Tootfinder

EnerBridge-DPO: Energy-Guided Protein Inverse Folding with Markov Bridges and Direct Preference Optimization
Dingyi Rong, Haotian Lu, Wenzhuo Zheng, Fan Zhang, Shuangjia Zheng, Ning Liu
https://arxiv.org/abs/2506.09496

EnerBridge-DPO: Energy-Guided Protein Inverse Folding with Markov Bridges and Direct Preference Optimization
Designing protein sequences with optimal energetic stability is a key challenge in protein inverse folding, as current deep learning methods are primarily trained by maximizing sequence recovery rates, often neglecting the energy of the generated sequences. This work aims to overcome this limitation by developing a model that directly generates low-energy, stable protein sequences. We propose EnerBridge-DPO, a novel inverse folding framework focused on generating low-energy, high-stability prot…

Energy Aware Development of Neuromorphic Implantables: From Metrics to Action
Enrique Barba Roque, Luis Cruz
https://arxiv.org/abs/2506.09599 https://

Energy Aware Development of Neuromorphic Implantables: From Metrics to Action
Spiking Neural Networks (SNNs) and neuromorphic computing present a promising alternative to traditional Artificial Neural Networks (ANNs) by significantly improving energy efficiency, particularly in edge and implantable devices. However, assessing the energy performance of SNN models remains a challenge due to the lack of standardized and actionable metrics and the difficulty of measuring energy consumption in experimental neuromorphic hardware. In this paper, we conduct a preliminary explora…

The Emergence of Abstract Thought in Large Language Models Beyond Any Language
Yuxin Chen, Yiran Zhao, Yang Zhang, An Zhang, Kenji Kawaguchi, Shafiq Joty, Junnan Li, Tat-Seng Chua, Michael Qizhe Shieh, Wenxuan Zhang
https://arxiv.org/abs/2506.09890

The Emergence of Abstract Thought in Large Language Models Beyond Any Language
As large language models (LLMs) continue to advance, their capacity to function effectively across a diverse range of languages has shown marked improvement. Preliminary studies observe that the hidden activations of LLMs often resemble English, even when responding to non-English prompts. This has led to the widespread assumption that LLMs may "think" in English. However, more recent results showing strong multilingual performance, even surpassing English performance on specific tasks in other…

Optimal quantum metrology under energy constraints
Longyun Chen, Yuxiang Yang
https://arxiv.org/abs/2506.09436 https://arxiv.org/pdf/…

Optimal quantum metrology under energy constraints
Quantum metrology promises enhanced precision in parameter estimation by exploiting quantum effects. The traditional framework of metrology commonly assumes unlimited access to resources, overlooking resource constraints in realistic scenarios. As such, the optimal strategies therein are often infeasible in practice. Here, we investigate quantum metrology where the total energy consumption of the probe state preparation, intermediate control operations, and the final measurement is subject to a…

Last week, our students learned how to conduct a proper evaluation for an NLP experiment. To this end, we introduced a small textcorpus with sentences about Joseph Fourier, who counts as one of the discoverers of the greenhouse effect, responsible for global warming.

A Neural Network-aided Low Complexity Chase Decoder for URLLC
Enrico Testi, Enrico Paolini
https://arxiv.org/abs/2506.10513 https://a…

A Neural Network-aided Low Complexity Chase Decoder for URLLC
Ultra-reliable low-latency communications (URLLC) demand decoding algorithms that simultaneously offer high reliability and low complexity under stringent latency constraints. While iterative decoding schemes for LDPC and Polar codes offer a good compromise between performance and complexity, they fall short in approaching the theoretical performance limits in the typical URLLC short block length regime. Conversely, quasi-ML decoding schemes for algebraic codes, like Chase-II decoding, exhibit …

Topological defects as effective dynamical dark energy
Haipeng An, Chengcheng Han, Borui Zhang
https://arxiv.org/abs/2506.10075 https://

Topological defects as effective dynamical dark energy
In this work, we consider the possibility that the dynamical dark energy hinted at by recent DESI data may be mimicked by the effects of additional components in the universe, potentially arising from topological defects. We find that the data does not show a particular preference for the existence of cosmic strings. However, a domain wall contribution at the percent level can improve the fit, yielding a $Δχ^2= -1.72$ compared to the $Λ\rm{CDM}$ model. The improvement indicates that topologi…

Securing Open RAN: A Survey of Cryptographic Challenges and Emerging Solutions for 5G
Ryan Barker, Fatemeh Afghah
https://arxiv.org/abs/2506.09418 https://…

Securing Open RAN: A Survey of Cryptographic Challenges and Emerging Solutions for 5G
The advent of Open Radio Access Networks (O-RAN) introduces modularity and flexibility into 5G deployments but also surfaces novel security challenges across disaggregated interfaces. This literature review synthesizes recent research across thirteen academic and industry sources, examining vulnerabilities such as cipher bidding-down attacks, partial encryption exposure on control/user planes, and performance trade-offs in securing O-RAN interfaces like E2 and O1. The paper surveys key cryptogr…

Physical properties of $R$Co$_{2}$Al$_{8}$ ($R=$ La, Ce, Pr, Nd and Sm) single crystals: an emerging structure-type for anisotropic Kondo lattice studies
Fernando A. Garcia, Sushma Kumari, Juan Schmidt, Cris Adriano, Aashish Sapkota, Paul C. Canfield, Rebecca Flint, Raquel A. Ribeiro
https://arxiv.org/abs/2506.10905

Physical properties of $R$Co$_{2}$Al$_{8}$ ($R=$ La, Ce, Pr, Nd and Sm) single crystals: an emerging structure-type for anisotropic Kondo lattice studies
Systematic investigations of rare-earth ($R$) based intermetallic materials is a leading strategy to reveal the underlying mechanisms governing a range of physical phenomena, such as the formation of a Kondo lattice and competing electronic and magnetic anisotropies. In this work, the magnetic, thermal and transport properties of $R$Co$_{2}$Al$_{8}$ ($R=$ La, Ce, Pr, Nd and Sm) single crystals are presented. LaCo$_{2}$Al$_{8}$ is characterized as a Pauli paramagnet and transport measurements, w…

Quanta Magazine's Stephen Ornes describes a novel algorithm that can factor large numbers using only one qubit. The technique relies on quantum oscillation, and although it has a catch (the larger the number being factored the more energy the oscillators expend), the work points to new ways to perform quantum computing.
"New Quantum Algorithm Factors Numbers With One Qubit
-The catch: It would require the energy of a few medium-size stars."