Open Problems in Mechanistic Interpretability

Kavli Affiliate: Max Tegmark | First 5 Authors: Lee Sharkey, Bilal Chughtai, Joshua Batson, Jack Lindsey, Jeff Wu | Summary: Mechanistic interpretability aims to understand the computational mechanisms underlying neural networks’ capabilities in order to accomplish concrete scientific and engineering goals. Progress in this field thus promises to provide greater assurance over AI system behavior […]


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Object Detection for Medical Image Analysis: Insights from the RT-DETR Model

Kavli Affiliate: Ting Xu | First 5 Authors: Weijie He, Yuwei Zhang, Ting Xu, Tai An, Yingbin Liang | Summary: Deep learning has emerged as a transformative approach for solving complex pattern recognition and object detection challenges. This paper focuses on the application of a novel detection framework based on the RT-DETR model for analyzing […]


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A Study of Afterglow Signatures in NaI and CsI Scintillator Modules for the Background and Transient Observer Instrument on COSI

Kavli Affiliate: Tadayuki Takahashi | First 5 Authors: Hannah Gulick, Hiroki Yoneda, Tadayuki Takahashi, Claire Chen, Kazuhiro Nakazawa | Summary: We present measurements of the afterglow signatures in NaI(Tl) and CsI(Tl) detector modules as part of the Background and Transient Observer (BTO) mission detector trade-study. BTO is a NASA Student Collaboration Project flying on the […]


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Cosmological Consequences of Domain Walls Biased by Quantum Gravity

Kavli Affiliate: Masahito Yamazaki | First 5 Authors: Yann Gouttenoire, Stephen F. King, Rishav Roshan, Xin Wang, Graham White | Summary: One of the simplest standard model extensions leading to a domain wall network is a real scalar $S$ with a $mathcal{Z}_2$ symmetry spontaneously broken during universe evolution. Motivated by the swampland program, we explore […]


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State Permutation Control in Non-Hermitian Multiqubit Systems with Suppressed Non-Adiabatic Transitions

Kavli Affiliate: Birgitta Whaley | First 5 Authors: Ievgen I. Arkhipov, Philippe Lewalle, Franco Nori, Şahin K. Özdemir, K. Birgitta Whaley | Summary: Non-Hermitian systems have been at the focus of intense research for over a decade, partly due to their nontrivial energy topology formed by intersecting Riemann manifolds with branch points known as exceptional […]


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Braiding Majoranas in a linear quantum dot-superconductor array: Mitigating the errors from Coulomb repulsion and residual tunneling

Kavli Affiliate: Michael Wimmer | First 5 Authors: Sebastian Miles, Francesco Zatelli, A. Mert Bozkurt, Michael Wimmer, Chun-Xiao Liu | Summary: Exchanging the positions of two non-Abelian anyons transforms between many-body wavefunctions within a degenerate ground-state manifold. This behavior is fundamentally distinct from fermions, bosons and Abelian anyons. Recently, quantum dot-superconductor arrays have emerged as […]


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A flux-controlled two-site Kitaev chain

Kavli Affiliate: Srijit Goswami | First 5 Authors: Ivan Kulesh, Sebastiaan L. D. ten Haaf, Qingzhen Wang, Vincent P. M. Sietses, Yining Zhang | Summary: In semiconducting-superconducting hybrid devices, Andreev bound states (ABSs) can mediate the coupling between quantum dots (QDs), allowing for the realisation of artificial Kitaev chains. In order to engineer Majorana bound […]


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CausalSR: Structural Causal Model-Driven Super-Resolution with Counterfactual Inference

Kavli Affiliate: Feng Wang | First 5 Authors: Zhengyang Lu, Bingjie Lu, Feng Wang, , | Summary: Physical and optical factors interacting with sensor characteristics create complex image degradation patterns. Despite advances in deep learning-based super-resolution, existing methods overlook the causal nature of degradation by adopting simplistic black-box mappings. This paper formulates super-resolution using structural […]


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MM-Retinal V2: Transfer an Elite Knowledge Spark into Fundus Vision-Language Pretraining

Kavli Affiliate: Yi Zhou | First 5 Authors: Ruiqi Wu, Na Su, Chenran Zhang, Tengfei Ma, Tao Zhou | Summary: Vision-language pretraining (VLP) has been investigated to generalize across diverse downstream tasks for fundus image analysis. Although recent methods showcase promising achievements, they significantly rely on large-scale private image-text data but pay less attention to […]


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