Tootfinder

Does the Spotlight dictionary search (cmd space d i c tab) in macOS 26 actually work? Words that *are* in the Dictionary app are shown as "No results found".

Parallel/Distributed Tabu Search for Scheduling Microprocessor Tasks in Hybrid Flowshop
Adam Janiak, Damian Kowalczyk, Maciej Lichtenstein
https://arxiv.org/abs/2509.11396 https…

Parallel/Distributed Tabu Search for Scheduling Microprocessor Tasks in Hybrid Flowshop
The paper deals with the makespan minimization in the hybrid flow shop scheduling problem with multiprocessor tasks. The hybrid flow shop (HFS) generalizes the classical flow shop processor configuration by replacing each processor (processing stage) by some number of identical parallel processors. Similarly, the multiprocessor tasks generalize the classical assumption, by allowing a task to require more than one processor simultaneously for its processing. In this work we present the algorithm…

DOSA: Differentiable Model-Based One-Loop Search for DNN Accelerators
Charles Hong, Qijing Huang, Grace Dinh, Mahesh Subedar, Yakun Sophia Shao
https://arxiv.org/abs/2509.10702 …

DOSA: Differentiable Model-Based One-Loop Search for DNN Accelerators
In the hardware design space exploration process, it is critical to optimize both hardware parameters and algorithm-to-hardware mappings. Previous work has largely approached this simultaneous optimization problem by separately exploring the hardware design space and the mapspace - both individually large and highly nonconvex spaces - independently. The resulting combinatorial explosion has created significant difficulties for optimizers. In this paper, we introduce DOSA, which consists of di…

Search for the $D^{*}\bar{D}^{*}$ Molecular State $X_{2}(4013)$ in $K^{-}p$ and $pp$ Collisions
Min Yuan, Yin Huang
https://arxiv.org/abs/2510.12292 https://

Search for the $D^{*}\bar{D}^{*}$ Molecular State $X_{2}(4013)$ in $K^{-}p$ and $pp$ Collisions
Motivated by the interpretation of $X(3872)$ as a $D\bar{D}^{*}$ molecular state, heavy-quark spin symmetry predicts a spin-2 partner, $X_{2}(4013)$, which can be regarded as a $D^{*}\bar{D}^{*}$ molecule with quantum numbers $J^{PC} = 2^{++}$. Its experimental confirmation, however, remains elusive. In this work, we investigate the production mechanisms of $X_{2}(4013)$ in the reactions $K^{-}p \to Λ_{c}^{+} D_{s}^{-} X_{2}(4013)$ and $pp \to Λ_{c}^{+}Λ_{c}^{+} X_{2}(4013)$ within an effect…

Currently sitting in a little park near the auto shop I've been going to for the better part of a decade. Which, definitely still a Protip: search out the best indie shop you can find in your area. Stay away from the chains. My credit card balance might be about to eat a fat bill (thank fuck I have the option even tho I hate it lol) but it's worth the money for the piece of mind knowing a real pro did the work.
Was an exciting short trip over here from home 😀 Basically 5mph un…

Two-Dimensional Na2LiAlP2 crystal for high-performance field-effect transistors
Run-Jie Peng, Xing-Yu Wang, Jun-Hui Yuan, Nian-Nian Yu, Kan-Hao Xue, Jiafu Wang, Pan Zhang
https://arxiv.org/abs/2510.12473

Two-Dimensional Na2LiAlP2 crystal for high-performance field-effect transistors
High-performance, low-power transistors are core components of advanced integrated circuits, and the ultimate limitation of Moore's law has made the search for new alternative pathways an urgent priority. Two-dimensional (2D) materials have become the most promising exploration target due to their exceptional electronic properties and scalability. In this work, we conducted device transport research on the previously proposed 2D quaternary semiconductor Na2LiAlP2 using the non-equilibrium Green…

Really important practical question: how to do type search for #Agda.
Unification Modulo Isomorphisms between Dependent Types for Type-based Library Search
Presented by Satoshi Takimoto. Joint work with Sosuke Moriguchi, Takuo Watanabe

During much of the 20th century, the town’s residents were forced to fan out across Europe in search of work, said Venancio Cuenca Lopéz, the head of a local retiree association.
“Some of them had papers, but some had no papers, no job offers, nothing,” he said
“We can’t say: ‘Well we did it, but now we’re against it.’ We’re all human beings, we need to have some empathy.”

FeNOMS: Enhancing Open Modification Spectral Library Search with In-Storage Processing on Ferroelectric NAND (FeNAND) Flash
Sumukh Pinge, Ashkan Moradifirouzabadi, Keming Fan, Prasanna Venkatesan Ravindran, Tanvir H. Pantha, Po-Kai Hsu, Zheyu Li, Weihong Xu, Zihan Xia, Flavio Ponzina, Winston Chern, Taeyoung Song, Priyankka Ravikumar, Mengkun Tian, Lance Fernandes, Huy Tran, Hari Jayasankar, Hang Chen, Chinsung Park, Amrit Garlapati, Kijoon Kim, Jongho Woo, Suhwan Lim, Kwangsoo Kim, Wa…

FeNOMS: Enhancing Open Modification Spectral Library Search with In-Storage Processing on Ferroelectric NAND (FeNAND) Flash
The rapid expansion of mass spectrometry (MS) data, now exceeding hundreds of terabytes, poses significant challenges for efficient, large-scale library search - a critical component for drug discovery. Traditional processors struggle to handle this data volume efficiently, making in-storage computing (ISP) a promising alternative. This work introduces an ISP architecture leveraging a 3D Ferroelectric NAND (FeNAND) structure, providing significantly higher density, faster speeds, and lower volt…

On the Speed-up of Wave-like Dark Matter Searches with Entangled Qubits
Arushi Bodas, Sohitri Ghosh, Roni Harnik
https://arxiv.org/abs/2510.11795 https://a…

On the Speed-up of Wave-like Dark Matter Searches with Entangled Qubits
Qubit-based sensing platforms offer promising new directions for wave-like dark matter searches. Recent proposals demonstrate that entangled qubits can achieve quadratic scaling of the signal in the number of qubits. In this work we expand on these proposals to analyze the bandwidth and scan rate performance of entangled qubit protocols across different error regimes. We find that the phase-based readout of entangled protocols preserves the search bandwidth independent of qubit number, in contr…

The Post-Electromagnetic Era: A Vision for Wireless Communication Beyond 6G
Shumaila Javaid, Nasir Saeed
https://arxiv.org/abs/2510.11097 https://arxiv.org…

The Post-Electromagnetic Era: A Vision for Wireless Communication Beyond 6G
Electromagnetic (EM) communication is nearing its physical and thermodynamic limits, where further performance gains through spectrum optimization alone have become increasingly unsustainable. Finite bandwidth, propagation loss at higher frequencies, and the inherent trade-offs between energy and information constrain the scalability of 6G and beyond systems. These limitations drive the search for alternative mechanisms for information transfer beyond conventional EM propagation. This work intr…

for all your solo robert hunter setlist & tape needs, douglas aldridge just updated/relaunched his long-dormant hunterbase. http://stillunsung.com

Robert Hunter Performance Archive
Comprehensive documentation of 600+ Robert Hunter performances spanning his complete musical career. Search setlists, venues, and recordings from the Grateful Dead lyricist's solo work and collaborations.

A Multi-Agent Framework for Stateful Inference-Time Search
Arshika Lalan, Rajat Ghosh, Aditya Kolsur, Debojyoti Dutta
https://arxiv.org/abs/2510.07147 https://

A Multi-Agent Framework for Stateful Inference-Time Search
Recent work explores agentic inference-time techniques to perform structured, multi-step reasoning. However, stateless inference often struggles on multi-step tasks due to the absence of persistent state. Moreover, task-specific fine-tuning or instruction-tuning often achieve surface-level code generation but remain brittle on tasks requiring deeper reasoning and long-horizon dependencies. To address these limitations, we propose stateful multi-agent evolutionary search, a training-free framewo…

First galaxy ultraviolet luminosity function limits on dark matter-proton scattering
Hovav Lazare, Ely D. Kovetz, Kimberly K. Boddy, Julian B. Munoz
https://arxiv.org/abs/2510.10757

First galaxy ultraviolet luminosity function limits on dark matter-proton scattering
Scattering between dark matter (DM) and protons leads to suppressed small-scale fluctuations, with implications for a variety of cosmological observables. In this work, we search for evidence of DM-proton scattering with an interaction cross section $σ\!=\!σ_0 (\frac{v}{c})^n$ for $n=0,2$ and $4$, corresponding e.g. to velocity-independent contact interactions from heavy mediators, velocity-dependent pseudoscalar-mediated scattering, and higher-order dipole interactions, respectively, using h…

Evidence of Physiological Co-Modulation During Human-Animal Interaction: A Systematic Review
G. Bargigli, L. Frassineti, A. Lanata', P. Baragli, C. Scopa, A. Vignoli
https://arxiv.org/abs/2510.10559

Evidence of Physiological Co-Modulation During Human-Animal Interaction: A Systematic Review
This review examines the evidence in the literature for physiological co-modulation during human-animal interaction. The aim of this work is to identify studies that assessed co-modulation via simultaneous measurement of physiological signals in both species, performing quantitative comparisons, and evaluate the consistency of the findings.\\ We searched PubMed, EM-BASE, Scopus, Google Scholar, Animal Studies Repository, and the ''Consensus app'' tool between June and August 2025 (last search: …

MANGOS II: Five new giant planets orbiting low-mass stars
G. Dransfield, M. Timmermans, D. Sebastian, B. V. Rackham, A. Burgasser, K. Barkaoui, A. H. M. J. Triaud, M. Gillon, J. M. Almenara, S. L. Casewell, K. A. Collins, A. Fukui, C. Jano-Munoz, S. Kanodia, N. Narita, E. Palle, M. G. Scott, A. Soubkiou, A. Stokholm, J. Audenaert, G. \'A. Bakos, Y. Beletsky, Z. L. de Beurs, Z. Benkhaldoun, A. Burdanov, R. P. Butler, D. Caldwell, J. D. Crane, Y. T. Davis, B. O. Demory, E. Ducrot, Y.…

MANGOS II: Five new giant planets orbiting low-mass stars
Giant planets orbiting low-mass stars on short orbits present a conundrum, as in the most extreme cases their existence cannot be reconciled with current models of core accretion. Therefore, surveys dedicated to finding these rare planets have a key role to play by growing the sample to overcome small number statistics. In this work we present MANGOS, a programme dedicated to the search for giant objects (planets, brown dwarfs, and low-mass stars) orbiting M dwarfs. We report on the discovery o…

Repository-Aware File Path Retrieval via Fine-Tuned LLMs
Vasudha Yanuganti, Ishaan Puri, Swapnil Chhatre, Mantinder Singh, Ashok Jallepalli, Hritvik Shrivastava, Pradeep Kumar Sharma
https://arxiv.org/abs/2510.08850

Repository-Aware File Path Retrieval via Fine-Tuned LLMs
Modern codebases make it hard for developers and AI coding assistants to find the right source files when answering questions like "How does this feature work?" or "Where was the bug introduced?" Traditional code search (keyword or IR based) often misses semantic context and cross file links, while large language models (LLMs) understand natural language but lack repository specific detail. We present a method for file path retrieval that fine tunes a strong LLM (Qwen3-8B) with QLoRA and Unslot…

Visualizing Multimodality in Combinatorial Search Landscapes
Xavier F. C. S\'anchez-D\'iaz, Ole Jakob Mengshoel
https://arxiv.org/abs/2510.06517 https://

Visualizing Multimodality in Combinatorial Search Landscapes
This work walks through different visualization techniques for combinatorial search landscapes, focusing on multimodality. We discuss different techniques from the landscape analysis literature, and how they can be combined to provide a more comprehensive view of the search landscape. We also include examples and discuss relevant work to show how others have used these techniques in practice, based on the geometric and aesthetic elements of the Grammar of Graphics. We conclude that there is no …

Learning-Based Hashing for ANN Search: Foundations and Early Advances
Sean Moran
https://arxiv.org/abs/2510.04127 https://arxiv.org/pdf/2510.04127

Learning-Based Hashing for ANN Search: Foundations and Early Advances
Approximate Nearest Neighbour (ANN) search is a fundamental problem in information retrieval, underpinning large-scale applications in computer vision, natural language processing, and cross-modal search. Hashing-based methods provide an efficient solution by mapping high-dimensional data into compact binary codes that enable fast similarity computations in Hamming space. Over the past two decades, a substantial body of work has explored learning to hash, where projection and quantisation funct…

Dark matter direct search result from InDEx run2 at JUSL
Susmita Das, Mala Das, Vimal Kumar, Suraj Ali, Nilanjan Biswas, Shantonu Sahoo, Niraj Chaddha
https://arxiv.org/abs/2510.06921

Dark matter direct search result from InDEx run2 at JUSL
The Indian Dark matter search Experiment (InDEx) has been initiated at Jaduguda Underground Science Laboratory (JUSL) to explore the low mass region of dark matter. The detectors used by InDEx are superheated droplet detectors with active liquid C2H2F4. The run1 of InDEx was with 2.47 kg-days of exposure at a threshold of 5.87 keV. In the present work, the run2 of InDEx, the detectors were set at 1.95 keV thresholds with an active liquid mass of 70.4 g. For a runtime of 102.48 days, the experim…

Imagine ChatGPT but instead of predicting text it just linked you to the to 3 documents most-influential on the probabilities that would have been used to predict that text.
Could even generate some info about which parts of each would have been combined how.
There would still be issues with how training data is sourced and filtered, but these could be solved by crawling normally respecting robots.txt and by paying filterers a fair wage with a more relaxed work schedule and mental health support.
The energy issues are mainly about wild future investment and wasteful query spam, not optimized present-day per-query usage.
Is this "just search?"
Yes, but it would have some advantages for a lot of use cases, mainly in synthesizing results across multiple documents and in leveraging a language model more fully to find relevant stuff.
When we talk about the harms of current corporate LLMs, the opportunity cost of NOT building things like this is part of that.
The equivalent for art would have been so amazing too! "Here are some artists that can do what you want, with examples pulled from their portfolios."
It would be a really cool coding assistant that I'd actually encourage my students to use (with some guidelines).
#AI #GenAI #LLMs

CoLLM-NAS: Collaborative Large Language Models for Efficient Knowledge-Guided Neural Architecture Search
Zhe Li, Zhiwei Lin, Yongtao Wang
https://arxiv.org/abs/2509.26037 https:…

CoLLM-NAS: Collaborative Large Language Models for Efficient Knowledge-Guided Neural Architecture Search
The integration of Large Language Models (LLMs) with Neural Architecture Search (NAS) has introduced new possibilities for automating the design of neural architectures. However, most existing methods face critical limitations, including architectural invalidity, computational inefficiency, and inferior performance compared to traditional NAS. In this work, we present Collaborative LLM-based NAS (CoLLM-NAS), a two-stage NAS framework with knowledge-guided search driven by two complementary LLMs…

Dynamic Automated Deduction by Contradiction Separation: The Standard Extension Algorithm
Yang Xu, Xingxing He, Shuwei Chen, Jun Liu, Xiaomei Zhong
https://arxiv.org/abs/2510.08468

Dynamic Automated Deduction by Contradiction Separation: The Standard Extension Algorithm
Automated deduction seeks to enable machines to reason with mathematical precision and logical completeness. Classical resolution-based systems, such as Prover9, E, and Vampire, rely on binary inference, which inherently limits multi-clause synergy during proof search. The Contradiction Separation Extension (CSE) framework, introduced by Xu et al. (2018), overcame this theoretical limitation by extending deduction beyond binary inference. However, the original work did not specify how contradic…

It’s time to learn how water leak sensors work and search for one that’s compatible with home assistant or has some sort of API.
This is ruining my previous plan, where I deluded myself into thinking that I could have the patience to figure out how to write a driver for a mouse dongle

BloomIntent: Automating Search Evaluation with LLM-Generated Fine-Grained User Intents
Yoonseo Choi, Eunhye Kim, Hyunwoo Kim, Donghyun Park, Honggu Lee, Jinyoung Kim, Juho Kim
https://arxiv.org/abs/2509.18641

BloomIntent: Automating Search Evaluation with LLM-Generated Fine-Grained User Intents
If 100 people issue the same search query, they may have 100 different goals. While existing work on user-centric AI evaluation highlights the importance of aligning systems with fine-grained user intents, current search evaluation methods struggle to represent and assess this diversity. We introduce BloomIntent, a user-centric search evaluation method that uses user intents as the evaluation unit. BloomIntent first generates a set of plausible, fine-grained search intents grounded on taxonomie…

Search for dark matter around intermediate mass black holes with the H.E.S.S. experiment
Jann Aschersleben (for the H.E.S.S. Collaboration), Dieter Horns (for the H.E.S.S. Collaboration), Emmanuel Moulin (for the H.E.S.S. Collaboration), Manuela Vecchi (for the H.E.S.S. Collaboration)
https://arxiv.org/abs/2510.03023

Search for dark matter around intermediate mass black holes with the H.E.S.S. experiment
Intermediate mass black holes (IMBHs), with masses ranging from a hundred and a million solar masses, are hypothesised to be surrounded by dense regions of dark matter known as dark matter spikes, where the annihilation of dark matter particles could produce detectable gamma rays. The detection of dark matter annihilation around IMBHs therefore offers a promising approach for probing the nature of dark matter. In this work, we search for dark matter annihilation around IMBHs using data from the…

OpenAI launches a "company knowledge" ChatGPT update to let Business, Enterprise, and Education users search for data in connected apps like Slack and GitHub (Jess Weatherbed/The Verge)
https://www.theverge.com/news/806046/openai-chatgpt-company-knowled…

OpenAI made ChatGPT better at sifting through your work or school information
OpenAI has launched a new ChatGPT feature that makes it easier to search for workspace information without switching between apps.

Which Programming Language and Model Work Best With LLM-as-a-Judge For Code Retrieval?
Lucas Roberts, Denisa Roberts
https://arxiv.org/abs/2510.00324 https://

Which Programming Language and Model Work Best With LLM-as-a-Judge For Code Retrieval?
Code search is an important information retrieval application. Benefits of better code search include faster new developer on-boarding, reduced software maintenance, and ease of understanding for large repositories. Despite improvements in search algorithms and search benchmarks, the domain of code search has lagged behind. One reason is the high cost of human annotation for code queries and answers. While humans may annotate search results in general text QA systems, code annotations require s…

My latest rabbit hole has been "LLM Routers"
Read and tried all the LLM Router code I could find. None of them were what I was looking for.
So I asked Claude to write what I wanted in Python. Simple and elegant. Based on a keyword search of the prompt, the prompt is sent to the proper model running in ollama. Seems to work.
#Claude #VibeCoding #Ollama #AI #LLM

SwiReasoning: Switch-Thinking in Latent and Explicit for Pareto-Superior Reasoning LLMs
Dachuan Shi, Abedelkadir Asi, Keying Li, Xiangchi Yuan, Leyan Pan, Wenke Lee, Wen Xiao
https://arxiv.org/abs/2510.05069

SwiReasoning: Switch-Thinking in Latent and Explicit for Pareto-Superior Reasoning LLMs
Recent work shows that, beyond discrete reasoning through explicit chain-of-thought steps, which are limited by the boundaries of natural languages, large language models (LLMs) can also reason continuously in latent space, allowing richer information per step and thereby improving token efficiency. Despite this promise, latent reasoning still faces two challenges, especially in training-free settings: 1) purely latent reasoning broadens the search distribution by maintaining multiple implicit …

Is it actually possible to delete files from a git repository without breaking existing forks etc?
There's a load of large generated and audio in @…'s git history. Trying to wipe them from history seems super risky though..

Less is More: Faster Maximum Clique Search by Work-Avoidance
Hans Vandierendonck
https://arxiv.org/abs/2509.22245 https://arxiv.org/pdf/2509.22245

Less is More: Faster Maximum Clique Search by Work-Avoidance
The maximum clique (MC) problem is a challenging graph mining problem which, due to its NP-hard nature, can take a substantial amount of execution time. The MC problem is dominated by set intersection operations similar to Maximal Clique Enumeration, however it differs in requiring to find only a clique of maximum size. As such, key to the problem is to demonstrate efficiently that a particular part of the search space does not contain a maximum clique, allowing to skip over major parts of the …

You would think Google Drive app would have basic search that finds all document titles containing search words. You would be wrong. Actually Apple Files/iCloud search is much better. The more I work with Google apps, the more mediocre they seem. The main thing that stops me from getting folks to use iCloud web apps is the unnecessary 2 modal dialogs to open every doc.

A $1000\times$ Faster LLM-enhanced Algorithm For Path Planning in Large-scale Grid Maps
Junlin Zeng, Xin Zhang, Xiang Zhao, Yan Pan
https://arxiv.org/abs/2510.02716 https://

A $1000\times$ Faster LLM-enhanced Algorithm For Path Planning in Large-scale Grid Maps
Path planning in grid maps, arising from various applications, has garnered significant attention. Existing methods, such as A*, Dijkstra, and their variants, work well for small-scale maps but fail to address large-scale ones due to high search time and memory consumption. Recently, Large Language Models (LLMs) have shown remarkable performance in path planning but still suffer from spatial illusion and poor planning performance. Among all the works, LLM-A* \cite{meng2024llm} leverages LLM to …

Conflict-Based Search as a Protocol: A Multi-Agent Motion Planning Protocol for Heterogeneous Agents, Solvers, and Independent Tasks
Rishi Veerapaneni, Alvin Tang, Haodong He, Sophia Zhao, Viraj Shah, Yidai Cen, Ziteng Ji, Gabriel Olin, Jon Arrizabalaga, Yorai Shaoul, Jiaoyang Li, Maxim Likhachev
https://arxiv.org/abs/2510.00425

Conflict-Based Search as a Protocol: A Multi-Agent Motion Planning Protocol for Heterogeneous Agents, Solvers, and Independent Tasks
Imagine the future construction site, hospital, office, or even sophisticated household with dozens of robots bought from different manufacturers. How can we enable these different systems to effectively move in a shared environment, given that each robot may have its own independent motion planning system? This work shows how we can get efficient collision-free movements between algorithmically heterogeneous agents by using Conflict-Based Search (Sharon et al. 2015) as a protocol. At its core,…

@… I haven’t convinced my employer to pay yet, but I added my personal Kagi account as the default search engine on my work laptop as well.
Finding SIGNIFICANTLY more useful results for programming problems that come up during the day than I did before.

I had to make a cucoloris at work today but we've got laser cutters and cardboard so it was quick and easy.
(Also, I did an image search for "cucoloris design" and found my own blog post from 2011. Argh...)

A sterile-neutrino search using data from the MicroBooNE liquid-argon time projection chamber performed in an undergraduate teaching laboratory
John Waiton, Joseph Bateman, Justin J Evans, Ole Gunnar Finnerud, Elena Gramellini, Roxanne Guenette, Pawel Guzowski, Alekander Kedziora, Stefan Soldner-Rembold
https://arxiv.org/abs/2509.18859

Day 26: Emily Short
If you know who Short is, you know exactly why she's on this list. If you don't, you're probably in the majority. She's an absolutely legendary author within the interactive fiction (IF) community, which gets somewhat pigeonholed by stuff like Zork when there's actually a huge range of stuff in the medium some of which isn't even puzzle-focused, and Short has been writing & coding on the bleeding edge of things for decades.
I was lucky enough to be introduced to Short's work in graduate school, where we played "Galatea" as part of an interactive fiction class. Short uses a lot of clever parser tricks to make your conversation with a statue feel very fluid and conversational, giving to contemporary audiences a great example of how vibrant interaction with a well-designed agent can be in contrast to an LLM, if you're willing to put in some work on bespoke parsing & responses (although the user does need to know basic IF conventions). While I didn't explore the full range of Galatea's many possible outcomes, it left a strong impression on me as a vision for what IF could be besides dorky puzzles, and I think that "visionary" is a great term to describe Short.
If you'd like you get a feel for her (very early) work, you can play Galatea here: #30AuthorsNoMen

Guiding Evolution of Artificial Life Using Vision-Language Models
Nikhil Baid, Hannah Erlebach, Paul Hellegouarch, Frederico Wieser
https://arxiv.org/abs/2509.22447 https://

Guiding Evolution of Artificial Life Using Vision-Language Models
Foundation models (FMs) have recently opened up new frontiers in the field of artificial life (ALife) by providing powerful tools to automate search through ALife simulations. Previous work aligns ALife simulations with natural language target prompts using vision-language models (VLMs). We build on Automated Search for Artificial Life (ASAL) by introducing ASAL++, a method for open-ended-like search guided by multimodal FMs. We use a second FM to propose new evolutionary targets based on a sim…

It’s time to learn how water leak sensors work and search for one that’s compatible with home assistant or has some sort of API.
This is ruining my previous plan, where I deluded myself into thinking that I could have the patience to figure out how to write a driver for a mouse dongle

A Comparison of Low and high-Order Methods for the Simulation of Supersonic Jet Flows
D. F. Abreu, C. Junqueira-Junior, E. T. V. Dauricio, J. L. F. Azevedo
https://arxiv.org/abs/2509.17725

A Comparison of Low and high-Order Methods for the Simulation of Supersonic Jet Flows
The present work compares results for different numerical methods in search of alternatives to improve the quality of large-eddy simulations for the problem of supersonic turbulent jet flows. Previous work has analyzed supersonic jet flows using a second-order, finite difference solver based on structured meshes, and the results indicated a shorter potential core of the jet and different levels of velocity fluctuations. In the present work, the results of previous simulations are compared to ne…

Agentic AI meets Neural Architecture Search: Proactive Traffic Prediction for AI-RAN
Abdelaziz Salama, Mohammed M. H. Qazzaz, Zeinab Nezami, Maryam Hafeez, Syed Ali Raza Zaidi
https://arxiv.org/abs/2510.00851

Agentic AI meets Neural Architecture Search: Proactive Traffic Prediction for AI-RAN
Next-generation wireless networks require intelligent traffic prediction to enable autonomous resource management and handle diverse, dynamic service demands. The Open Radio Access Network (O-RAN) framework provides a promising foundation for embedding machine learning intelligence through its disaggregated architecture and programmable interfaces. This work applies a Neural Architecture Search (NAS)-based framework that dynamically selects and orchestrates efficient Long Short-Term Memory (LST…

My answer is NO to AI in a browser. All I want is for a browser to go to the URL and render the page. A search site to provide me a list of sites that meet my query, not a hallucination of a list. The page that is edited by a person presenting real information and not AI slop.
And yes, I do use AI at times at work. I use it to quickly find documents, but I will do the review to see if they are relevant.

I'm curious - what San Francisco media has covered this? Admittedly something I have not been looking for. But a quick search doesn't find many news articles - but it appears to be a nationwide problem. Sure, FDA has published their alert (2022) but that's not a great tool to reach people who need to know about risks.
The FDA has warned against this ‘natural remedy’ for joint pain. San Francisco immigrants still trust it

I'm curious - what San Francisco media has covered this? Admittedly something I have not been looking for. But a quick search doesn't find many news articles - but it appears to be a nationwide problem. Sure, FDA has published their alert (2022) but that's not a great tool to reach people who need to know about risks.
The FDA has warned against this ‘natural remedy’ for joint pain. San Francisco immigrants still trust it

Fast OTSU Thresholding Using Bisection Method
Sai Varun Kodathala
https://arxiv.org/abs/2509.16179 https://arxiv.org/pdf/2509.16179

Fast OTSU Thresholding Using Bisection Method
The Otsu thresholding algorithm represents a fundamental technique in image segmentation, yet its computational efficiency is severely limited by exhaustive search requirements across all possible threshold values. This work presents an optimized implementation that leverages the bisection method to exploit the unimodal characteristics of the between-class variance function. Our approach reduces the computational complexity from O(L) to O(log L) evaluations while preserving segmentation accurac…

Open Political Corpora: Structuring, Searching, and Analyzing Political Text Collections with PoliCorp
Nina Smirnova, Muhammad Ahsan Shahid, Philipp Mayr
https://arxiv.org/abs/2509.17465

Open Political Corpora: Structuring, Searching, and Analyzing Political Text Collections with PoliCorp
In this work, we present PoliCorp (https://demo-pollux.gesis.org/), a web portal designed to facilitate the search and analysis of political text corpora. PoliCorp provides researchers with access to rich textual data, enabling in-depth analysis of parliamentary discourse over time. The platform currently features a collection of transcripts from debates in the German parliament, spanning 76 years of proceedings. With the advanced search functionality, researchers can apply logical operations t…

GRACE: A Language Model Framework for Explainable Inverse Reinforcement Learning
Silvia Sapora, Devon Hjelm, Alexander Toshev, Omar Attia, Bogdan Mazoure
https://arxiv.org/abs/2510.02180

GRACE: A Language Model Framework for Explainable Inverse Reinforcement Learning
Inverse Reinforcement Learning aims to recover reward models from expert demonstrations, but traditional methods yield "black-box" models that are difficult to interpret and debug. In this work, we introduce GRACE (Generating Rewards As CodE), a method for using Large Language Models within an evolutionary search to reverse-engineer an interpretable, code-based reward function directly from expert trajectories. The resulting reward function is executable code that can be inspected and verified.…

@… depending on where you are, Vimeo is already enshittified : in France the search do not work anymore.

AI workplace agents startup Genspark raised a $275M Series B at a $1.25B valuation and says it hit $50M in annualized revenue after pivoting from AI search (Anna Tong/Forbes)
https://www.forbes.com/sites/annatong/2025/11/20/genspark…

Genspark Joins The Unicorn Club With Latest Funding Round
The startup, which offers AI work productivity tools, got to $50 million in annualized revenue just five months after launching its suite of AI agents.

Graph-Based Approximate Nearest Neighbor Search Revisited: Theoretical Analysis and Optimization
Xinran Ma, Zhaoqi Zhou, Chuan Zhou, Qi Meng, Zaijiu Shang, Guoliang Li, Zhiming Ma
https://arxiv.org/abs/2509.15531

Graph-Based Approximate Nearest Neighbor Search Revisited: Theoretical Analysis and Optimization
Graph-based approaches to approximate nearest neighbor search (ANNS) have achieved remarkable success in enabling fast, high-recall retrieval on billion-scale vector datasets. Among them, the Sparse Neighborhood Graph (SNG) has emerged as a widely adopted graph structure due to its superior search performance. However, the theoretical understanding of SNG remains limited, leading to reliance on heuristic-based and often suboptimal truncation strategies. In this work, we aim to bridge the gap be…

I just spent ~20 minutes trying to find information on how to do something in a Golang library on my client computer, before I decided it was worth pulling up @… on my personal computer to look it up instead.
Immediately found the answer I needed to get me moving.
We don’t need “vibe coding”, we need search engines that actually work.

ALNS for Tugboat Scheduling in Inland Waterway
Zihang Ma
https://arxiv.org/abs/2509.19718 https://arxiv.org/pdf/2509.19718…

ALNS for Tugboat Scheduling in Inland Waterway
This paper focuses on the barges shipping problem, also known as the tugboats scheduling problem, within the context of a scenario where a single tugboat has the capacity to tow multiple barges and conduct multiple trips in a drop-and-pull mode during a daily work shift. The problem is mathematically formalized as mixed-integer programming models. To tackle real-world-sized problem instances, an adaptive large neighborhood search (ALNS) algorithm integrated with a decoding mathematical model is…

None tech, techy.
All you see, read, and hear people talk about is AI. Everyone wants the latest phone with AI baked in, feeding those models with every step you take and every conversation you make. And honestly? I don’t get it.
For me, AI is a search tool. A new “Google it.” Something to nudge me at work when I forget how to do something — which is about 99% of the time because my brain is like a sieve. Say something to it and it’s gone in 60 seconds.
So yeah, I don’t see wh…

Improving Disease Risk Estimation in Small Areas by Accounting for Spatiotemporal Local Discontinuities
Santaf\'e, G., Adin, A., Ugarte, M. L
https://arxiv.org/abs/2509.19889

Improving Disease Risk Estimation in Small Areas by Accounting for Spatiotemporal Local Discontinuities
This work proposes a two-step method to enhance disease risk estimation in small areas by integrating spatiotemporal cluster detection within a Bayesian hierarchical spatiotemporal model. First, we introduce an efficient scan-statistic-based clustering algorithm that employs a greedy search within the scan window, enabling flexible cluster detection across large spatial domains. We then integrate these detected clusters into a Bayesian spatiotemporal model to estimate relative risks, explicitly…

Three-dimensional Search for Annihilating Dark Matter in CBe dSph with the MAGIC Telescopes
Stefan Fr\"ose (for the MAGIC Collaboration), Dominik Martin El\"asser (for the MAGIC Collaboration), Hendrik Hildebrandt, Elisa Pueschel
https://arxiv.org/abs/2509.18861

Three-dimensional Search for Annihilating Dark Matter in CBe dSph with the MAGIC Telescopes
Dark matter (DM) candidates, such as Weakly Interacting Massive Particles (WIMPs), can annihilate to Standard Model particles, subsequently producing gamma rays. In this work, we search for DM-induced gamma-ray signals from Coma Berenices dwarf spheroidal galaxy (CBe dSph) using approximately 25 hours of observations carried out by the Major Atmospheric Gamma Imaging Cherenkov (MAGIC) Telescope, located at Roque de los Muchachos Observatory, La Palma, Spain. Building upon preceding analyses in …

Do LLM Agents Know How to Ground, Recover, and Assess? A Benchmark for Epistemic Competence in Information-Seeking Agents
Jiaqi Shao, Yuxiang Lin, Munish Prasad Lohani, Yufeng Miao, Bing Luo
https://arxiv.org/abs/2509.22391

Do LLM Agents Know How to Ground, Recover, and Assess? A Benchmark for Epistemic Competence in Information-Seeking Agents
Recent work has explored training Large Language Model (LLM) search agents with reinforcement learning (RL) for open-domain question answering (QA). However, most evaluations focus solely on final answer accuracy, overlooking how these agents reason with and act on external evidence. We introduce SeekBench, the first benchmark for evaluating the \textit{epistemic competence} of LLM search agents through step-level analysis of their response traces. SeekBench comprises 190 expert-annotated trace…

InfoAgent: Advancing Autonomous Information-Seeking Agents
Gongrui Zhang, Jialiang Zhu, Ruiqi Yang, Kai Qiu, Miaosen Zhang, Zhirong Wu, Qi Dai, Bei Liu, Chong Luo, Zhengyuan Yang, Linjie Li, Lijuan Wang, Weizhu Chen, Yuan Zhang, Xin Li, Zhaoyi Liu, Xin Geng, Baining Guo
https://arxiv.org/abs/2509.25189…

InfoAgent: Advancing Autonomous Information-Seeking Agents
Building Large Language Model agents that expand their capabilities by interacting with external tools represents a new frontier in AI research and applications. In this paper, we introduce InfoAgent, a deep research agent powered by an innovative data synthesis pipeline and orchestrated web search tools. To construct challenging, hard-to-find queries,we build entity trees and apply sub-tree sampling with entity fuzzification to systematically increase question difficulty. Unlike prior work tha…

Bacterial Gene Regulatory Neural Network as a Biocomputing Library of Mathematical Solvers
Adrian Ratwatte, Samitha Somathilaka, Thanh Cao, Xu Li, Sasitharan Balasubramaniam
https://arxiv.org/abs/2509.21598

Bacterial Gene Regulatory Neural Network as a Biocomputing Library of Mathematical Solvers
Current biocomputing approaches predominantly rely on engineered circuits with fixed logic, offering limited stability and reliability under diverse environmental conditions. Here, we use the GRNN framework introduced in our previous work to transform bacterial gene expression dynamics into a biocomputing library of mathematical solvers. We introduce a sub-GRNN search algorithm that identifies functional subnetworks tailored to specific mathematical calculation and classification tasks by evalu…

Okay, here's the promised follow-up with more authors I respect who didn't make it onto this list. I won't do deep dives but I'll list at least one work per author:
YA novelists:
- Randi Pink ("Girls Like Us")
- Louisa Onomé ("Twice as Perfect")
- Emery Lee ("Meet Cute Diary")
- Robin Benway ("Far from the Tree")
- Angela Velez ("Lulu and Milagro's Search for Clarity")
Children's book authors:
- Jacqueline Davies ("Bubbles Up")
- Freya Hartas ("Slow Down in the Park")
Novelists:
- Rimma Onoseta ("How You Grow Wings")
Graphic novelists:
- Linda Medley ("Castle Waiting")
- 🖋️Magsalene Visaggio 🖌️Paulina Ganucheau ("Girlmode")
- Ursula Vernon ("Digger")
- SJ Sindu ("Tall Water" w/ Dion MBD)
- Hope Larson ("Be That Way"; "Salt Magic" w/ Rebecca Mock)
- Lily Williams Karen Schneemann ("Go With the Flow")
- Maia Kobabe ("Gender Queer")
- Kay O'Neill ("Tea Dragon Society")
- Marjane Satrapi ("Persepolis")
Mangaka:
- Kaoru Mori ("Young Bride's Stories")
- Ryoko Kui ("Delicious in Dungeon")
- Natsuki Takaya ("Fruits Basket")
Anime writers/directors and/or Japanese light/fantasy/SF novelists:
- Nahoko Uehashi ("Moribito")
- Sayo Yamamoto ("Michiko & Hatchin"; "Yuri!!! On Ice")
- Mari Okada ("Ano Hana: The Flower we Saw That Day"; "Toradora!")
Game designers/programmers:
(Upon review I was pretty remiss in skipping over a few of these people, some of whom I wasn't aware of but most of whom I just didn't remember when writing my short list. Subconscious misogyny in action. Short & Thorson probably would have squeezed out some of the YA authors I included, although I have no real regrets.)
- Junko Kawano ("Suikoden")
- Elizabeth LaPensée ("When Rivers Were Trails")
- Momo Pixel ("Hair Nah")
- Zoë Quinn ("Depression Quest"; narrative designer on "Solar Ash")
- Kellee Santiago ("Cloud"; "Flower")
- Tanya X. Short ("Moon Hunters")
- Kim Swift ("Portal")
- Maddy Thorson ("Celeste")
- Andi McClure @… ("Jumpman")
Note: I haven't included composers or artists here, but there's a deep bench.
Games journalists/steamers:
- Tanya DePass @… (#/INeedDiverseGames; twitch streams)
- Anita Sarkeesian (Feminist Frequency)
Game/play scholars:
- Mary Flanagan ("Critical Play")
- Tracy Fullerton ("Game Design Workshop")
- Brenda Laurel ("Toward the Design of a Computer-Based Interactive Fantasy System")
- Janet Murray ("Hamlet on the Holodeck"l
- Susana Tosca ("A Pragmatics of Links")
- Jichen Zhu ("Agency Play: Dimensions of Agency for Interactive Narrative Design")
- Magy Seif El Nasr ("Design patterns to guide player movement in 3D games")
- Kate Compton ("Causal Creators"; also "Spore")
P.S. upon consideration I've decided not to include any authors who are men in this coda.
There are definitely others who probably deserve to be here that I'm forgetting...
#GsmeDesign #Authors

OpenAI expands group chats in ChatGPT globally to all logged-in users on Free, Go, Plus, and Pro plans, after piloting the feature in select regions (Aisha Malik/TechCrunch)
https://techcrunch.com/2025/11/20/chatgpt-launches-group-chats-globally/

ChatGPT launches group chats globally | TechCrunch
The company sees group chats in ChatGPT as a way for people to coordinate trips, co-write documents, settle debates, or work through research together, while ChatGPT helps search, summarize, and compare options.

Random Forest Classification of MBTA Gravitational-Wave Triggers for Low-Latency Detection
Lorenzo Mobilia, Gianluca Maria Guidi
https://arxiv.org/abs/2509.12882 https://…

Random Forest Classification of MBTA Gravitational-Wave Triggers for Low-Latency Detection
In this work, we explore a possible application of a machine learning classifier for candidate events in a template-based search for gravitational-wave (GW) signals from various compact system sources. We analyze data from the O3a and O3b data acquisition campaign, during which the sensitivity of ground-based detectors is limited by real non-Gaussian noise transient. The state-of-the-art searches for such signals tipically rely on the signal-to-noise ratio (SNR) and a chi-square test to assess …

Observation-Free Attacks on Online Learning to Rank
Sameep Chattopadhyay, Nikhil Karamchandani, Sharayu Mohair
https://arxiv.org/abs/2509.22855 https://arx…

Observation-Free Attacks on Online Learning to Rank
Online learning to rank (OLTR) plays a critical role in information retrieval and machine learning systems, with a wide range of applications in search engines and content recommenders. However, despite their extensive adoption, the susceptibility of OLTR algorithms to coordinated adversarial attacks remains poorly understood. In this work, we present a novel framework for attacking some of the widely used OLTR algorithms. Our framework is designed to promote a set of target items so that they …

Boundary on the Table: Efficient Black-Box Decision-Based Attacks for Structured Data
Roie Kazoom, Yuval Ratzabi, Etamar Rothstein, Ofer Hadar
https://arxiv.org/abs/2509.22850 h…

Boundary on the Table: Efficient Black-Box Decision-Based Attacks for Structured Data
Adversarial robustness in structured data remains an underexplored frontier compared to vision and language domains. In this work, we introduce a novel black-box, decision-based adversarial attack tailored for tabular data. Our approach combines gradient-free direction estimation with an iterative boundary search, enabling efficient navigation of discrete and continuous feature spaces under minimal oracle access. Extensive experiments demonstrate that our method successfully compromises nearly …

Efficient Grand Canonical Global Optimization with On-the-fly-trained Machine-learning Interatomic Potentials
Jon Eunan Quinlivan Dominguez, Mads-Peter Verner Christiansen, Konstantin M. Neyman, B{\o}jrk Hammer, Albert Bruix
https://arxiv.org/abs/2509.19968

Efficient Grand Canonical Global Optimization with On-the-fly-trained Machine-learning Interatomic Potentials
The characterization of nanostructued materials under reactive environments is challenging due to the complexity of the structural motifs involved and their chemical transformations. Global optimization approaches allow predicting stable structures for targeted materials but addressing the configurational and compositional search spaces is both computationally demanding and inefficient, especially when first principles calculations are required. In this work, we implement and evaluate a computa…

Evaluating Large Language Models for Cross-Lingual Retrieval
Longfei Zuo, Pingjun Hong, Oliver Kraus, Barbara Plank, Robert Litschko
https://arxiv.org/abs/2509.14749 https://

Evaluating Large Language Models for Cross-Lingual Retrieval
Multi-stage information retrieval (IR) has become a widely-adopted paradigm in search. While Large Language Models (LLMs) have been extensively evaluated as second-stage reranking models for monolingual IR, a systematic large-scale comparison is still lacking for cross-lingual IR (CLIR). Moreover, while prior work shows that LLM-based rerankers improve CLIR performance, their evaluation setup relies on lexical retrieval with machine translation (MT) for the first stage. This is not only prohibi…

Instrument, Variable and Model Selection with Nonignorable Nonresponse
Ji Chen, Jun Shao
https://arxiv.org/abs/2509.12557 https://arxiv.org/pdf/2509.12557

Instrument, Variable and Model Selection with Nonignorable Nonresponse
With nonignorable nonresponse, an effective method to construct valid estimators of population parameters is to use a covariate vector called instrument that can be excluded from the nonresponse propensity but are still useful covariate even when other covariates are conditioned. The existing work in this approach assumes such an instrument is given, which is frequently not the case in applications. In this paper we investigate how to search for an instrument from a given set of covariates. The…

FragmentRetro: A Quadratic Retrosynthetic Method Based on Fragmentation Algorithms
Yu Shee, Anthony M. Smaldone, Anton Morgunov, Gregory W. Kyro, Victor S. Batista
https://arxiv.org/abs/2509.15409

FragmentRetro: A Quadratic Retrosynthetic Method Based on Fragmentation Algorithms
Retrosynthesis, the process of deconstructing a target molecule into simpler precursors, is crucial for computer-aided synthesis planning (CASP). Widely adopted tree-search methods often suffer from exponential computational complexity. In this work, we introduce FragmentRetro, a novel retrosynthetic method that leverages fragmentation algorithms, specifically BRICS and r-BRICS, combined with stock-aware exploration and pattern fingerprint screening to achieve quadratic complexity. FragmentRetr…

Long-lived axion-like particles from electromagnetic cascades
Samuel Patrone, Nikita Blinov, Ryan Plestid
https://arxiv.org/abs/2509.14310 https://arxiv.or…

Long-lived axion-like particles from electromagnetic cascades
We study axion-like particles (ALPs) in beam dump experiments, focusing on the Search for Hidden Particles (SHiP, at CERN) experiment and the Beam Dump eXperiment (BDX, at JLab). Many existing projections for sensitivity to ALPs in beam dump experiments have focused on production from either the primary proton/electron beam, or - in the case of SHiP - the secondary (high-energy) photons produced by neutral meson decays (e.g., $π^0\rightarrowγγ$). In this work, we study the subsequent product…