Tootfinder

LARP: Learner-Agnostic Robust Data Prefiltering
Kristian Minchev, Dimitar Iliev Dimitrov, Nikola Konstantinov
https://arxiv.org/abs/2506.20573 https://

LARP: Learner-Agnostic Robust Data Prefiltering
The widespread availability of large public datasets is a key factor behind the recent successes of statistical inference and machine learning methods. However, these datasets often contain some low-quality or contaminated data, to which many learning procedures are sensitive. Therefore, the question of whether and how public datasets should be prefiltered to facilitate accurate downstream learning arises. On a technical level this requires the construction of principled data prefiltering metho…

Replaced article(s) found for cs.AI. https://arxiv.org/list/cs.AI/new
[5/5]:
- Understanding Reasoning in Thinking Language Models via Steering Vectors
Constantin Venhoff, Iv\'an Arcuschin, Philip Torr, Arthur Conmy, Neel Nanda

The VLA Frontier Fields Survey: A 6GHz High-resolution Radio Survey of Abell 2744
Esteban A. Orozco, Eric F. Jim\'enez-Andrade, Eric J. Murphy, Ian Smail, Emmanuel Momjian, Ian Heywood, Miguel Vega-Gutierrez, Christa DeCoursey
https://arxiv.org/abs/2506.20634

The VLA Frontier Fields Survey: A 6GHz High-resolution Radio Survey of Abell 2744
We present a 6GHz radio continuum image of the galaxy cluster Abell 2744 ($z = 0.307$) obtained with the Karl G. Jansky Very Large Array (VLA) as part of the VLA Frontier Fields program, whose goal is to explore the radio continuum emission from high-redshift galaxies that are magnified by foreground, massive galaxy clusters. With an rms noise of $\approx 1 μ$Jy beam$^{-1}$, at the phase center, and sub-arcsec angular resolution ($θ_{1/2}=0.82$ arcsec), this is the deepest and most detailed r…

LLM-Based Social Simulations Require a Boundary
Zengqing Wu, Run Peng, Takayuki Ito, Chuan Xiao
https://arxiv.org/abs/2506.19806 https://

LLM-Based Social Simulations Require a Boundary
This position paper argues that large language model (LLM)-based social simulations should establish clear boundaries to meaningfully contribute to social science research. While LLMs offer promising capabilities for modeling human-like agents compared to traditional agent-based modeling, they face fundamental limitations that constrain their reliability for social pattern discovery. The core issue lies in LLMs' tendency towards an ``average persona'' that lacks sufficient behavioral heterogene…

Communicating Smartly in Molecular Communication Environments: Neural Networks in the Internet of Bio-Nano Things
Jorge Torres G\'omez, Pit Hofmann, Lisa Y. Debus, Osman Tugay Ba\c{s}aran, Sebastian Lotter, Roya Khanzadeh, Stefan Angerbauer, Bige Deniz Unluturk, Sergi Abadal, Werner Haselmayr, Frank H. P. Fitzek, Robert Schober, Falko Dressler
ht…

Communicating Smartly in Molecular Communication Environments: Neural Networks in the Internet of Bio-Nano Things
Recent developments in the Internet of Bio-Nano Things (IoBNT) are laying the groundwork for innovative applications across the healthcare sector. Nanodevices designed to operate within the body, managed remotely via the internet, are envisioned to promptly detect and actuate on potential diseases. In this vision, an inherent challenge arises due to the limited capabilities of individual nanosensors; specifically, nanosensors must communicate with one another to collaborate as a cluster. Aiming…

LKA: Large Kernel Adapter for Enhanced Medical Image Classification
Ziquan Zhu, Si-Yuan Lu, Tianjin Huang, Lu Liu, Zhe Liu
https://arxiv.org/abs/2506.19118

LKA: Large Kernel Adapter for Enhanced Medical Image Classification
Despite the notable success of current Parameter-Efficient Fine-Tuning (PEFT) methods across various domains, their effectiveness on medical datasets falls short of expectations. This limitation arises from two key factors: (1) medical images exhibit extensive anatomical variation and low contrast, necessitating a large receptive field to capture critical features, and (2) existing PEFT methods do not explicitly address the enhancement of receptive fields. To overcome these challenges, we propo…

Leptogenesis in automatic Nelson-Barr models
Clara Murgui, Samuel Patrone
https://arxiv.org/abs/2506.18963 https://arxiv.org/pdf/2506…

Leptogenesis in automatic Nelson-Barr models
In this study, we numerically show that automatic Nelson-Barr models with new chiral fermions can simultaneously solve the strong CP problem and generate the observed baryon asymmetry via high-scale leptogenesis. In these models, all CP violation arises from a single spontaneous symmetry-breaking scale, linking the origin of quark and lepton CP phases. Using conservative assumptions and minimal dynamics, we identify a viable parameter window where successful leptogenesis occurs without spoiling…

Discovery of Diffuse Radio Emission in a Massive z=1.709 Cool Core Cluster: A Candidate Radio Mini-Halo
Julie Hlavacek-Larrondo, Roland Timmerman, Christoph Pfrommer, Erik Osinga, Larissa Tevlin, Tracy M. A. Webb, Natalia Martorella, Xiaoyuan Zhang, Reinout van Weeren, Hyunseop Choi, Gabriella Di Gennaro, Marie-Lou Gendron-Marsolais, Carter Rhea
http…

Discovery of Diffuse Radio Emission in a Massive z=1.709 Cool Core Cluster: A Candidate Radio Mini-Halo
Clusters of galaxies host spectacular diffuse radio sources, extending over scales from 100 kpc to several Mpcs. These sources, with extremely faint surface brightness ($μ$Jy/arcsec$^2$ level), are not tied to individual galaxies but trace synchrotron emission from large-scale magnetic fields and relativistic particles within the intracluster environment. Here, we report the discovery of a candidate radio mini-halo in SpARCS104922.6+564032.5, the most distant cool-core galaxy cluster identifie…

Which Consciousness Can Be Artificialized? Local Percept-Perceiver Phenomenon for the Existence of Machine Consciousness
Shri Lal Raghudev Ram Singh
https://arxiv.org/abs/2506.18935

Which Consciousness Can Be Artificialized? Local Percept-Perceiver Phenomenon for the Existence of Machine Consciousness
This paper presents a novel paradigm of the local percept-perceiver phenomenon to formalize certain observations in neuroscientific theories of consciousness. Using this model, a set-theoretic formalism is developed for artificial systems, and the existence of machine consciousness is proved by invoking Zermelo-Fraenkel set theory. The article argues for the possibility of a reductionist form of epistemic consciousness within machines.

Properties of the cores and filaments in the Ophiuchus molecular cloud and its L1688 hub-filament system
Bo-Sheng Jia, Guo-Yin Zhang, Alexander Menshchikov, Sami Dib, Jin-Zeng Li, Ke Wang, Di Li, Xue-Mei Li, Zhi-Yuan Ren, Chang Zhang, Nageen Pervaiz, Lin Xiao
https://arxiv.org/abs/2506.20619…

Properties of the cores and filaments in the Ophiuchus molecular cloud and its L1688 hub-filament system
Analyzing filaments and cores in molecular clouds is key to understanding galactic star formation and its environmental dependence. This paper studies the properties and distribution of dense cores and filaments in the Ophiuchus molecular cloud, with a focus on the L1688 hub-filament system (HFS) and its star formation potential. We extracted sources and filaments from Herschel images and a 13.5 arcsec resolution surface density map using the getsf method, identified prestellar cores among the …