Matias Zaldarriaga , Oliver Zahn

Instruction Fine-tuning~(IFT) is a critical phase in building large language models~(LLMs). Previous works mainly focus on the IFT's role in the transfer of behavioral norms and the learning of additional world knowledge. However, the…

Computation and Language · Computer Science 2024-08-13 Mengjie Ren , Boxi Cao , Hongyu Lin , Cao Liu , Xianpei Han , Ke Zeng , Guanglu Wan , Xunliang Cai , Le Sun