Tootfinder

HTTP Request Synchronization Defeats Discrepancy Attacks
Cem Topcuoglu, Kaan Onarlioglu, Steven Sprecher, Engin Kirda
https://arxiv.org/abs/2510.09952 https://

HTTP Request Synchronization Defeats Discrepancy Attacks
Contemporary web application architectures involve many layers of proxy services that process traffic. Due to the complexity of HTTP and vendor design decisions, these proxies sometimes process a given request in different ways. Attackers can exploit these processing discrepancies to launch damaging attacks including web cache poisoning and request smuggling. Discrepancy attacks are surging, yet, there exists no systemic defense. In this work, we propose the first comprehensive defense to add…

Entropy Engineering-Regulated Electron-Phonon Coupling for Highly Efficient Photoluminescence in Se-doped WS2
Chi Zhang, Quan Shen, Mengmeng Zhang, Zhiming Deng, Taishen Wu, Xuying Zhong, Gang Ouyang, Dongsheng Tang, Qi Zheng, Jiansheng Dong, Weichang Zhou
https://arxiv.org/abs/2510.11081

Entropy Engineering-Regulated Electron-Phonon Coupling for Highly Efficient Photoluminescence in Se-doped WS2
The limited quantum yield of strained monolayer transition metal dichalcogenides grown by vapor-phase methods and during transfer-based stacking poses a fundamental challenge for their optoelectronic applications. Here, we introduce the concept of "entropy engineering" as a transformative strategy to selectively enhance light-matter interactions through controlled electron-phonon coupling. We unveil how tailored entropy introduced via precise selenium doping or interfacial van der Waals proximi…

Large Language Model Prompt Datasets: An In-depth Analysis and Insights
Yuanming Zhang, Yan Lin, Arijit Khan, Huaiyu Wan
https://arxiv.org/abs/2510.09316 https://

Large Language Model Prompt Datasets: An In-depth Analysis and Insights
A prompt is a natural language instruction that defines a specific task for a large language model (LLM) and serves as the primary interface for human-LLM interaction. With the growing deployment of LLMs, diverse prompt datasets are emerging from platforms such as GitHub and social media. These datasets span a wide array of applications and content types, facilitating both broader LLM utilization and improved prompt engineering. In this work, we--for the first time--have compiled an extensive l…

Band Gap Engineering of Nitrogen-Doped Monolayer WSe$_2$ Superlattice and its application to Field Effect Transistor
Yi-Cheng Lo, Liao Jia Wang, Yu-Chang Chen
https://arxiv.org/abs/2510.01917

Band Gap Engineering of Nitrogen-Doped Monolayer WSe$_2$ Superlattice and its application to Field Effect Transistor
We systematically investigate the electronic structures of pristine monolayer WSe$_2$ and WSe$_2$ superlattices with periodic nitrogen substitution. Unlike random doping, which often introduces in-gap impurity states, periodic nitrogen doping primarily modulates the band gap, thereby facilitating effective band gap engineering for electronic and optoelectronic applications. The gap narrows monotonically with increasing dopant density (pristine $>$ 8-row $>$ 6-row $>$ 4-row), directly influencin…

Backdoor-Powered Prompt Injection Attacks Nullify Defense Methods
Yulin Chen, Haoran Li, Yuan Sui, Yangqiu Song, Bryan Hooi
https://arxiv.org/abs/2510.03705 https://

Backdoor-Powered Prompt Injection Attacks Nullify Defense Methods
With the development of technology, large language models (LLMs) have dominated the downstream natural language processing (NLP) tasks. However, because of the LLMs' instruction-following abilities and inability to distinguish the instructions in the data content, such as web pages from search engines, the LLMs are vulnerable to prompt injection attacks. These attacks trick the LLMs into deviating from the original input instruction and executing the attackers' target instruction. Recently, var…

Deterministic Detection of Single Ion Implantation
Mason Adshead, Lok Kan Wan, Maddison Coke, Richard J Curry
https://arxiv.org/abs/2510.01035 https://arxi…

Deterministic Detection of Single Ion Implantation
Single ion implantation using focused ion beam systems enables high spatial resolution and maskless doping for rapid and scalable engineering of materials for quantum technologies, particularly qubits and colour centres in solid-state hosts. In such applications, the confidence with which a single ion can be deterministically implanted is crucial, and so the efficiency of the detection mechanism is a vital parameter. Here, we present a study of the single-ion detection efficiency for a variety …

Hexagonal boron nitride/bilayer graphene moir\'e superlattices in the Dirac-material family: energy-band engineering and carrier doping by dual gating
Takuya Iwasaki, Yoshifumi Morita
https://arxiv.org/abs/2509.21759

Hexagonal boron nitride/bilayer graphene moiré superlattices in the Dirac-material family: energy-band engineering and carrier doping by dual gating
We review the fabrication and transport characterization of hexagonal boron nitride (hBN)/Bernal bilayer graphene (BLG) moiré superlattices. Due to the moiré effect, the hBN/BLG moiré superlattices exhibit an energy gap at the charge neutrality point (CNP) even in the absence of a perpendicular electric field. In BLG, the application of a perpendicular electric field tunes the energy gap at the CNP, which contrasts with single-layer graphene and is similar to the family of rhombohedral multi…

SafeSteer: Adaptive Subspace Steering for Efficient Jailbreak Defense in Vision-Language Models
Xiyu Zeng, Siyuan Liang, Liming Lu, Haotian Zhu, Enguang Liu, Jisheng Dang, Yongbin Zhou, Shuchao Pang
https://arxiv.org/abs/2509.21400

SafeSteer: Adaptive Subspace Steering for Efficient Jailbreak Defense in Vision-Language Models
As the capabilities of Vision Language Models (VLMs) continue to improve, they are increasingly targeted by jailbreak attacks. Existing defense methods face two major limitations: (1) they struggle to ensure safety without compromising the model's utility; and (2) many defense mechanisms significantly reduce the model's inference efficiency. To address these challenges, we propose SafeSteer, a lightweight, inference-time steering framework that effectively defends against diverse jailbreak atta…

Orbital-Engineered Spin Asymmetry and Multifunctionality in Eu-Activated CaAlSiN$_3$: A First-Principles Roadmap to Optical-Thermoelectric Fusion
Muhammad Tayyab, Faiq Umar, Sikander Azam, Qaiser Rafiq, Rajwali Khan, Muhammad Tahir Khan, Vineet Tirth, Ali Algahtani
https://arxiv.org/abs/2510.00863 …

Orbital-Engineered Spin Asymmetry and Multifunctionality in Eu-Activated CaAlSiN$_3$: A First-Principles Roadmap to Optical-Thermoelectric Fusion
Rare-earth-doped nitride phosphors are promising materials for solid-state lighting and photonic applications due to their thermal stability, sharp emission lines, and strong UV-blue absorption. In this work, we present a first-principles density functional theory (DFT) study, using the GGA+U approach, of pristine and Eu3+-doped CaAlSiN3 at doping levels of 8.5% and 17%. Electronic structure calculations show that Eu incorporation introduces localized 4f states within the band gap, leading to b…

Binary Diff Summarization using Large Language Models
Meet Udeshi, Venkata Sai Charan Putrevu, Prashanth Krishnamurthy, Prashant Anantharaman, Sean Carrick, Ramesh Karri, Farshad Khorrami
https://arxiv.org/abs/2509.23970

Binary Diff Summarization using Large Language Models
Security of software supply chains is necessary to ensure that software updates do not contain maliciously injected code or introduce vulnerabilities that may compromise the integrity of critical infrastructure. Verifying the integrity of software updates involves binary differential analysis (binary diffing) to highlight the changes between two binary versions by incorporating binary analysis and reverse engineering. Large language models (LLMs) have been applied to binary analysis to augment …