Tootfinder

Corner-Sharing PS$_4$-BS$_4$ Modes Facilitate Fast Ion Conduction in Lithium Thioborophosphate Iodide Glassy Solid Electrolytes
Yun An
https://arxiv.org/abs/2507.08215

Corner-Sharing PS$_4$-BS$_4$ Modes Facilitate Fast Ion Conduction in Lithium Thioborophosphate Iodide Glassy Solid Electrolytes
Glassy solid electrolytes (GSEs), with their amorphous nature and the absence of grain boundaries, make them highly attractive for applications in all-solid-state lithium batteries (ASSLBs), a leading candidate for next-generation energy storage technologies. A recently developed lithium thioborophosphate iodide GSE, composed of 30Li$_2$S-25B$_2$S$_3$-45LiI-5P$_2$S$_5$ (LBPSI), has demonstrated excellent room-temperature ionic conductivity and low activation energy. Despite this exciting findin…

Multi-Functional Chirp Signalling for Next-Generation Multi-Carrier Wireless Networks: Communications, Sensing and ISAC Perspectives
Zeping Sui, Qu Luo, Zilong Liu, Murat Temiz, Leila Musavian, Christos Masouros, Yong Liang Guan, Pei Xiao, Lajos Hanzo
https://arxiv.org/abs/2508.06022

Multi-Functional Chirp Signalling for Next-Generation Multi-Carrier Wireless Networks: Communications, Sensing and ISAC Perspectives
To meet the increasingly demanding quality-of-service requirements of the next-generation multi-carrier mobile networks, it is essential to design multi-functional signalling schemes facilitating efficient, flexible, and reliable communication and sensing in complex wireless environments. As a compelling candidate, we advocate chirp signalling, beneficially amalgamating sequences (e.g., Zadoff-Chu sequences) with waveforms (e.g., chirp spread spectrum and frequency-modulated continuous wave (FM…

In-Loop Filtering Using Learned Look-Up Tables for Video Coding
Zhuoyuan Li, Jiacheng Li, Yao Li, Jialin Li, Li Li, Dong Liu, Feng Wu
https://arxiv.org/abs/2509.09494 https://…

In-Loop Filtering Using Learned Look-Up Tables for Video Coding
In-loop filtering (ILF) is a key technology in video coding standards to reduce artifacts and enhance visual quality. Recently, neural network-based ILF schemes have achieved remarkable coding gains, emerging as a powerful candidate for next-generation video coding standards. However, the use of deep neural networks (DNN) brings significant computational and time complexity or high demands for dedicated hardware, making it challenging for general use. To address this limitation, we study a prac…

Ultra-pure Nickel for Structural Components of Low-Radioactivity Instruments
T. J. Roosendaal, C. T. Overman, G. S. Ortega, T. D. Schlieder, N. D. Rocco, L. K. S. Horkley, K. P. Hobbs, K. Harouaka, J. L. Orrell, P. Acharya, A. Amy, E. Angelico, A. Anker, I. J. Arnquist, A. Atencio, J. Bane, V. Belov, E. P. Bernard, T. Bhatta, A. Bolotnikov, J. Breslin, P. A. Breur, J. P. Brodsky, E. Brown, T. Brunner, B. Burnell, E. Caden, L. Q. Cao, D. Cesmecioglu, S. A. Charlebois, D. Chernyak, M. Ch…

Ultra-pure Nickel for Structural Components of Low-Radioactivity Instruments
The next generation of rare-event search experiments in nuclear and particle physics demand structural materials combining exceptional mechanical strength with ultra-low levels of radioactive contamination. This study evaluates chemical vapor deposition (CVD) nickel as a candidate structural material for such applications. Manufacturer-supplied CVD Ni grown on aluminum substrates underwent tensile testing before and after welding alongside standard Ni samples. CVD Ni exhibited a planar tensile …

Mapping the Gravitational-wave Background Across the Spectrum with a Next-Generation Anisotropic Per-frequency Optimal Statistic
Kyle A. Gersbach, Stephen R. Taylor, Bence B\'ecsy, Anna-Malin Lemke, Andrea Mitridate, Nihan Pol
https://arxiv.org/abs/2509.07090

Mapping the Gravitational-wave Background Across the Spectrum with a Next-Generation Anisotropic Per-frequency Optimal Statistic
With pulsar timing arrays (PTAs) having observed a gravitational wave background (GWB) at nanohertz frequencies, the focus of the field is shifting towards determining and characterizing its origin. While the primary candidate is a population of GW-emitting supermassive black hole binaries (SMBHBs), many other cosmological processes could produce a GWB with similar spectral properties as have been measured. One key argument to help differentiate an SMBHB GWB from a cosmologically sourced one is…

Right-handed neutrino dark matter consistent with the generation of baryon number asymmetry
Daijiro Suematsu
https://arxiv.org/abs/2507.05957 https://

Right-handed neutrino dark matter consistent with the generation of baryon number asymmetry
A right-handed neutrino is a promising candidate for dark matter (DM) which has no interaction with nuclei. Since two right-handed neutrinos explain neutrino oscillation data and baryon number asymmetry through seesaw mechanism and leptogenesis based on the out-of-equilibrium decay of the lighter one, the lightest third right-handed neutrino could be free from them and stable to be DM. It suggests a possibility that the right-handed neutrinos could be common key particles for the explanation of…

The Impact of Critique on LLM-Based Model Generation from Natural Language: The Case of Activity Diagrams
Parham Khamsepour, Mark Cole, Ish Ashraf, Sandeep Puri, Mehrdad Sabetzadeh, Shiva Nejati
https://arxiv.org/abs/2509.03463

The Impact of Critique on LLM-Based Model Generation from Natural Language: The Case of Activity Diagrams
Large Language Models (LLMs) show strong potential for automating the generation of models from natural-language descriptions. A common approach is an iterative generate-critique-refine loop, where candidate models are produced, evaluated, and updated based on detected issues. This process needs to address: (1) structural correctness - compliance with well-formedness rules - and (2) semantic alignment - accurate reflection of the intended meaning in the source text. We present LADEX (LLM-based …

Secure Quantum Key Distribution via Entangled Quantum Walkers
Chia-Tso Lai
https://arxiv.org/abs/2508.05593 https://arxiv.org/pdf/2508.05593

Secure Quantum Key Distribution via Entangled Quantum Walkers
Quantum Key Distribution (QKD) is an emerging cryptographic method designed for secure key sharing. Its security is theoretically guaranteed by fundamental principles of quantum mechanics, making it a leading candidate for future communication protocols. Quantum Random Walks (QRWs), on the other hand, are quantum processes that exhibit intriguing phenomena such as interference and superposition, enabling the generation of decentralized and asymmetric probability distributions. Inspired by both …

GENPLUGIN: A Plug-and-Play Framework for Long-Tail Generative Recommendation with Exposure Bias Mitigation
Kun Yang, Siyao Zheng, Tianyi Li, Xiaodong Li, Hui Li
https://arxiv.org/abs/2507.03568

GENPLUGIN: A Plug-and-Play Framework for Long-Tail Generative Recommendation with Exposure Bias Mitigation
Generative recommendation (GenRec) offers LLM integration, reduced embedding costs, and eliminates per-candidate scoring, attracting great attention. Despite its promising performance, this study reveals that it suffers from generation exposure bias and poor long-tail item generalization, two critical limitations overlooked by prior works on GenRec. To address these, we propose GENPLUGIN, a plug-and-play framework featuring a dual-encoder, shared-decoder architecture. During pre-training, it al…

PiCSAR: Probabilistic Confidence Selection And Ranking
Joshua Ong Jun Leang, Zheng Zhao, Aryo Pradipta Gema, Sohee Yang, Wai-Chung Kwan, Xuanli He, Wenda Li, Pasquale Minervini, Eleonora Giunchiglia, Shay B. Cohen
https://arxiv.org/abs/2508.21787

PiCSAR: Probabilistic Confidence Selection And Ranking
Best-of-n sampling improves the accuracy of large language models (LLMs) and large reasoning models (LRMs) by generating multiple candidate solutions and selecting the one with the highest reward. The key challenge for reasoning tasks is designing a scoring function that can identify correct reasoning chains without access to ground-truth answers. We propose Probabilistic Confidence Selection And Ranking (PiCSAR): a simple, training-free method that scores each candidate generation using the jo…

Combining Type Inference and Automated Unit Test Generation for Python
Lukas Krodinger, Stephan Lukasczyk, Gordon Fraser
https://arxiv.org/abs/2507.01477 h…

Combining Type Inference and Automated Unit Test Generation for Python
Automated unit test generation is an established research field that has so far focused on statically-typed programming languages. The lack of type information in dynamically-typed programming languages, such as Python, inhibits test generators, which heavily rely on information about parameter and return types of functions to select suitable arguments when constructing test cases. Since automated test generators inherently rely on frequent execution of candidate tests, we make use of these fre…

Synthesizable by Design: A Retrosynthesis-Guided Framework for Molecular Analog Generation
Shuan Chen, Gunwook Nam, Yousung Jung
https://arxiv.org/abs/2507.02752

Synthesizable by Design: A Retrosynthesis-Guided Framework for Molecular Analog Generation
The disconnect between AI-generated molecules with desirable properties and their synthetic feasibility remains a critical bottleneck in computational drug and material discovery. While generative AI has accelerated the proposal of candidate molecules, many of these structures prove challenging or impossible to synthesize using established chemical reactions. Here, we introduce SynTwins, a novel retrosynthesis-guided molecular analog design framework that designs synthetically accessible molecu…

Frequency comb generation in low-loss, low-stress, high-Q deuterated silicon nitride microring resonators in an 8-inch photonics platform
Y. Cao, G. F. Chen, C. Lau, L. Y. M. Tobing, S. L. H. Jang, Y. F. Tsang, J. O. Yoo, Y. T. Toh, J. S. Goh, L. W. Lim, C. W. Wong, D. K. T. Ng, D. T. H. Tan, X. Luo
https://arxiv.org/abs/2507.17287

Frequency comb generation in low-loss, low-stress, high-Q deuterated silicon nitride microring resonators in an 8-inch photonics platform
Systematic studies on different SiN films in terms of propagation losses are presented, and deuterated SiN emerges as a good candidate for ultralow loss (< 0.1 dB/cm) and reliability by simple 8-inch process with low thermal budget. Frequency comb generation in high-Q (~1 million) deuterated silicon nitride microring is demonstrated and used for intensity modulated direct detection transmission. Negligible power penalty for 25.78 GBaud/s NRZ and PAM4 is achieved at error rates <10-6, below the …

HelixDesign-Antibody: A Scalable Production-Grade Platform for Antibody Design Built on HelixFold3
Jie Gao, Jing Hu, Shanzhuo Zhang, Kunrui Zhu, Sheng Qian, Yueyang Huang, Xiaonan Zhang, Xiaomin Fang
https://arxiv.org/abs/2507.02345

HelixDesign-Antibody: A Scalable Production-Grade Platform for Antibody Design Built on HelixFold3
Antibody engineering is essential for developing therapeutics and advancing biomedical research. Traditional discovery methods often rely on time-consuming and resource-intensive experimental screening. To enhance and streamline this process, we introduce a production-grade, high-throughput platform built on HelixFold3, HelixDesign-Antibody, which utilizes the high-accuracy structure prediction model, HelixFold3. The platform facilitates the large-scale generation of antibody candidate sequence…

ReCatcher: Towards LLMs Regression Testing for Code Generation
Altaf Allah Abbassi, Leuson Da Silva, Amin Nikanjam, Foutse Khomh
https://arxiv.org/abs/2507.19390 https://…

ReCatcher: Towards LLMs Regression Testing for Code Generation
Large Language Models (LLMs) for code generation evolve rapidly through fine-tuning, merging, or new model releases. However, such updates can introduce regressions, not only in correctness but also in code quality and performance. To address this, we present ReCatcher, a regression testing framework for Python code generation. ReCatcher systematically compares two LLMs, typically a current model and a candidate update, across three dimensions: logical correctness, static code quality, and exec…

Robust Task Offloading for UAV-enabled Secure MEC Against Aerial Eavesdropper
Can Cui, ZIye Jia, Chao Dong, Qihui Wu
https://arxiv.org/abs/2507.00710 https…

Robust Task Offloading for UAV-enabled Secure MEC Against Aerial Eavesdropper
Unmanned aerial vehicles (UAVs) are recognized as a promising candidate for the multi-access edge computing (MEC) in the future sixth generation communication networks. However, the aerial eavesdropping UAVs (EUAVs) pose a significant security threat to the data offloading. In this paper, we investigate a robust MEC scenario with multiple service UAVs (SUAVs) towards the potential eavesdropping from the EUAV, in which the random parameters such as task complexities are considered in the practic…

Democratizing News Recommenders: Modeling Multiple Perspectives for News Candidate Generation with VQ-VAE
Hardy, Sebastian Pad\'o, Amelie W\"uhrl, Tanise Ceron
https://arxiv.org/abs/2508.13978

Democratizing News Recommenders: Modeling Multiple Perspectives for News Candidate Generation with VQ-VAE
Current News Recommender Systems based on past clicks are designed for engagement, but come at the cost of limiting diversity in the suggested content. While diversity-aware algorithms exist, they suffer from two major limitations. First, they fail to account for normative diversity, which requires fair access to a broad range of perspectives. Second, they typically apply diversity late in the system's pipeline, after a lot of content has already been filtered out. Both limitations confine thei…

Affine Frequency Division Multiplexing (AFDM) for 6G: Properties, Features, and Challenges
Hyeon Seok Rou, Kuranage Roche Rayan Ranasinghe, Vincent Savaux, Giuseppe Thadeu Freitas de Abreu, David Gonz\'alez G., Christos Masouros
https://arxiv.org/abs/2507.21704

Affine Frequency Division Multiplexing (AFDM) for 6G: Properties, Features, and Challenges
Affine frequency division multiplexing (AFDM) is an emerging waveform candidate for future sixth generation (6G) systems offering a range of promising features, such as enhanced robustness in heterogeneous and high-mobility environments, as well as inherent suitability for integrated sensing and communications (ISAC) applications. In addition, unlike other candidates such as orthogonal time-frequency space (OTFS) modulation, AFDM provides several unique advantages that strengthen its relevance …

Phase Competition and Rutile Phase Stabilization of Growing GeO2 Films by MOCVD
Imteaz Rahaman, Botong Li, Hunter D. Ellis, Kathy Anderson, Feng Liu, Michael A. Scarpulla, Kai Fu
https://arxiv.org/abs/2507.22430

Phase Competition and Rutile Phase Stabilization of Growing GeO2 Films by MOCVD
Rutile germanium dioxide (r-GeO2) is an ultra-wide bandgap semiconductor with potential for ambipolar doping, making it a promising candidate for next-generation power electronics and optoelectronics. Growth of phase-pure r-GeO2 films by vapor phase techniques like metalorganic chemical vapor deposition (MOCVD) is challenging because of polymorphic competition from amorphous and quartz GeO2. Here, we introduce seed-driven stepwise crystallization (SDSC) as a segmented growth strategy for obtain…

JointRank: Rank Large Set with Single Pass
Evgeny Dedov
https://arxiv.org/abs/2506.22262 https://arxiv.org/pdf/2506.22262

JointRank: Rank Large Set with Single Pass
Efficiently ranking relevant items from large candidate pools is a cornerstone of modern information retrieval systems -- such as web search, recommendation, and retrieval-augmented generation. Listwise rerankers, which improve relevance by jointly considering multiple candidates, are often limited in practice: either by model input size constraints, or by degraded quality when processing large sets. We propose a model-agnostic method for fast reranking large sets that exceed a model input limi…

Toughening beta-Ga2O3 via mechanically seeded dislocations
Zanlin Cheng, Jiawen Zhang, Peng Gao, Guosong Zeng, Xufei Fang, Wenjun Lu
https://arxiv.org/abs/2508.20439 https://

Toughening beta-Ga2O3 via mechanically seeded dislocations
\b{eta}-Ga2O3 is a promising candidate for next-generation semiconductors, but is limited by its intrinsic brittleness, which hinders its application in flexible electronics and high-precision devices. This study explores a new approach to improving the damage tolerance of (001)-oriented \b{eta}-Ga2O3 by introducing mechanically seeded dislocations via surface scratching. By applying a Brinell indenter to scratch the surface along the [100] direction, we effectively generate edge-type dislocati…

Adding colour to the Zernike wavefront sensor: Advantages of including multi-wavelength measurements for wavefront reconstruction
M. Darcis, S. Y. Haffert, V. Chambouleyron, D. S. Doelman, P. J. de Visser, M. A. Kenworthy
https://arxiv.org/abs/2508.15458

Adding colour to the Zernike wavefront sensor: Advantages of including multi-wavelength measurements for wavefront reconstruction
To directly image Earth-like planets, contrast levels of 10^-8 - 10^-10 are required. The next generation of instruments will need wavefront control below the nanometer level to achieve these goals. The Zernike wavefront sensor (ZWFS) is a promising candidate thanks to its sensitivity, which reaches the fundamental quantum information limits. However, its highly non-linear response restricts its practical use case. We aim to demonstrate the improvement in robustness of the ZWFS by reconstructin…

A Comprehensive Review on Harnessing Large Language Models to Overcome Recommender System Challenges
Rahul Raja, Anshaj Vats, Arpita Vats, Anirban Majumder
https://arxiv.org/abs/2507.21117

A Comprehensive Review on Harnessing Large Language Models to Overcome Recommender System Challenges
Recommender systems have traditionally followed modular architectures comprising candidate generation, multi-stage ranking, and re-ranking, each trained separately with supervised objectives and hand-engineered features. While effective in many domains, such systems face persistent challenges including sparse and noisy interaction data, cold-start problems, limited personalization depth, and inadequate semantic understanding of user and item content. The recent emergence of Large Language Model…

Meta-Reinforcement Learning Optimization for Movable Antenna-aided Full-Duplex CF-DFRC Systems with Carrier Frequency Offset
Yue Xiu, Wanting Lyu, You Li, Ran Yang, Phee Lep Yeoh, Wei Zhang, Guangyi Liu, Ning Wei
https://arxiv.org/abs/2507.16132

Meta-Reinforcement Learning Optimization for Movable Antenna-aided Full-Duplex CF-DFRC Systems with Carrier Frequency Offset
By enabling spectrum sharing between radar and communication operations, the cell-free dual-functional radar-communication (CF-DFRC) system is a promising candidate to significantly improve spectrum efficiency in future sixth-generation (6G) wireless networks. However, in wideband scenarios, synchronization errors caused by carrier frequency offset (CFO) can severely reduce both communication capacity and sensing accuracy. To address this challenge, this paper integrates movable antennas (MAs) …