Tootfinder

Iterative Partition Search Variational Quantum Algorithm for Solving Shortest Vector Problem
Zi-Wen Huang, Xiao-Hui Ni, Jia-Cheng Fan, Su-Juan Qin, Wei Huang, Bing-Jie Xu, Fei Gao
https://arxiv.org/abs/2508.18996

Iterative Partition Search Variational Quantum Algorithm for Solving Shortest Vector Problem
The Partition Search Algorithm (PSA) and the Iterative Quantum Optimization with an Adaptive Problem (IQOAP) framework are two existing Variational Quantum Algorithms (VQAs) for solving the Shortest Vector Problem (SVP), but both suffer from certain limitations. In this work, we proposed the Iterative Partition Search Algorithm (IPSA), which is a targeted synthesis and refinement of these preceding methods. Our algorithm inherits the core idea of ``partitioning to circumvent the zero vector" fr…

Monocular Vision-Based Swarm Robot Localization Using Equilateral Triangular Formations
Taewon Kang, Ji-Wook Kwon, Il Bae, Jin Hyo Kim
https://arxiv.org/abs/2507.19100 https://

Monocular Vision-Based Swarm Robot Localization Using Equilateral Triangular Formations
Localization of mobile robots is crucial for deploying robots in real-world applications such as search and rescue missions. This work aims to develop an accurate localization system applicable to swarm robots equipped only with low-cost monocular vision sensors and visual markers. The system is designed to operate in fully open spaces, without landmarks or support from positioning infrastructures. To achieve this, we propose a localization method based on equilateral triangular formations. By …

RegScore: Scoring Systems for Regression Tasks
Michal K. Grzeszczyk, Tomasz Szczepa\'nski, Pawel Renc, Siyeop Yoon, Jerome Charton, Tomasz Trzci\'nski, Arkadiusz Sitek
https://arxiv.org/abs/2507.19155

RegScore: Scoring Systems for Regression Tasks
Scoring systems are widely adopted in medical applications for their inherent simplicity and transparency, particularly for classification tasks involving tabular data. In this work, we introduce RegScore, a novel, sparse, and interpretable scoring system specifically designed for regression tasks. Unlike conventional scoring systems constrained to integer-valued coefficients, RegScore leverages beam search and k-sparse ridge regression to relax these restrictions, thus enhancing predictive per…

Simple Stepsize for Quasi-Newton Methods with Global Convergence Guarantees
Artem Agafonov, Vladislav Ryspayev, Samuel Horv\'ath, Alexander Gasnikov, Martin Tak\'a\v{c}, Slavomir Hanzely
https://arxiv.org/abs/2508.19712

Simple Stepsize for Quasi-Newton Methods with Global Convergence Guarantees
Quasi-Newton methods are widely used for solving convex optimization problems due to their ease of implementation, practical efficiency, and strong local convergence guarantees. However, their global convergence is typically established only under specific line search strategies and the assumption of strong convexity. In this work, we extend the theoretical understanding of Quasi-Newton methods by introducing a simple stepsize schedule that guarantees a global convergence rate of ${O}(1/k)$ for…

The UK CMA giving Google "strategic market status" could allow publishers to opt out of Google AI Overviews without removing websites from search (Dominic Ponsford/Press Gazette)
https://pressgazette.co.uk/platforms/cma-to…

CMA set to force Google to work more fairly with UK publishers
CMA sets out plans to start curbing Google power in the UK and will address secrecy and unfairness around Google AI Overviews.

"AI Generated Algorithmic Virality"
https://aiforensics.org/work/gen-ai-slop
A recent report by
@…
🔹 "25% of…

AI Generated Algorithmic Virality
This investigation systematically analyzes AI-generated content across TikTok and Instagram in three European countries. We found that 25% of TikTok's top search results contain synthetic AI imagery, with over 80% produced by "Agentic AI Accounts." Despite platforms' DSA commitments, only half of AI content receives proper labeling, creating significant risks for users.

A Heuristic Algorithm for Shortest Path Search
Huashan Yu, Xiaolin Wang, Yingwei Luo
https://arxiv.org/abs/2506.19349 https://arxiv.o…

A Heuristic Algorithm for Shortest Path Search
The Single-Source Shortest Path (SSSP) problem is well-known for the challenges in developing fast, practical, and work-efficient parallel algorithms. This work introduces a novel shortest path search method. It allows paths with different lengths to be extended in parallel at the cost of almost negligible repeated relaxations. A dynamic-stepping heuristic is proposed for the method to efficiently reduce the extended paths and the synchronizations. A traversal-optimization heuristic is proposed…

Tunable quantum anomalous Hall effect in fullerene monolayers
Leonard Werner Pingen, Jiaqi Wu, Bo Peng
https://arxiv.org/abs/2508.19849 https://arxiv.org/p…

Tunable quantum anomalous Hall effect in fullerene monolayers
Nearly four decades after its theoretical prediction, the search for material realizations of quantum anomalous Hall effect (QAHE) remains a highly active field of research. Many materials have been predicted to exhibit quantum anomalous Hall (QAH) physics under feasible conditions but the experimental verification remains widely elusive. In this work, we propose an alternative approach towards QAH materials design by engineering customized molecular building blocks. We demonstrate this ansatz …

Prediction of Ambient-Pressure High-Temperature Superconductivity in Doped Transition-Metal Hydrides
Haowei Xu, Olivia Schneble, Rafael Jaramillo, Marek Pola\'nski, Ju Li
https://arxiv.org/abs/2507.19768

Prediction of Ambient-Pressure High-Temperature Superconductivity in Doped Transition-Metal Hydrides
The search for conventional superconductors with high transition temperatures ($T_c$) has largely focused on intrinsically metallic compounds. In this work, we explore the potential of intrinsically non-metallic compounds to exhibit high-$T_c$ superconductivity under ambient pressure through carrier doping. We identify $\rm MgAlFeH_6$, a representative of carrier-doped transition-metal hydrides like $\rm Mg_2FeH_6$, as a promising example with a predicted $T_c \approx 130~\rm K$. We propose tha…

Managing level of detail through head-tracked peripheral degradation: a model and resulting design principles
Benjamin Watson, Neff Walker, Larry F Hodges
https://arxiv.org/abs/2506.21456

Managing level of detail through head-tracked peripheral degradation: a model and resulting design principles
Previous work has demonstrated the utility of reductions in the level of detail (LOD) in the periphery of head-tracked, large field of view displays. This paper provides a psychophysically based model, centered around an eye/head movement tradeoff, that explains the effectiveness of peripheral degradation and suggests how peripherally degraded displays should be designed. An experiment evaluating the effect on search performance of the shape and area of the high detail central area (inset) in p…

This https://arxiv.org/abs/2505.03071 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_ees…

The Search for Squawk: Agile Modeling in Bioacoustics
Passive acoustic monitoring (PAM) has shown great promise in helping ecologists understand the health of animal populations and ecosystems. However, extracting insights from millions of hours of audio recordings requires the development of specialized recognizers. This is typically a challenging task, necessitating large amounts of training data and machine learning expertise. In this work, we introduce a general, scalable and data-efficient system for developing recognizers for novel bioacoust…

Attribute Filtering in Approximate Nearest Neighbor Search: An In-depth Experimental Study
Mocheng Li, Xiao Yan, Baotong Lu, Yue Zhang, James Cheng, Chenhao Ma
https://arxiv.org/abs/2508.16263

Attribute Filtering in Approximate Nearest Neighbor Search: An In-depth Experimental Study
With the growing integration of structured and unstructured data, new methods have emerged for performing similarity searches on vectors while honoring structured attribute constraints, i.e., a process known as Filtering Approximate Nearest Neighbor (Filtering ANN) search. Since many of these algorithms have only appeared in recent years and are designed to work with a variety of base indexing methods and filtering strategies, there is a pressing need for a unified analysis that identifies thei…

Dark Matter Haloscope with a Disordered Dielectric Absorber
Stewart Koppell, Otavio D. A. R. Bittencourt, Dip Joti Paul, Junwu Huang, Masha Baryakhtar, Karl K. Berggren
https://arxiv.org/abs/2506.00115

Dark Matter Haloscope with a Disordered Dielectric Absorber
Light dark matter candidates such as axions and dark photons generically couple to electromagnetism, yielding dark-matter-to-photon conversion as a key search strategy. In addition to resonant conversion in cavities and circuits, light dark matter bosons efficiently convert to photons on material interfaces, with a broadband power proportional to the total area of these interfaces. In this work, we make use of interface conversion to develop a new experimental dark matter detector design: the d…

Sequence-to-Sequence Models with Attention Mechanistically Map to the Architecture of Human Memory Search
Nikolaus Salvatore, Qiong Zhang
https://arxiv.org/abs/2506.17424

Sequence-to-Sequence Models with Attention Mechanistically Map to the Architecture of Human Memory Search
Past work has long recognized the important role of context in guiding how humans search their memory. While context-based memory models can explain many memory phenomena, it remains unclear why humans develop such architectures over possible alternatives in the first place. In this work, we demonstrate that foundational architectures in neural machine translation -- specifically, recurrent neural network (RNN)-based sequence-to-sequence models with attention -- exhibit mechanisms that directly…

Software Model Checking via Summary-Guided Search (Extended Version)
Ruijie Fang, Zachary Kincaid, Thomas Reps
https://arxiv.org/abs/2508.15137 https://arx…

Software Model Checking via Summary-Guided Search (Extended Version)
In this work, we describe a new software model-checking algorithm called GPS. GPS treats the task of model checking a program as a directed search of the program states, guided by a compositional, summary-based static analysis. The summaries produced by static analysis are used both to prune away infeasible paths and to drive test generation to reach new, unexplored program states. GPS can find both proofs of safety and counter-examples to safety (i.e., inputs that trigger bugs), and features a…

In silico investigation of Ba-based ternary chalcogenides for photovoltaic applications
Ramya Kormath Madam Raghupathy, Hossein Mirhosseini, Thomas D. K\"uhne
https://arxiv.org/abs/2508.18796

In silico investigation of Ba-based ternary chalcogenides for photovoltaic applications
In solar cells, the absorbers are the key components for capturing solar energy and converting photons into electron-hole pairs. The search for high-performance absorbers with advantageous characteristics is an ongoing task for researchers. In this work, we investigated promising and environmentally benign Ba-based ternary chalcogenides for photovoltaic applications. The total number of Ba-based ternary chalcogenides in the Materials Project database was found to be 279. Materials screening bas…

Bayesian Optimization-based Search for Agent Control in Automated Game Testing
Carlos Celemin
https://arxiv.org/abs/2508.13121 https://arxiv.org/pdf/2508.1…

Bayesian Optimization-based Search for Agent Control in Automated Game Testing
This work introduces an automated testing approach that employs agents controlling game characters to detect potential bugs within a game level. Harnessing the power of Bayesian Optimization (BO) to execute sample-efficient search, the method determines the next sampling point by analyzing the data collected so far and calculates the data point that will maximize information acquisition. To support the BO process, we introduce a game testing-specific model built on top of a grid map, that featu…

Search for the in-situ production of $^{77}$Ge in the GERDA neutrinoless double-beta decay experiment
M. Agostini, A. Alexander, G. Araujo, A. M. Bakalyarov, M. Balata, I. Barabanov, L. Baudis, C. Bauer, S. Belogurov, A. Bettini, L. Bezrukov, V. Biancacci, E. Bossio, V. Bothe, R. Brugnera, A. Caldwell, S. Calgaro, C. Cattadori, A. Chernogorov, P. -J. Chiu, T. Comellato, V. D'Andrea, E. V. Demidova, N. Di Marco, E. Doroshkevich, M. Fomina, A. Gangapshev, A. Garfagnini, C. Gooch, P. …

Search for the in-situ production of $^{77}$Ge in the GERDA neutrinoless double-beta decay experiment
The beta decay of $^{77}$Ge and $^{77\mathrm{m}}$Ge, both produced by neutron capture on $^{76}$Ge, is a potential background for Germanium based neutrinoless double-beta decay search experiments such as GERDA or the LEGEND experiment. In this work we present a search for $^{77}$Ge decays in the full GERDA Phase II data set. A delayed coincidence method was employed to identify the decay of $^{77}$Ge via the isomeric state of $^{77}$As (9/2$^+$, 475 keV, ${T_{1/2} = 114}\,μ$s, $^{77\mathrm{m}}…

MorphoNAS: Embryogenic Neural Architecture Search Through Morphogen-Guided Development
Mykola Glybovets, Sergii Medvid
https://arxiv.org/abs/2507.13785 htt…

MorphoNAS: Embryogenic Neural Architecture Search Through Morphogen-Guided Development
While biological neural networks develop from compact genomes using relatively simple rules, modern artificial neural architecture search methods mostly involve explicit and routine manual work. In this paper, we introduce MorphoNAS (Morphogenetic Neural Architecture Search), a system able to deterministically grow neural networks through morphogenetic self-organization inspired by the Free Energy Principle, reaction-diffusion systems, and gene regulatory networks. In MorphoNAS, simple genomes …

Back in 1964, microbiologist Tom Brock received a grant from the National Science Foundation to study how life works at high temperatures,
a question that took him to Yellowstone’s hot springs in search of extremophiles.
There, he and his student discovered a bacteria they called Thermus aquaticus,
which had enzymes that could work at incredibly high temperatures.
Two decades later, this discovery paved the way for the development of a technique called polymerase ch…

What It Would Mean To Lose The National Science Foundation
In a companion piece to our previous article on the NIH, we discuss the importance of the National Science Foundation (NSF) and how the agency is currently being affected by political interference.

There used to be this deal between Google (and other search engines) and the Web: You get to index our stuff, show ads next to them but you link our work. AI Overview and Perplexity and all these systems cancel that deal.
And maybe - for a while - search will also need to die a bit? Make the whole web uncrawlable. Refuse any bots. As an act of resistance to the tech sector as a whole.

UniECS: Unified Multimodal E-Commerce Search Framework with Gated Cross-modal Fusion
Zihan Liang, Yufei Ma, ZhiPeng Qian, Huangyu Dai, Zihan Wang, Ben Chen, Chenyi Lei, Yuqing Ding, Han Li
https://arxiv.org/abs/2508.13843

UniECS: Unified Multimodal E-Commerce Search Framework with Gated Cross-modal Fusion
Current e-commerce multimodal retrieval systems face two key limitations: they optimize for specific tasks with fixed modality pairings, and lack comprehensive benchmarks for evaluating unified retrieval approaches. To address these challenges, we introduce UniECS, a unified multimodal e-commerce search framework that handles all retrieval scenarios across image, text, and their combinations. Our work makes three key contributions. First, we propose a flexible architecture with a novel gated mu…

Noise-Resilient Spatial Search with Lackadaisical Quantum Walks
Gabriel M. O. Vieira, Nelson Maculan, Franklin de L. Marquezino
https://arxiv.org/abs/2508.13462 https://

Noise-Resilient Spatial Search with Lackadaisical Quantum Walks
Quantum walks are a powerful framework for the development of quantum algorithms, with lackadaisical quantum walks (LQWs) standing out as an efficient model for spatial search. In this work, we investigate how broken-link decoherence affects the performance of LQW-based search on a two-dimensional toroidal grid. We show through numerical simulations that, while decoherence drives the loopless walk toward a uniform distribution and eliminates its search capability, the inclusion of self-loops si…

Learning Protein-Ligand Binding in Hyperbolic Space
Jianhui Wang, Wenyu Zhu, Bowen Gao, Xin Hong, Ya-Qin Zhang, Wei-Ying Ma, Yanyan Lan
https://arxiv.org/abs/2508.15480 https://…

Learning Protein-Ligand Binding in Hyperbolic Space
Protein-ligand binding prediction is central to virtual screening and affinity ranking, two fundamental tasks in drug discovery. While recent retrieval-based methods embed ligands and protein pockets into Euclidean space for similarity-based search, the geometry of Euclidean embeddings often fails to capture the hierarchical structure and fine-grained affinity variations intrinsic to molecular interactions. In this work, we propose HypSeek, a hyperbolic representation learning framework that em…

GPU-accelerated Modeling of Biological Regulatory Networks
Joyce Reimer, Pranta Saha, Chris Chen, Neeraj Dhar, Brook Byrns, Steven Rayan, Gordon Broderick
https://arxiv.org/abs/2506.19866

GPU-accelerated Modeling of Biological Regulatory Networks
The complex regulatory dynamics of a biological network can be succinctly captured using discrete logic models. Given even sparse time-course data from the system of interest, previous work has shown that global optimization schemes are suitable for proposing logic models that explain the data and make predictions about how the system will behave under varying conditions. Considering the large scale of the parameter search spaces associated with these regulatory systems, performance optimizatio…

My great failure in life is that I never put myself in a position to monetise being this embarrassingly incompetent.
#auspol #australia #government

Hybrid Classical-Quantum Rainbow Table Attack on Human Passwords
MA. Khajeian
https://arxiv.org/abs/2507.14600 https://arxiv.org/pdf/…

Hybrid Classical-Quantum Rainbow Table Attack on Human Passwords
Passwords that are long and human-generated pose a challenge for both classical and quantum attacks due to their irregular structure and large search space. In this work, we present an enhanced classical-quantum hybrid attack tailored to this scenario. We build rainbow tables using dictionary-based password generation with transformation rules to better model real user behavior. These tables are then organized into buckets, enabling faster lookup and reduced space complexity. To perform quantum…

Differentially Private Conformal Prediction via Quantile Binary Search
Ogonnaya M. Romanus, Roberto Molinari
https://arxiv.org/abs/2507.12497 https://

Differentially Private Conformal Prediction via Quantile Binary Search
Most Differentially Private (DP) approaches focus on limiting privacy leakage from learners based on the data that they are trained on, there are fewer approaches that consider leakage when procedures involve a calibration dataset which is common in uncertainty quantification methods such as Conformal Prediction (CP). Since there is a limited amount of approaches in this direction, in this work we deliver a general DP approach for CP that we call Private Conformity via Quantile Search (P-COQS).…

A High Geometric Albedo for LTT9779b Points Towards a Metal-rich Atmosphere and Silicate Clouds
Suman Saha, James S. Jenkins, Vivien Parmentier, Sergio Hoyer, Magali Deleuil, Ian J. M. Crossfield, Pablo A. Pe\~na R., Jose I. Vines, R. Ram\'irez Reyes, Mat\'ias R. D\'iaz
https://arxiv.org/abs/2506.17550

A High Geometric Albedo for LTT9779b Points Towards a Metal-rich Atmosphere and Silicate Clouds
Aims: In this work, we aim to confirm the high albedo of the benchmark ultrahot Neptune LTT9779b using 20 secondary eclipse measurements of the planet observed with CHEOPS. In addition, we perform a search for variability in the reflected light intensity of the planet as a function of time. Methods: First, we used the TESS follow-up data of LTT9779b from three sectors (2, 29, and 69) to remodel the transit signature and estimate an updated set of transit and ephemeris parameters, which were dir…

Interesting stuff. This touches on a lot of work that was on my todo list. Especially estimating the "interestingness" of data by measuring the maximum compute needed to reach the optimal compression.
AIT is definitely becoming practically relevant.
https://arxiv.org/abs/2507.07995

Single-pass Adaptive Image Tokenization for Minimum Program Search
According to Algorithmic Information Theory (AIT) -- Intelligent representations compress data into the shortest possible program that can reconstruct its content, exhibiting low Kolmogorov Complexity (KC). In contrast, most visual representation learning systems use fixed-length representations for all inputs, ignoring variations in complexity or familiarity. Recent adaptive tokenization methods address this by allocating variable-length representations but typically require test-time search o…

Graph theory inspired anomaly detection at the LHC
Jack Y. Araz, Dimitrios Athanasakos, Mateusz Ploskon, Felix Ringer
https://arxiv.org/abs/2506.19920 http…

Graph theory inspired anomaly detection at the LHC
Designing model-independent anomaly detection algorithms for analyzing LHC data remains a central challenge in the search for new physics, due to the high dimensionality of collider events. In this work, we develop a graph autoencoder as an unsupervised, model-agnostic tool for anomaly detection, using the LHC Olympics dataset as a benchmark. By representing jet constituents as a graph, we introduce a method to systematically control the information available to the model through sparse graph c…

With a little experience, it's easy to identify website search queries that don't work. In this session, @… used live examples from several high-profile websites to demonstrate how to effectively break search. He explained what is meant by 'broken' search, the different types of failure and what these problems reveal about the underlying search…

Series D, Episode 05 - Animals
SERVALAN: Your work and the animals.
JUSTIN: My work is destroyed.
SERVALAN: Then you die. Both of you.
DAYNA: It's in his head. He said so.
https://blake.torpidity.net/m/405/386 B7B2

Blakes7Bot | Search
Companion site to the Blakes7Bot Twitter, Mastodon, and Bluesky accounts. Automated lines of Blakes 7 dialog. Includes a script search facility.

Queen Domination by SAT Solving
Taha Rostami, Curtis Bright
https://arxiv.org/abs/2508.11945 https://arxiv.org/pdf/2508.11945

Queen Domination by SAT Solving
The queen domination problem asks for the minimum number of queens needed to attack all squares on an $n\times n$ chessboard. Once this optimal number is known, determining the number of distinct solutions up to isomorphism has also attracted considerable attention. Previous work has introduced specialized and highly optimized search procedures to address open instances of the problem. While efficient in terms of runtime, these approaches have not provided proofs that can be independently verif…

Efficiently Constructing Sparse Navigable Graphs
Alex Conway, Laxman Dhulipala, Martin Farach-Colton, Rob Johnson, Ben Landrum, Christopher Musco, Yarin Shechter, Torsten Suel, Richard Wen
https://arxiv.org/abs/2507.13296

Efficiently Constructing Sparse Navigable Graphs
Graph-based nearest neighbor search methods have seen a surge of popularity in recent years, offering state-of-the-art performance across a wide variety of applications. Central to these methods is the task of constructing a sparse navigable search graph for a given dataset endowed with a distance function. Unfortunately, doing so is computationally expensive, so heuristics are universally used in practice. In this work, we initiate the study of fast algorithms with provable guarantees for se…

"Brain-only participants exhibited the strongest, most distributed networks; Search Engine users showed moderate engagement; and LLM users displayed the weakest connectivity."
"LLM users also struggled to accurately quote their own work."
"Over four months, LLM users consistently underperformed at neural, linguistic, and behavioral levels."

🔊 #NowPlaying on #BBCRadio3:
#SundayFeature
- New Generation Thinkers: How Lullabies Work
New Generation Thinker, historian Oskar Jensen, explores the history of lullabies, in search of the power and the know-how that makes Hush-a-bye Baby do what it says in the title.
Relisten now 👇
https://www.bbc.co.uk/programmes/m002dcdj

Safety Assurance for Quadrotor Kinodynamic Motion Planning
Theodoros Tavoulareas, Marzia Cescon
https://arxiv.org/abs/2507.17679 https://arxiv.org/pdf/2507…

Safety Assurance for Quadrotor Kinodynamic Motion Planning
Autonomous drones have gained considerable attention for applications in real-world scenarios, such as search and rescue, inspection, and delivery. As their use becomes ever more pervasive in civilian applications, failure to ensure safe operation can lead to physical damage to the system, environmental pollution, and even loss of human life. Recent work has demonstrated that motion planning techniques effectively generate a collision-free trajectory during navigation. However, these methods, w…

Sources: Apple formed an Answers, Knowledge, and Information team to work on ChatGPT-like search experiences; iPhone 17 Pro may have been seen in live testing (Mark Gurman/Bloomberg)
https://www.bloomberg.com/news/newsletters

I'll test it on Apples.
I use the Orion browser on Apple computers. EFF's attempting to tell advertisers to USE EXPLICIT METHODS to control ads, and our privacy.
The Orion browser has its own "advanced" blockers.
But because it has Firefox extensions, it should "work" in Orion (the free browser by search engine company Kagi). Also, on iPads and iPhones, extensions work in Orion, but not Safari.
Privacy is a Human Right.

FIRE-GNN: Force-informed, Relaxed Equivariance Graph Neural Network for Rapid and Accurate Prediction of Surface Properties
Circe Hsu, Claire Schlesinger, Karan Mudaliar, Jordan Leung, Robin Walters, Peter Schindler
https://arxiv.org/abs/2508.16012

FIRE-GNN: Force-informed, Relaxed Equivariance Graph Neural Network for Rapid and Accurate Prediction of Surface Properties
The work function and cleavage energy of a surface are critical properties that determine the viability of materials in electronic emission applications, semiconductor devices, and heterogeneous catalysis. While first principles calculations are accurate in predicting these properties, their computational expense combined with the vast search space of surfaces make a comprehensive screening approach with density functional theory (DFT) infeasible. Here, we introduce FIRE-GNN (Force-Informed, Re…

Rethinking Click Models in Light of Carousel Interfaces: Theory-Based Categorization and Design of Click Models
Jingwei Kang, Maarten de Rijke, Santiago de Leon-Martinez, Harrie Oosterhuis
https://arxiv.org/abs/2506.18548

Rethinking Click Models in Light of Carousel Interfaces: Theory-Based Categorization and Design of Click Models
Click models are a well-established for modeling user interactions with web interfaces. Previous work has mainly focused on traditional single-list web search settings; this includes existing surveys that introduced categorizations based on the first generation of probabilistic graphical model (PGM) click models that have become standard. However, these categorizations have become outdated, as their conceptualizations are unable to meaningfully compare PGM with neural network (NN) click models …

The Trump administration has dealt a sharp blow to work on H.I.V. vaccines, terminating a $258 million program whose work was instrumental to the search for a vaccine.
Officials from the H.I.V. division of the National Institutes of Health delivered the news on Friday to the program’s two leaders, at Duke University and the Scripps Research Institute.
Both teams were collaborating with numerous other research partners.
The work was broadly applicable to a wide range of treatm…

Trump Administration Ends Program Critical to Search for an H.I.V. Vaccine
The termination is the latest in a series of cuts to H.I.V. research and programs to prevent the disease.

New study on the effects of LLM use (in this case on essay writing):
https://arxiv.org/abs/2506.08872
Quote:
"LLM users also struggled to accurately quote their own work. While LLMs offer immediate convenience, our findings highlight potential cognitive costs. Over four month…

Your Brain on ChatGPT: Accumulation of Cognitive Debt when Using an AI Assistant for Essay Writing Task
This study explores the neural and behavioral consequences of LLM-assisted essay writing. Participants were divided into three groups: LLM, Search Engine, and Brain-only (no tools). Each completed three sessions under the same condition. In a fourth session, LLM users were reassigned to Brain-only group (LLM-to-Brain), and Brain-only users were reassigned to LLM condition (Brain-to-LLM). A total of 54 participants took part in Sessions 1-3, with 18 completing session 4. We used electroencephalo…

Unraveling dark Higgs mechanism via dark photon production at an e^ e^- collider
Song Li, Jin Min Yang, Mengchao Zhang, Yang Zhang, Rui Zhu
https://arxiv.org/abs/2506.20208

Unraveling dark Higgs mechanism via dark photon production at an e^+ e^- collider
In the phenomenology study of dark photon, its mass origin is usually not considered. But in the theory construction, its mass is often generated via a dark Higgs mechanism, which predicts a dark Higgs particle. In this work, we study the impact of such a light (non-decoupled) dark Higgs particle in the collider detection of the dark photon. Assuming both the dark photon and dark Higgs decay invisibly, the search for dark photon via its photon-associated production would be affected by the dark…

In This Thread: denizens of debian-user mailing list who refuse to accept that there are people who do creative work without wanting to use email.
Apparently it is only "kids" who "don't understand what is important", who "have a mobile phone glued to their hand" and "don't care about their computer as long as it plays their games."

Dynamic Sub-region Search in Homogeneous Collections Using CLIP
Bastian J\"ackl, Vojt\v{e}ch Kloda, Daniel A. Keim, Jakub Loko\v{c}
https://arxiv.org/abs/2506.09506

Dynamic Sub-region Search in Homogeneous Collections Using CLIP
Querying with text-image-based search engines in highly homogeneous domain-specific image collections is challenging for users, as they often struggle to provide descriptive text queries. For example, in an underwater domain, users can usually characterize entities only with abstract labels, such as corals and fish, which leads to low recall rates. Our work investigates whether recall can be improved by supplementing text queries with position information. Specifically, we explore dynamic image…

Hey so is search in Mail going to work now or
#WWDC25 #WWDC #AppleIntelligence

Search for gravitational waves from eccentric binary black holes with an effective-one-body template
Yi-Fan Wang, Alexander H. Nitz
https://arxiv.org/abs/2508.05018 https://

Search for gravitational waves from eccentric binary black holes with an effective-one-body template
As gravitational wave astronomy has entered an era of routine detections, it becomes increasingly important to precisely measure the physical parameters of individual events and infer population properties. Eccentricity is a key observable, suggesting that binaries form in a dense stellar environment through dynamical encounters. This work performs the first matched-filtering search for gravitational waves from eccentric binary black holes (BBHs) covering the mass range $[5, 200]~M_\odot$ and e…

Zobrist Hash-based Duplicate Detection in Symbolic Regression
Bogdan Burlacu
https://arxiv.org/abs/2508.13859 https://arxiv.org/pdf/2508.13859

Zobrist Hash-based Duplicate Detection in Symbolic Regression
Symbolic regression encompasses a family of search algorithms that aim to discover the best fitting function for a set of data without requiring an a priori specification of the model structure. The most successful and commonly used technique for symbolic regression is Genetic Programming (GP), an evolutionary search method that evolves a population of mathematical expressions through the mechanism of natural selection. In this work we analyze the efficiency of the evolutionary search in GP and…

Multi-Instrument Search for Gamma-Ray Counterpart of X-ray Transients detected by EP/WXT
Yan-Qiu Zhang, Wang-Chen Xue, Jin-Peng Zhang, Ce Cai, Shao-Lin Xiong, Cheng-Kui Li, Yuan Liu, Chen-Wei Wang, Hao-Xuan Guo, Shuo Xiao, Wen-Jun Tan, Chao Zheng, Jia-Cong Liu, Sheng-Lun Xie, Peng Zhang, Wen-Long Zhang, Yue Wang, Zheng-Hang Yu, Yang-Zhao Ren, Ping Wang, Yue Huang, Xiao-Bo Li, Xiao-Yun Zhao, Shi-Jie Zheng, Zhen Zhang, Shu-Xu Yi, Li-Ming Song, Shuang-Nan Zhang

Multi-Instrument Search for Gamma-Ray Counterpart of X-ray Transients detected by EP/WXT
As a soft X-ray imager with unprecedentedly large field of view, EP/WXT has detected many (fast) X-ray transients, whose nature is very intriguing. Whether there is gamma-ray counterpart for the X-ray transient provides important implications for its origin. Some of them have been reported to be associated with GRB, however, a systematic study on the gamma-ray emission of these X-ray transients is lacking. In this work, we implemented a comprehensive targeted search for gamma-ray counterparts t…

A Comparative Analysis on ASR System Combination for Attention, CTC, Factored Hybrid, and Transducer Models
Noureldin Bayoumi, Robin Schmitt, Tina Raissi, Albert Zeyer, Ralf Schl\"uter, Hermann Ney
https://arxiv.org/abs/2508.09880

A Comparative Analysis on ASR System Combination for Attention, CTC, Factored Hybrid, and Transducer Models
Combination approaches for speech recognition (ASR) systems cover structured sentence-level or word-based merging techniques as well as combination of model scores during beam search. In this work, we compare model combination across popular ASR architectures. Our method leverages the complementary strengths of different models in exploring diverse portions of the search space. We rescore a joint hypothesis list of two model candidates. We then identify the best hypothesis through log-linear co…

Exoplanet Atmospheric Refraction Effects in the #Kepler Sample: https://arxiv.org/abs/2507.02126 -> "We present an analysis on the detection viability of refraction effects in Kepler's exoplanet atmospheres using binning techniques for their light curves in order to compare against simulated refraction effects. We split the Kepler exoplanets into sub-populations according to orbital period and planetary radius, then search for out-of-transit changes in the relative flux associated with atmospheric refraction of starlight. The presence of refraction effects - or lack thereof - may be used to measure and set limits on the bulk properties of an atmosphere, including mean molecular weight or the presence of hazes.
In this work, we use the presence of refraction effects to test whether exoplanets above the period-radius valley have H/He atmospheres, which high levels of stellar radiation could evaporate away, in turn leaving rocky cores below the valley. We find strong observational evidence of refraction effects for exoplanets above the period-radius valley based on Kepler photometry, however those related to optically thin H/He atmospheres are not common in the observed planetary population. This result may be attributed to signal dampening caused by clouds and hazes, consistent with the optically thick and intrinsically hotter atmospheres of Kepler exoplanets caused by relatively close host star proximity."

A Versatile Dataset of Mouse and Eye Movements on Search Engine Results Pages
Kayhan Latifzadeh, Jacek Gwizdka, Luis A. Leiva
https://arxiv.org/abs/2507.08003

A Versatile Dataset of Mouse and Eye Movements on Search Engine Results Pages
We contribute a comprehensive dataset to study user attention and purchasing behavior on Search Engine Result Pages (SERPs). Previous work has relied on mouse movements as a low-cost large-scale behavioral proxy but also has relied on self-reported ground-truth labels, collected at post-task, which can be inaccurate and prone to biases. To address this limitation, we use an eye tracker to construct an objective ground-truth of continuous visual attention. Our dataset comprises 2,776 transaction…

Directed Acyclic Graph Convolutional Networks
Samuel Rey, Hamed Ajorlou, Gonzalo Mateos
https://arxiv.org/abs/2506.12218 https://arxi…

Directed Acyclic Graph Convolutional Networks
Directed acyclic graphs (DAGs) are central to science and engineering applications including causal inference, scheduling, and neural architecture search. In this work, we introduce the DAG Convolutional Network (DCN), a novel graph neural network (GNN) architecture designed specifically for convolutional learning from signals supported on DAGs. The DCN leverages causal graph filters to learn nodal representations that account for the partial ordering inherent to DAGs, a strong inductive bias d…

First Full Dalitz Plot Measurement in Neutron $\beta$-Decay using the Nab Spectrometer and Implications for New Physics
Francisco M. Gonzalez, Jin Ha Choi, Himal Acharya, Skylar Clymer, Andrew Hagemeier, David G. Mathews, August Mendelsohn, Austin Nelsen, Hitesh Rahangdale, Love Richburg, Ricardo Alarcon, Ariella Atencio, Stefan Bae{\ss}ler, Thomas Bailey, Noah Birge, Dennis Borissenko, Michael Bowler, Leah J. Broussard, Albert T. Bryant, Jimmy Caylor, Tim Chupp, Christopher Crawford, …

First Full Dalitz Plot Measurement in Neutron $β$-Decay using the Nab Spectrometer and Implications for New Physics
Precision measurements of observables in neutron $β$-decay are used to test the Standard Model description of the weak interaction and search for evidence of new physics. The Nab experiment at the Fundamental Neutron Physics Beamline at the Spallation Neutron Source was constructed to measure correlations in neutron decay by utilizing an asymmetric spectrometer and novel detection system to accurately reconstruct the proton momentum and electron energy for each $β$-decay. This work describes …

Improving and Evaluating Open Deep Research Agents
Doaa Allabadi, Kyle Bradbury, Jordan M. Malof
https://arxiv.org/abs/2508.10152 https://arxiv.org/pdf/250…

Improving and Evaluating Open Deep Research Agents
We focus here on Deep Research Agents (DRAs), which are systems that can take a natural language prompt from a user, and then autonomously search for, and utilize, internet-based content to address the prompt. Recent DRAs have demonstrated impressive capabilities on public benchmarks however, recent research largely involves proprietary closed-source systems. At the time of this work, we only found one open-source DRA, termed Open Deep Research (ODR). In this work we adapt the challenging recen…

You Don’t Have to Sell Your Art to Call Yourself an Artist
https://www.artiststrong.com/you-dont-have-to-sell-your-art-to-call-yourself-an-ar…

You Don’t Have to Sell Your Art to Call Yourself an Artist
One of the most commonly search phrases when you look at Google or Pinterest is: How To Sell Art How, How To Sell Art work How To Sell Art on Etsy How to sell Art on Instagram? How to sell art onli…

Series D, Episode 11 - Orbit
PINDER: Egrorian? Egrorian? They're here! Come and see. [Egrorian enters. He slaps Pinder away from the monitor. They look at the monitor and laugh hysterically.]
[Back on Scorpio]
https://blake.torpidity.net/m/411/9 B7B3

Blakes7Bot | Search
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Boosting Rust Unit Test Coverage through Hybrid Program Analysis and Large Language Models
Bei Chu, Yang Feng, Kui Liu, Hange Shi, Zifan Nan, Zhaoqiang Guo, Baowen Xu
https://arxiv.org/abs/2506.09002

Boosting Rust Unit Test Coverage through Hybrid Program Analysis and Large Language Models
Unit testing is essential for ensuring software reliability and correctness. Classic Search-Based Software Testing (SBST) methods and concolic execution-based approaches for generating unit tests often fail to achieve high coverage due to difficulties in handling complex program units, such as branching conditions and external dependencies. Recent work has increasingly utilized large language models (LLMs) to generate test cases, improving the quality of test generation by providing better cont…

Enhancing Document Retrieval in COVID-19 Research: Leveraging Large Language Models for Hidden Relation Extraction
Hoang-An Trieu, Dinh-Truong Do, Chau Nguyen, Vu Tran, Minh Le Nguyen
https://arxiv.org/abs/2506.18311

Enhancing Document Retrieval in COVID-19 Research: Leveraging Large Language Models for Hidden Relation Extraction
In recent years, with the appearance of the COVID-19 pandemic, numerous publications relevant to this disease have been issued. Because of the massive volume of publications, an efficient retrieval system is necessary to provide researchers with useful information if an unexpected pandemic happens so suddenly, like COVID-19. In this work, we present a method to help the retrieval system, the Covrelex-SE system, to provide more high-quality search results. We exploited the power of the large lan…

A High Resolution Search for Dual AGNs in Mergers: Pushing the Frontier with Keck AO
Camilo Vazquez, S. Satyapal, G. Canalizo, N. J. Secrest, R. W. Pfeifle, T. Bohn, K. Nyland, A. Aravindan, L. Blecha, J. M. Cann, S. Doan, E. K. Hicks, P. Kurczynski, S. Juneau, M. Malkan, M. McDonald, J. McKaig, P. Nair, B. Rothberg, E. Schwartzman, F. Muller-Sanchez, R. Sexton, V. U

A High Resolution Search for Dual AGNs in Mergers: Pushing the Frontier with Keck AO
Accreting supermassive black holes (SMBHs) in galaxy mergers with separations $<$ 1kpc are crucial to our understanding of SMBH growth, galaxy evolution, and the evolution of SMBH binaries. Despite their importance, there are less than a handful known, and most have been discovered serendipitously. In this work, we employ a new selection method to systematically pre-select candidate advanced mergers likely to contain unresolved substructure at sub-arcsecond scales. By exploiting the large surve…

Recommender systems, stigmergy, and the tyranny of popularity
Zackary Okun Dunivin, Paul E. Smaldino
https://arxiv.org/abs/2506.06162 https://

Recommender systems, stigmergy, and the tyranny of popularity
Scientific recommender systems, such as Google Scholar and Web of Science, are essential tools for discovery. Search algorithms that power work through stigmergy, a collective intelligence mechanism that surfaces useful paths through repeated engagement. While generally effective, this ``rich-get-richer'' dynamic results in a small number of high-profile papers that dominate visibility. This essay argues argue that these algorithm over-reliance on popularity fosters intellectual homogeneity and…

Efficient Visual Appearance Optimization by Learning from Prior Preferences
Zhipeng Li, Yi-Chi Liao, Christian Holz
https://arxiv.org/abs/2507.15355 https:…

Efficient Visual Appearance Optimization by Learning from Prior Preferences
Adjusting visual parameters such as brightness and contrast is common in our everyday experiences. Finding the optimal parameter setting is challenging due to the large search space and the lack of an explicit objective function, leaving users to rely solely on their implicit preferences. Prior work has explored Preferential Bayesian Optimization (PBO) to address this challenge, involving users to iteratively select preferred designs from candidate sets. However, PBO often requires many rounds …

Task and Motion Planning for Humanoid Loco-manipulation
Michal Ciebielski, Victor Dh\'edin, Majid Khadiv
https://arxiv.org/abs/2508.14099 https://arxiv…

Task and Motion Planning for Humanoid Loco-manipulation
This work presents an optimization-based task and motion planning (TAMP) framework that unifies planning for locomotion and manipulation through a shared representation of contact modes. We define symbolic actions as contact mode changes, grounding high-level planning in low-level motion. This enables a unified search that spans task, contact, and motion planning while incorporating whole-body dynamics, as well as all constraints between the robot, the manipulated object, and the environment. R…

The government would *never* misuse their vast and terrifying domestic spying capabilities for evil. The people who *work* for the government, on the other hand....
https://www.404media.co/a-texas-cop-searched-license-plate-cameras-…

A Texas Cop Searched License Plate Cameras Nationwide for a Woman Who Got an Abortion
The sheriff said the woman self-administered the abortion and her family were concerned for her safety, so authorities searched through Flock cameras. Experts are still concerned that a cop in a state where abortion is illegal can search cameras in others where it's a human right.

Expanding the search space of high entropy oxides and predicting synthesizability using machine learning interatomic potentials
Oliver A. Dicks, Solveig S. Aamlid, Alannah M. Hallas, Joerg Rottler
https://arxiv.org/abs/2508.13389

Expanding the search space of high entropy oxides and predicting synthesizability using machine learning interatomic potentials
We propose an efficient computational methodology for predicting the synthesizability of high entropy oxides (HEOs) in a large space of possible candidate compounds. HEOs are a growing field with an enormous potential chemical composition space, and yet the discovery of new HEOs is slow and driven by experimental trial-and-error. In this work, we attempt to speed up this process by using a machine learned interatomic potential offering DFT-level accuracy. Our methodology starts by identifying a…

Quantum Search for Gravitational Wave of Massive Black Hole Binaries
Fangzhou Guo, Jibo He
https://arxiv.org/abs/2505.24459 https://a…

Quantum Search for Gravitational Wave of Massive Black Hole Binaries
Matched filtering is a common method for detecting gravitational waves. However, the computational costs of searching large template banks limit the efficiency of classical algorithms when searching for massive black hole binary (MBHB) systems. In this work, a quantum matched filtering algorithm based on Grover's algorithm is applied to the MBHB signals. It is demonstrated that the quantum approach can reduce the computational complexity from $O(N)$ to $O(\sqrt{N})$ theoretically, where $N$ is …

Series A, Episode 03 - Cygnus Alpha
GAN: As long as the door doesn't break.
VILA: Did you see? They killed Arco.
BLAKE: I don't understand. There's no response from the ship.
VILA: Perhaps these bracelets don't work any more.
https://blake.torpidity.net/m/103/543

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Optimizing Districting Plans to Maximize Majority-Minority Districts via IPs and Local Search
Daniel Brous, David Shmoys
https://arxiv.org/abs/2508.07446 https://

Optimizing Districting Plans to Maximize Majority-Minority Districts via IPs and Local Search
In redistricting litigation, effective enforcement of the Voting Rights Act has often involved providing the court with districting plans that display a larger number of majority-minority districts than the current proposal (as was true, for example, in what followed Allen v. Milligan concerning the congressional districting plan for Alabama in 2023). Recent work by Cannon et al. proposed a heuristic algorithm for generating plans to optimize majority-minority districts, which they called short…

Department of Homeland Security (DHS) Secretary Kristi Noem, whose department oversees FEMA’s work,
issued a new agency rule this year requiring all contracts and grants costing over $100,000 to be personally approved by her.
As floodwaters were rising in Texas, Noem failed to respond to such requests over the weekend,
taking four days to approve the spending that could have saved lives.
As of Wednesday evening, 120 people in Texas have been killed by the massive flo…

DHS Head Kristi Noem Prioritized Instagram Pics Over FEMA Requests for Response to Texas Floods
It took Noem four days to respond to requests from FEMA, delaying access to some search and rescue tools.

PLA: Prompt Learning Attack against Text-to-Image Generative Models
Xinqi Lyu, Yihao Liu, Yanjie Li, Bin Xiao
https://arxiv.org/abs/2508.03696 https://arxi…

PLA: Prompt Learning Attack against Text-to-Image Generative Models
Text-to-Image (T2I) models have gained widespread adoption across various applications. Despite the success, the potential misuse of T2I models poses significant risks of generating Not-Safe-For-Work (NSFW) content. To investigate the vulnerability of T2I models, this paper delves into adversarial attacks to bypass the safety mechanisms under black-box settings. Most previous methods rely on word substitution to search adversarial prompts. Due to limited search space, this leads to suboptimal p…

Search for dynamical black hole captures with Gaussian mixture modelling
Leigh Smith, Shubhanshu Tiwari, Michael Ebersold, Yeong-Bok Bae, Gungwon Kang, Ik Siong Heng
https://arxiv.org/abs/2508.00481

Search for dynamical black hole captures with Gaussian mixture modelling
Gravitational waves (GWs) are expected to originate from black holes interacting dynamically in dense astrophysical environments. In such environments, given that the velocity and cross section between the interacting black holes is low, dynamical capture may occur. Such events merge on very short timescales with high eccentricities and are expected to be detectable in the LIGO-Virgo-KAGRA (LVK) sensitivity band. In this work, we present a dedicated search for dynamical black hole capture event…

Optimizing Start Locations in Ergodic Search for Disaster Response
Ananya Rao, Alyssa Hargis, David Wettergreen, Howie Choset
https://arxiv.org/abs/2507.02708

Optimizing Start Locations in Ergodic Search for Disaster Response
In disaster response scenarios, deploying robotic teams effectively is crucial for improving situational awareness and enhancing search and rescue operations. The use of robots in search and rescue has been studied but the question of where to start robot deployments has not been addressed. This work addresses the problem of optimally selecting starting locations for robots with heterogeneous capabilities by formulating a joint optimization problem. To determine start locations, this work adds …

All-sky search for individual Primordial Black Hole bursts with LHAASO
Cao, Aharonian, Bai, Bao, Bastieri, Bi, Bi, Bian, Bukevich, Cai, Cao, Cao, Chang, Chang, Chen, Chen, Chen, Chen, Chen, Chen, Chen, Chen, Chen, Chen, Chen, Chen, Chen, Chen, Chen, Chen, Cheng, Cheng, Chu, Cui, Cui, Cui, Cui, Dai, Dai, Dai, , Diao, Dong, Duan, Fan, Fan, Fang, Fang, Fang, Feng, Feng, Feng, Feng, Feng, Feng, Feng, Gabici, Gao, Gao, Gao, Gao, Gao, Ge, Ge, Geng, Giacinti, Gong, Gou, Gu, Guo, Guo, Guo, Guo…

All-sky search for individual Primordial Black Hole bursts with LHAASO
Primordial Black Holes~(PBHs) are hypothetical black holes with a wide range of masses that formed in the early universe. As a result, they may play an important cosmological role and provide a unique probe of the early universe. A PBH with an initial mass of approximately $10^{15}$~g is expected to explode today in a final burst of Hawking radiation. In this work, we conduct an all-sky search for individual PBH burst events using the data collected from March 2021 to July 2024 by the Water Che…

Experimental Evaluation of Static Image Sub-Region-Based Search Models Using CLIP
Bastian J\"ackl, Vojt\v{e}ch Kloda, Daniel A. Keim, Jakub Loko\v{c}
https://arxiv.org/abs/2506.06938

Experimental Evaluation of Static Image Sub-Region-Based Search Models Using CLIP
Advances in multimodal text-image models have enabled effective text-based querying in extensive image collections. While these models show convincing performance for everyday life scenes, querying in highly homogeneous, specialized domains remains challenging. The primary problem is that users can often provide only vague textual descriptions as they lack expert knowledge to discriminate between homogenous entities. This work investigates whether adding location-based prompts to complement the…

AI Guided Accelerator For Search Experience
Jayanth Yetukuri, Mehran Elyasi, Samarth Agrawal, Aritra Mandal, Rui Kong, Harish Vempati, Ishita Khan
https://arxiv.org/abs/2508.05649

AI Guided Accelerator For Search Experience
Effective query reformulation is pivotal in narrowing the gap between a user's exploratory search behavior and the identification of relevant products in e-commerce environments. While traditional approaches predominantly model query rewrites as isolated pairs, they often fail to capture the sequential and transitional dynamics inherent in real-world user behavior. In this work, we propose a novel framework that explicitly models transitional queries--intermediate reformulations occurring durin…

Submillimeter galaxy overdensities around physically associated quasar pairs
Eileen Herwig, Fabrizio Arrigoni Battaia, Chian-Chou Chen, Aura Obreja, Marta Nowotka, Rhea-Silvia Remus, Hidenobu Yajima
https://arxiv.org/abs/2506.11193

Submillimeter galaxy overdensities around physically associated quasar pairs
A commonly employed method to detect protoclusters in the young universe is the search for overdensities of massive star forming galaxies, such as submillimeter galaxies (SMGs), around high-mass halos, including those hosting quasars. In this work, we study the Megaparsec environment surrounding nine physically associated quasar pairs between $z=2.45$ and $z=3.82$ with JCMT/SCUBA-2 observations at 450 $μ$m and 850 $μ$m covering a field of view of roughly 13.7 arcmin in diameter (or 32 Mpc$^2$…

Blind search for activity-sensitive lines in the near-infrared using HARPS and NIRPS observations of Proxima and Gl 581
Jo\~ao Gomes da Silva, Elisa Delgado-Mena, Nuno C. Santos, Telmo Monteiro, Pierre Larue, Alejandro Su\'arez Mascare\~no, Xavier Delfosse, Lucile Mignon, \'Etienne Artigau, Nicola Nari, Manuel Abreu, Jos\'e L. A. Aguiar, Khaled Al Moulla, Guillaume Allain, Romain Allart, Tomy Arial, Hugues Auger, Fr\'ed\'erique Baron, Susana C. C. Barros, Luc Bazine…

Blind search for activity-sensitive lines in the near-infrared using HARPS and NIRPS observations of Proxima and Gl 581
Stellar activity variability is one of the main obstacles to the detection of Earth-like planets using the RV method. The aim of this work is to measure the effect of activity in the spectra of M dwarfs and detect activity-sensitive lines in the NIR. We took advantage of the simultaneous observations of HARPS and the newly commissioned NIRPS spectrograph to carry out a blind search of the most activity-sensitive spectral lines in the NIR using NIRPS spectra and known activity indicators in the …

NLO Corrections to Dimuonium Production in Photon-Photon Collision
Qi-Ming Feng, Si-Mao Guo, Qi-Wei Hu, Cong-Feng Qiao, Qi-Ming Qiu, Yu-Jie Tian, Bai-Rong Zhang, Hao Zhang, Xuan-Heng Zhang, Bo-Ting Zhou
https://arxiv.org/abs/2508.14424

NLO Corrections to Dimuonium Production in Photon-Photon Collision
Dimuonium ($μ^+ μ^-$) is one of the pure QED bound systems of leptons, together with positronium and ditauonium. The former had been observed in experiment in 1951, while the search for dimuonium and ditauonium ($τ^+ τ^-$) are still in vain. The ditauonium is thought to be hard to measure due to its short life time, whereas the dimuonium is very likely to be observed in current running experiments. We calculate in this work the para and ortho dimuonium production in photon-photon collision …

Superconductivity in atom-intercalated quaternary hydrides under ambient pressure
Bo-Wen Yao, Zhenfeng Ouyang, Xiao-Qi Han, Chang-Jiang Wu, Peng-Jie Guo, Ze-Feng Gao, Zhong-Yi Lu
https://arxiv.org/abs/2508.10912

Superconductivity in atom-intercalated quaternary hydrides under ambient pressure
Hydrogen-rich materials are the most promising candidates for high-temperature conventional superconductors under ambient pressure. Multinary hydrides have abundant structural configurations and are more promising to find high-temperature superconductors at ambient pressure, but searching for multinary materials in complex phase space is a great challenge. In this work, we used our developed AI search engine (InvDesFlow) to perform extensive investigations regarding ambient stable superconducti…

Solving the Pod Repositioning Problem with Deep Reinforced Adaptive Large Neighborhood Search
Lin Xie, Hanyi Li
https://arxiv.org/abs/2506.02746 https://…

Solving the Pod Repositioning Problem with Deep Reinforced Adaptive Large Neighborhood Search
The Pod Repositioning Problem (PRP) in Robotic Mobile Fulfillment Systems (RMFS) involves selecting optimal storage locations for pods returning from pick stations. This work presents an improved solution method that integrates Adaptive Large Neighborhood Search (ALNS) with Deep Reinforcement Learning (DRL). A DRL agent dynamically selects destroy and repair operators and adjusts key parameters such as destruction degree and acceptance thresholds during the search. Specialized heuristics for bo…

A Differential Evolution Algorithm with Neighbor-hood Mutation for DOA Estimation
Bo Zhou, Kaijie Xu, Yinghui Quan, Mengdao Xing
https://arxiv.org/abs/2507.06020

A Differential Evolution Algorithm with Neighbor-hood Mutation for DOA Estimation
Two-dimensional (2D) Multiple Signal Classification algorithm is a powerful technique for high-resolution direction-of-arrival (DOA) estimation in array signal processing. However, the exhaustive search over the 2D an-gular domain leads to high computa-tional cost, limiting its applicability in real-time scenarios. In this work, we reformulate the peak-finding process as a multimodal optimization prob-lem, and propose a Differential Evolu-tion algorithm with Neighborhood Mutation (DE-NM) to eff…

Bridging the Gap: From Ad-hoc to Proactive Search in Conversations
Chuan Meng, Francesco Tonolini, Fengran Mo, Nikolaos Aletras, Emine Yilmaz, Gabriella Kazai
https://arxiv.org/abs/2506.00983

Bridging the Gap: From Ad-hoc to Proactive Search in Conversations
Proactive search in conversations (PSC) aims to reduce user effort in formulating explicit queries by proactively retrieving useful relevant information given conversational context. Previous work in PSC either directly uses this context as input to off-the-shelf ad-hoc retrievers or further fine-tunes them on PSC data. However, ad-hoc retrievers are pre-trained on short and concise queries, while the PSC input is longer and noisier. This input mismatch between ad-hoc search and PSC limits retr…

A Systematic Search for Spectral Hardening in Blazar Flares with the Fermi-Large Area Telescope
Adithiya Dinesh (UC Madrid,IPARCOS), Alberto Dominguez (UC Madrid,IPARCOS), V. Paliya, J. L. Contreras, S. Buson, M. Ajello
https://arxiv.org/abs/2507.02718

A Systematic Search for Spectral Hardening in Blazar Flares with the Fermi-Large Area Telescope
Blazars are a subclass of active galactic nuclei (AGN) that emit non-thermal radiation through relativistic jets, characterized by rapid flux and polarization variability. Extreme high synchrotron-peaked blazars (EHSPs), with synchrotron peaks exceeding 10$^{17}$ Hz, are essential for understanding the full range of blazar phenomena and testing jet physics models. However, the number of known extreme blazars is small, so this class of objects remains poorly studied. This work aims to systematic…

On the spatiotemporal coincidence of meteorites in recent fall search campaigns
P. Gr\`ebol-Tom\`as, E. Pe\~na-Asensio, J. M. Trigo-Rodr\'iguez, J. Ib\'a\~nez-Insa
https://arxiv.org/abs/2508.03572

On the spatiotemporal coincidence of meteorites in recent fall search campaigns
The meteoritical community widely assumes that the probability of finding two meteorites from different falls laying in close proximity is negligible. However, recent studies have suggested that spatiotemporal coincidences may be critical when associating a meteorite with a witnessed fall. In this work, we estimate the number of accumulated meteorites--those resulting from past falls--that are present in landing regions of new falls, while accounting for the effects of terrestrial weathering. W…

Series D, Episode 02 - Power
TARRANT: Why?
AVON: Because that was my instruction.
DAYNA: You told Orac not to crack the code?
TARRANT: Why do that?
https://blake.torpidity.net/m/402/505 B7B6

Blakes7Bot | Search
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A systematic search for AGN obscuration variability in the Chandra archive
Isaiah S. Cox, N\'uria Torres-Alb\`a, Stefano Marchesi, Vittoria E. Gianolli, Xiurui Zhao, Marco Ajello, Indrani Pal, Ross Silver
https://arxiv.org/abs/2506.04457

A systematic search for AGN obscuration variability in the Chandra archive
The nature of the obscuring material in active galactic nuclei (AGN) can be studied by measuring changes in the line-of-sight column density, $N_{\rm H,los}$, over time. This can be accomplished by monitoring AGN over long periods of time and at all timescales. However, this can only be done for a few selected objects as it is resource intensive. Therefore, the best option currently is to focus on population statistics based on the available archival data. In this work, we estimate a lower limi…

Reexamining the search for light ALPs at flavor and forward accelerator experiments
Tong Li, Michael A. Schmidt, Man Yuan
https://arxiv.org/abs/2506.08342 …

Reexamining the search for light ALPs at flavor and forward accelerator experiments
The axion-like particle (ALP) is a well-motivated extension of the Standard Model. In this work, we revisit the sensitivity of forward accelerator experiments to light long-lived ALPs, and analyze flavor constraints. Our analysis incorporates recent measurements of the rare decays $B\to K + X$ and $K\to π+X$, which place stringent bounds on quark flavor violation of a light ALP. We consider the complete list of hadronic modes in the calculation of the ALP decay rate and exclusive production ch…

This https://arxiv.org/abs/2505.15998 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csAI_…

Exploring Flow-Lenia Universes with a Curiosity-driven AI Scientist: Discovering Diverse Ecosystem Dynamics
We present a method for the automated discovery of system-level dynamics in Flow-Lenia$-$a continuous cellular automaton (CA) with mass conservation and parameter localization$-$using a curiosity-driven AI scientist. This method aims to uncover processes leading to self-organization of evolutionary and ecosystemic dynamics in CAs. We build on previous work which uses diversity search algorithms in Lenia to find self-organized individual patterns, and extend it to large environments that support…

Measurement of Beam-Recoil Observables $C_x$ and $C_z$ for $K^ \Lambda$ Photoproduction
CLAS Collaboration, S. Adhikari, B. A. Raue, D. S. Carman, L. Guo, T. Chetry, P. Achenbach, J. S. Alvarado, M. J. Amaryan, W. R. Armstrong, H. Atac, H. Avakian, L. Baashen, N. A. Baltzell, L. Barion, M. Bashkanov, M. Battaglieri, F. Benmokhtar, A. Bianconi, A. S. Biselli, S. Boiarinov, M. Bondi, F. Bossu, K. -Th. Brinkmann, W. J. Briscoe, W. K. Brooks, S. Bueltmann, V. D. Burkert, T. Cao, R. Capobia…

Measurement of Beam-Recoil Observables $C_x$ and $C_z$ for $K^+Λ$ Photoproduction
Exclusive photoproduction of $K^+ Λ$ final states off a proton target has been an important component in the search for missing nucleon resonances and our understanding of the production of final states containing strange quarks. Polarization observables have been instrumental in this effort. The current work is an extension of previously published CLAS results on the beam-recoil transferred polarization observables $C_x$ and $C_z$. We extend the kinematic range up to invariant mass $W=3.33$~G…

Intent-Aware Neural Query Reformulation for Behavior-Aligned Product Search
Jayanth Yetukuri, Ishita Khan
https://arxiv.org/abs/2507.22213 https://arxiv.or…

Intent-Aware Neural Query Reformulation for Behavior-Aligned Product Search
Understanding and modeling buyer intent is a foundational challenge in optimizing search query reformulation within the dynamic landscape of e-commerce search systems. This work introduces a robust data pipeline designed to mine and analyze large-scale buyer query logs, with a focus on extracting fine-grained intent signals from both explicit interactions and implicit behavioral cues. Leveraging advanced sequence mining techniques and supervised learning models, the pipeline systematically capt…

Series D, Episode 02 - Power
TARRANT: Why?
AVON: Because that was my instruction.
DAYNA: You told Orac not to crack the code?
TARRANT: Why do that?
https://blake.torpidity.net/m/402/505 B7B6

Blakes7Bot | Search
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This https://arxiv.org/abs/2505.24586 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_…

All-sky search for individual Primordial Black Hole bursts with LHAASO
Primordial Black Holes~(PBHs) are hypothetical black holes with a wide range of masses that formed in the early universe. As a result, they may play an important cosmological role and provide a unique probe of the early universe. A PBH with an initial mass of approximately $10^{15}$~g is expected to explode today in a final burst of Hawking radiation. In this work, we conduct an all-sky search for individual PBH burst events using the data collected from March 2021 to July 2024 by the Water Che…

Automatically discovering heuristics in a complex SAT solver with large language models
Yiwen Sun, Furong Ye, Zhihan Chen, Ke Wei, Shaowei Cai
https://arxiv.org/abs/2507.22876 h…

Automatically discovering heuristics in a complex SAT solver with large language models
Satisfiability problem (SAT) is a cornerstone of computational complexity with broad industrial applications, and it remains challenging to optimize modern SAT solvers in real-world settings due to their intricate architectures. While automatic configuration frameworks have been developed, they rely on manually constrained search spaces and yield limited performance gains. This work introduces a novel paradigm which effectively optimizes complex SAT solvers via Large Language Models (LLMs), and…

Fast Estimation of Globally Optimal Independent Contact Regions for Robust Grasping and Manipulation
Jonathan P. King, Harnoor Ahluwalia, Michael Zhang, Nancy S. Pollard
https://arxiv.org/abs/2506.08856

Fast Estimation of Globally Optimal Independent Contact Regions for Robust Grasping and Manipulation
This work presents a fast anytime algorithm for computing globally optimal independent contact regions (ICRs). ICRs are regions such that one contact within each region enables a valid grasp. Locations of ICRs can provide guidance for grasp and manipulation planning, learning, and policy transfer. However, ICRs for modern applications have been little explored, in part due to the expense of computing them, as they have a search space exponential in the number of contacts. We present a divide an…

Situationally-aware Path Planning Exploiting 3D Scene Graphs
Saad Ejaz, Marco Giberna, Muhammad Shaheer, Jose Andres Millan-Romera, Ali Tourani, Paul Kremer, Holger Voos, Jose Luis Sanchez-Lopez
https://arxiv.org/abs/2508.06283

Situationally-aware Path Planning Exploiting 3D Scene Graphs
3D Scene Graphs integrate both metric and semantic information, yet their structure remains underutilized for improving path planning efficiency and interpretability. In this work, we present S-Path, a situationally-aware path planner that leverages the metric-semantic structure of indoor 3D Scene Graphs to significantly enhance planning efficiency. S-Path follows a two-stage process: it first performs a search over a semantic graph derived from the scene graph to yield a human-understandable h…

This https://arxiv.org/abs/2505.04209 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csIR_…

To Judge or not to Judge: Using LLM Judgements for Advertiser Keyphrase Relevance at eBay
E-commerce sellers are recommended keyphrases based on their inventory on which they advertise to increase buyer engagement (clicks/sales). The relevance of advertiser keyphrases plays an important role in preventing the inundation of search systems with numerous irrelevant items that compete for attention in auctions, in addition to maintaining a healthy seller perception. In this work, we describe the shortcomings of training Advertiser keyphrase relevance filter models on click/sales/search …

Incorporating Stochastic Models of Controller Behavior into Kinodynamic Efficiently Adaptive State Lattices for Mobile Robot Motion Planning in Off-Road Environments
Eric R. Damm, Eli S. Lancaster, Felix A. Sanchez, Kiana Bronder, Jason M. Gregory, Thomas M. Howard
https://arxiv.org/abs/2508.04384 …

Incorporating Stochastic Models of Controller Behavior into Kinodynamic Efficiently Adaptive State Lattices for Mobile Robot Motion Planning in Off-Road Environments
Mobile robot motion planners rely on theoretical models to predict how the robot will move through the world. However, when deployed on a physical robot, these models are subject to errors due to real-world physics and uncertainty in how the lower-level controller follows the planned trajectory. In this work, we address this problem by presenting three methods of incorporating stochastic controller behavior into the recombinant search space of the Kinodynamic Efficiently Adaptive State Lattice …