Tootfinder

StyleAdaptedLM: Enhancing Instruction Following Models with Efficient Stylistic Transfer
Pritika Ramu, Apoorv Saxena, Meghanath M Y, Varsha Sankar, Debraj Basu
https://arxiv.org/abs/2507.18294

StyleAdaptedLM: Enhancing Instruction Following Models with Efficient Stylistic Transfer
Adapting LLMs to specific stylistic characteristics, like brand voice or authorial tones, is crucial for enterprise communication but challenging to achieve from corpora which lacks instruction-response formatting without compromising instruction adherence. We introduce StyleAdaptedLM, a framework that efficiently transfers stylistic traits to instruction-following models using Low-Rank Adaptation (LoRA). LoRA adapters are first trained on a base model with diverse unstructured stylistic corpor…

Learning Approach to Efficient Vision-based Active Tracking of a Flying Target by an Unmanned Aerial Vehicle
Jagadeswara PKV Pothuri, Aditya Bhatt, Prajit KrisshnaKumar, Manaswin Oddiraju, Souma Chowdhury
https://arxiv.org/abs/2506.18264

Learning Approach to Efficient Vision-based Active Tracking of a Flying Target by an Unmanned Aerial Vehicle
Autonomous tracking of flying aerial objects has important civilian and defense applications, ranging from search and rescue to counter-unmanned aerial systems (counter-UAS). Ground based tracking requires setting up infrastructure, could be range limited, and may not be feasible in remote areas, crowded cities or in dense vegetation areas. Vision based active tracking of aerial objects from another airborne vehicle, e.g., a chaser unmanned aerial vehicle (UAV), promises to fill this important …

I mean...
I would much rather Trump falling for being a nazi-adjacent inhuman pile of steaming orange shit. But if he ends up falling for being a raping pedophile, I won't complain.
After all, Al Capone fell to tax evasion, not to murder. He still fell.

Generative Diffusion Receivers: Achieving Pilot-Efficient MIMO-OFDM Communications
Yuzhi Yang, Omar Alhussein, Atefeh Arani, Zhaoyang Zhang, M\'erouane Debbah
https://arxiv.org/abs/2506.18419

Generative Diffusion Receivers: Achieving Pilot-Efficient MIMO-OFDM Communications
This paper focuses on wireless multiple-input multiple-output (MIMO)-orthogonal frequency division multiplex (OFDM) receivers. Traditional wireless receivers have relied on mathematical modeling and Bayesian inference, achieving remarkable success in most areas but falling short in their ability to characterize channel matrices. Neural networks (NNs) have demonstrated significant potential in this aspect. Nevertheless, integrating traditional inference methods with NNs presents challenges, part…

In April, shortly before being valued by venture investors at $9 billion, Elon Musk’s Neuralink labeled itself a
“small disadvantaged business” in a federal filing
The filing would have reached the Small Business Administration at a time when Musk was leading the Trump administration’s Department of Government Efficiency (DOGE)

Elon Musk's Neuralink filed as 'disadvantaged business' before being valued at $9 billion
Neuralink labeled itself in April as a "small disadvantaged business" in a federal filing with the U.S. Small Business Administration.

Electron-muon conversion in nuclei and rare decays induced by LFV dark photon
Alexey S. Zhevlakov, Sergey Kuleshov, Valery E. Lyubovitskij, Evgenie O. Oleynik
https://arxiv.org/abs/2507.17733

Electron-muon conversion in nuclei and rare decays induced by LFV dark photon
We study lepton flavor violation (LFV) effects occurring in the $e-μ$ conversion in nuclei and in the rare radiative decays $η(η') \to γμe$ of the $η$ and $η'$ mesons with a special impact of the sub-GeV mass vector mediator (dark photon). In the case of the lepton conversion we make estimates for running and future experiments operating with electron beams at fixed target. Obtained results are implemented in analysis of the LFV decays $η(η') \to γμe$. In particular, we derive the fo…

Binary Neutron Star Mergers as Potential Sources for Ultra-High-Energy Cosmic Rays and High-Energy Neutrinos
Gang Guo, Yong-Zhong Qian, Meng-Ru Wu
https://arxiv.org/abs/2506.17581

Binary Neutron Star Mergers as Potential Sources for Ultra-High-Energy Cosmic Rays and High-Energy Neutrinos
Recent studies suggest that the most energetic cosmic rays, exceeding 100 EeV, may primarily consist of $r$-process nuclei. This highlights binary neutron star mergers and collapsars as promising sources of ultra-high-energy cosmic rays (UHECRs). Building on these insights, we examine the conditions that facilitate the efficient production of UHE $r$-process nuclei during the prompt radiation (PR), extended emission (EE), and plateau emission phases of short gamma-ray bursts (sGRBs) following n…

Cost for research -- how cost data of research can be included in open metadata to be reused and evaluated
Julia Bartlewski, Christoph Broschinski, Gernot Deinzer, Cornelia Lang, Dirk Pieper, Bianca Schweighofer, Colin Sippl, Lisa-Marie Stein, Alexander Wagner, Silke Weisheit
https://arxiv.org/abs/2506.18517

Cost for research -- how cost data of research can be included in open metadata to be reused and evaluated
The openCost project aims to enhance transparency in research funding by making publication-related costs publicly accessible, following FAIR principles. It introduces a metadata schema for cost data, allowing aggregation and analysis across institutions. The project promotes open access and cost-efficient models, benefiting academic institutions, funders, and policymakers.

Local feature filtering for scalable and well-conditioned Random Feature Methods
Jan Willem van Beek, Victorita Dolean, Ben Moseley
https://arxiv.org/abs/2506.17626

Local feature filtering for scalable and well-conditioned Random Feature Methods
In recent years, machine learning has emerged as a powerful tool for solving partial differential equations (PDEs), with randomized neural networks showing remarkable potential. These networks, typically shallow, differ from conventional approaches by randomizing all parameters except those in the final layer. Notably, by integrating techniques inspired by domain decomposition, they achieve improved local accuracy and computational efficiency. Following \cite{chen:2022:BTM}, we refer to these a…

Tuning chiral anomaly signature in a Dirac semimetal via fast-ion implantation
Manasi Mandal, Eunbi Rha, Abhijatmedhi Chotrattanapituk, Denisse C\'ordova Carrizales, Alexander Lygo, Kevin B. Woller, Mouyang Cheng, Ryotaro Okabe, Guomin Zhu, Kiran Mak, Chu-Liang Fu, Chuhang Liu, Lijun Wu, Yimei Zhu, Susanne Stemmer, Mingda Li
https://ar…

Tuning chiral anomaly signature in a Dirac semimetal via fast-ion implantation
Cd$_3$As$_2$ is a prototypical Dirac semimetal that hosts a chiral anomaly and thereby functions as a platform to test high-energy physics hypotheses and to realize energy efficient applications. Here we use a combination of accelerator-based fast ion implantation and theory-driven planning to enhance the negative longitudinal magnetoresistance (NLMR)--a signature of a chiral anomaly--in Nb-doped Cd$_3$As$_2$ thin films. High-energy ion implantation is commonly used to investigate semiconductor…