Tootfinder

Context as Memory: Scene-Consistent Interactive Long Video Generation with Memory Retrieval
Jiwen Yu, Jianhong Bai, Yiran Qin, Quande Liu, Xintao Wang, Pengfei Wan, Di Zhang, Xihui Liu
https://arxiv.org/abs/2506.03141

Context as Memory: Scene-Consistent Interactive Long Video Generation with Memory Retrieval
Recent advances in interactive video generation have shown promising results, yet existing approaches struggle with scene-consistent memory capabilities in long video generation due to limited use of historical context. In this work, we propose Context-as-Memory, which utilizes historical context as memory for video generation. It includes two simple yet effective designs: (1) storing context in frame format without additional post-processing; (2) conditioning by concatenating context and frame…

DM-SegNet: Dual-Mamba Architecture for 3D Medical Image Segmentation with Global Context Modeling
Hangyu Ji
https://arxiv.org/abs/2506.05297 https://

DM-SegNet: Dual-Mamba Architecture for 3D Medical Image Segmentation with Global Context Modeling
Accurate 3D medical image segmentation demands architectures capable of reconciling global context modeling with spatial topology preservation. While State Space Models (SSMs) like Mamba show potential for sequence modeling, existing medical SSMs suffer from encoder-decoder incompatibility: the encoder's 1D sequence flattening compromises spatial structures, while conventional decoders fail to leverage Mamba's state propagation. We present DM-SegNet, a Dual-Mamba architecture integrating direct…

A developer details how he shipped Context, a native macOS app that was almost 100% built using Claude Code (Indragie Karunaratne/My Portfolio)
https://www.indragie.com/blog/i-shipped-a-macos-app-built-entirely-by-claude-code

I Shipped a macOS App Built Entirely by Claude Code
How I built Context—a native macOS SwiftUI app for debugging MCP servers—almost entirely with Claude Code, and what I learned about building with AI coding agents.

OMD at the Greek Theater in Los Angeles, performing 'Anthropocene' June 21, 2025.
https://open.spotify.com/track/1zTghGUFb7Ajrn5ghO9ZQl?si=XNxEhurBRXaWIu3kJmY42Q&context=spotify:album:2yW1JUK…

Anthropocene
Orchestral Manoeuvres In The Dark · Bauhaus Staircase (The Complete Edition) · Song · 2023

This https://arxiv.org/abs/2505.21427 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csAI_…

Policy Induction: Predicting Startup Success via Explainable Memory-Augmented In-Context Learning
Early-stage startup investment is a high-risk endeavor characterized by scarce data and uncertain outcomes. Traditional machine learning approaches often require large, labeled datasets and extensive fine-tuning, yet remain opaque and difficult for domain experts to interpret or improve. In this paper, we propose a transparent and data-efficient investment decision framework powered by memory-augmented large language models (LLMs) using in-context learning (ICL). Central to our method is a natu…

Thanks for the thoughtful replies. Answers to questions:
Many people asked for the context. This is for college students using what they already know about the order of arithmetic operations to start analyzing the structure of code. In the activity, they visual code structures using these kind of diagrams. The important thing here is thus not just subtraction; it’s this way of visualizing the relationships — and there already is a sight-centeric word, “visualize!” But I suspect a blind reader could also use these spatial relationships as a learning tool…if there were a good way of conveying the spatial relationships.

This https://arxiv.org/abs/2506.02040 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCR_…

Beyond the Protocol: Unveiling Attack Vectors in the Model Context Protocol Ecosystem
The Model Context Protocol (MCP) is an emerging standard designed to enable seamless interaction between Large Language Model (LLM) applications and external tools or resources. Within a short period, thousands of MCP services have already been developed and deployed. However, the client-server integration architecture inherent in MCP may expand the attack surface against LLM Agent systems, introducing new vulnerabilities that allow attackers to exploit by designing malicious MCP servers. In th…

Improving LLM-Based Fault Localization with External Memory and Project Context
Inseok Yeo, Duksan Ryu, Jongmoon Baik
https://arxiv.org/abs/2506.03585 http…

Improving LLM-Based Fault Localization with External Memory and Project Context
Fault localization, the process of identifying the software components responsible for failures, is essential but often time-consuming. Recent advances in Large Language Models (LLMs) have enabled fault localization without extensive defect datasets or model fine-tuning. However, existing LLM-based methods rely only on general LLM capabilities and lack integration of project-specific knowledge, resulting in limited effectiveness, especially for complex software. We introduce MemFL, a novel ap…

This https://arxiv.org/abs/2502.12089 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_sta…

How Compositional Generalization and Creativity Improve as Diffusion Models are Trained
Natural data is often organized as a hierarchical composition of features. How many samples do generative models need in order to learn the composition rules, so as to produce a combinatorially large number of novel data? What signal in the data is exploited to learn those rules? We investigate these questions in the context of diffusion models both theoretically and empirically. Theoretically, we consider a simple probabilistic context-free grammar - a tree-like graphical model used to represe…

[Thread] an NYT standards editor responds to criticism of its recent Zohran Mamdani story, says the "ultimate source" was Columbia data that Mamdani confirmed (Patrick Healy/@patrickhealynyt)
https://x.com/patrickhealynyt/status/1941262786006483418

Patrick Healy (@patrickhealynyt) on X
As the @nytimes assistant managing editor for Standards and Trust, I’ve received reader feedback regarding our reporting on Zohran Mamdani’s 2009 application to Columbia University. To provide context on how the reporting came together, I wanted to share some information:

"Instead of calculators, we could sit at exams with certain books on our desks, filled with logarithm and trigonometry tables, featuring formulae for algebra, calculus, and geometry. French-speaking Swiss students might remember the ubiquitous “Formulaire et Tables” of the “Commissions romandes de mathématiques, de physique et de chimie”, published by the Éditions du Tricorne, that many generations of Swiss students used during their exams."

Banning, Adopting, Reckoning
Last month, OpenAI, the company (in)famous for their ChatGPT product, released a course called "ChatGPT Foundations for K-12 Educators", an event that has raised more than a few eyebrows, and even some outrage. We must have a serious conversation about the value of a bullshit generator in the context of teaching programming skills to new generations.

Medical Data Pecking: A Context-Aware Approach for Automated Quality Evaluation of Structured Medical Data
Irena Girshovitz, Atai Ambus, Moni Shahar, Ran Gilad-Bachrach
https://arxiv.org/abs/2507.02628

Medical Data Pecking: A Context-Aware Approach for Automated Quality Evaluation of Structured Medical Data
Background: The use of Electronic Health Records (EHRs) for epidemiological studies and artificial intelligence (AI) training is increasing rapidly. The reliability of the results depends on the accuracy and completeness of EHR data. However, EHR data often contain significant quality issues, including misrepresentations of subpopulations, biases, and systematic errors, as they are primarily collected for clinical and billing purposes. Existing quality assessment methods remain insufficient, la…

Context-aware gate set tomography: Improving the self-consistent characterization of trapped-ion universal gate sets by leveraging non-Markovianity
Pablo Vi\~nas, Alejandro Bermudez
https://arxiv.org/abs/2507.02542

Context-aware gate set tomography: Improving the self-consistent characterization of trapped-ion universal gate sets by leveraging non-Markovianity
To progress in the characterization of noise for current quantum computers, gate set tomography (GST) has emerged as a self-consistent tomographic protocol that can accurately estimate the complete set of noisy quantum gates, state preparations, and measurements. In its original incarnation, GST improves the estimation precision by applying the gates sequentially, provided that the noise makes them a set of fixed completely-positive and trace preserving (CPTP) maps independent of the history of…

Figma releases Dev Mode Model Context Protocol server, which provides more context about how AI designs are created in Figma (Jess Weatherbed/The Verge)
https://www.theverge.com/news/679439/figma-dev-mode-mcp-server-beta-release

Figma will let your AI access its design servers
Figma is launching a Dev Mode MCP Server that can help AI models more effectively translate designs into fully coded applications.

This https://arxiv.org/abs/2505.09833 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csRO_…

Learning Rock Pushability on Rough Planetary Terrain
In the context of mobile navigation in unstructured environments, the predominant approach entails the avoidance of obstacles. The prevailing path planning algorithms are contingent upon deviating from the intended path for an indefinite duration and returning to the closest point on the route after the obstacle is left behind spatially. However, avoiding an obstacle on a path that will be used repeatedly by multiple agents can hinder long-term efficiency and lead to a lasting reliance on an ac…

This https://arxiv.org/abs/2505.17433 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csAI_…

MemeReaCon: Probing Contextual Meme Understanding in Large Vision-Language Models
Memes have emerged as a popular form of multimodal online communication, where their interpretation heavily depends on the specific context in which they appear. Current approaches predominantly focus on isolated meme analysis, either for harmful content detection or standalone interpretation, overlooking a fundamental challenge: the same meme can express different intents depending on its conversational context. This oversight creates an evaluation gap: although humans intuitively recognize ho…

This https://arxiv.org/abs/2404.11841 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csLO_…

On the Unprovability of Circuit Size Bounds in Intuitionistic $\mathsf{S}^1_2$
We show that there is a constant $k$ such that Buss's intuitionistic theory $\mathsf{IS}^1_2$ does not prove that SAT requires co-nondeterministic circuits of size at least $n^k$. To our knowledge, this is the first unconditional unprovability result in bounded arithmetic in the context of worst-case fixed-polynomial size circuit lower bounds. We complement this result by showing that the upper bound $\mathsf{NP} \subseteq \mathsf{coNSIZE}[n^k]$ is unprovable in $\mathsf{IS}^1_2$. In order to…

Async Rust: When to Use It and When to Avoid It
“Asynchronous” (often abbreviated as “async”) is a widely used term in computer science, but its meaning varies depending on the context. […]
🦀 https://fmoya.dev/posts/async-rust/

In-context Clustering-based Entity Resolution with Large Language Models: A Design Space Exploration
Jiajie Fu, Haitong Tang, Arijit Khan, Sharad Mehrotra, Xiangyu Ke, Yunjun Gao
https://arxiv.org/abs/2506.02509

In-context Clustering-based Entity Resolution with Large Language Models: A Design Space Exploration
Entity Resolution (ER) is a fundamental data quality improvement task that identifies and links records referring to the same real-world entity. Traditional ER approaches often rely on pairwise comparisons, which can be costly in terms of time and monetary resources, especially with large datasets. Recently, Large Language Models (LLMs) have shown promising results in ER tasks. However, existing methods typically focus on pairwise matching, missing the potential of LLMs to perform clustering di…

Hey, folks who understand alt text and limited vision accessibility:
I have need to write alt text for the diagram below. The alt text needs to be comprehensible to somebody who is encountering this kind of diagram for the ••very first time••. I could describe the images using the relevant jargon, but that would only serve people who already know the thing this activity is teaching them!
Any suggestions for how I could write good alt text for something like this? Is it possible? (The horizontal black bars are minus signs, i.e. subtraction. This is clear from context in the text, but probably not clear in the image.)
PLEASE NOTE: I am looking for people with ••relevant accessibility expertise••, not just random best shots from people who (like me) don’t really know much about this kind of problem.

This https://arxiv.org/abs/2404.06432 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csHC_…

Missing Pieces: How Do Designs that Expose Uncertainty Longitudinally Impact Trust in AI Decision Aids? An In Situ Study of Gig Drivers
Decision aids based on artificial intelligence (AI) induce a wide range of outcomes when they are deployed in uncertain environments. In this paper, we investigate how users' trust in recommendations from an AI decision aid is impacted over time by designs that expose uncertainty in predicted outcomes. Unlike previous work, we focus on gig driving - a real-world, repeated decision-making context. We report on a longitudinal mixed-methods study ($n=51$) where we measured gig drivers' trust as th…

Flare frequency in M dwarfs belonging to Young Moving Groups
E. Mamonova, Y. Shan, A. F. Kowalski, S. Wedemeyer S. C. Werner
https://arxiv.org/abs/2506.04465

Flare frequency in M dwarfs belonging to Young Moving Groups
Context. M stars are preferred targets for studying terrestrial exoplanets, for which we hope to obtain their atmosphere spectra in the next decade. However, M dwarfs have long been known for strong magnetic activity and the ability to frequently produce optical, broadband emission flares. Aims. We aim to characterise the flaring behaviour of young M dwarfs in the temporal, spectral, and energetic dimensions, as well as examine the stellar parameters governing this behaviour, in order to improv…

Context is Gold to find the Gold Passage: Evaluating and Training Contextual Document Embeddings
Max Conti, Manuel Faysse, Gautier Viaud, Antoine Bosselut, C\'eline Hudelot, Pierre Colombo
https://arxiv.org/abs/2505.24782

Context is Gold to find the Gold Passage: Evaluating and Training Contextual Document Embeddings
A limitation of modern document retrieval embedding methods is that they typically encode passages (chunks) from the same documents independently, often overlooking crucial contextual information from the rest of the document that could greatly improve individual chunk representations. In this work, we introduce ConTEB (Context-aware Text Embedding Benchmark), a benchmark designed to evaluate retrieval models on their ability to leverage document-wide context. Our results show that state-of-t…

Intentionally Unintentional: GenAI Exceptionalism and the First Amendment
David Atkinson, Jena D. Hwang, Jacob Morrison
https://arxiv.org/abs/2506.05211 ht…

Intentionally Unintentional: GenAI Exceptionalism and the First Amendment
This paper challenges the assumption that courts should grant First Amendment protections to outputs from large generative AI models, such as GPT-4 and Gemini. We argue that because these models lack intentionality, their outputs do not constitute speech as understood in the context of established legal precedent, so there can be no speech to protect. Furthermore, if the model outputs are not speech, users cannot claim a First Amendment speech right to receive the outputs. We also argue that ex…

This https://arxiv.org/abs/2312.09720 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_ees…

RIS-Enabled NLoS Near-Field Joint Position and Velocity Estimation under User Mobility
In the context of single-base station (BS) non-line-of-sight (NLoS) single-epoch localization with the aid of a reflective reconfigurable intelligent surface (RIS), this paper introduces a novel three-step algorithm that jointly estimates the position and velocity of a mobile user equipment (UE), while compensating for the Doppler effects observed in near-field (NF) at the RIS elements over the short transmission duration of a sequence of downlink (DL) pilot symbols. First, a low-complexity ini…

Goal-Oriented Semantic Resource Allocation with Cumulative Prospect Theoretic Agents
Symeon Vaidanis, Photios A. Stavrou, Marios Kountouris
https://arxiv.org/abs/2506.04947

Goal-Oriented Semantic Resource Allocation with Cumulative Prospect Theoretic Agents
We introduce a resource allocation framework for goal-oriented semantic networks, where participating agents assess system quality through subjective (e.g., context-dependent) perceptions. To accommodate this, our model accounts for agents whose preferences deviate from traditional expected utility theory (EUT), specifically incorporating cumulative prospect theory (CPT) preferences. We develop a comprehensive analytical framework that captures human-centric aspects of decision-making and risky…

This https://arxiv.org/abs/2506.01969 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csDC_…

FlashMLA-ETAP: Efficient Transpose Attention Pipeline for Accelerating MLA Inference on NVIDIA H20 GPUs
Efficient inference of Multi-Head Latent Attention (MLA) is challenged by deploying the DeepSeek-R1 671B model on a single Multi-GPU server. This paper introduces FlashMLA-ETAP, a novel framework that enhances MLA inference for the single-instance deployment scenario on NVIDIA H20 GPUs. We propose the Efficient Transpose Attention Pipeline (ETAP), which reconfigures attention computation through transposition to align the KV context length with the \(M\)-dimension in WGMMA operations, significa…

This https://arxiv.org/abs/2410.14899 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Out-of-distribution Robust Optimization
In this paper, we consider the contextual robust optimization problem under an out-of-distribution setting. The contextual robust optimization problem considers a risk-sensitive objective function for an optimization problem with the presence of a context vector (also known as covariates or side information) capturing related information. While the existing works mainly consider the in-distribution setting, and the resultant robustness achieved is in an out-of-sample sense, our paper studies an…

Beyond the Protocol: Unveiling Attack Vectors in the Model Context Protocol Ecosystem
Hao Song, Yiming Shen, Wenxuan Luo, Leixin Guo, Ting Chen, Jiashui Wang, Beibei Li, Xiaosong Zhang, Jiachi Chen
https://arxiv.org/abs/2506.02040

Beyond the Protocol: Unveiling Attack Vectors in the Model Context Protocol Ecosystem
The Model Context Protocol (MCP) is an emerging standard designed to enable seamless interaction between Large Language Model (LLM) applications and external tools or resources. Within a short period, thousands of MCP services have already been developed and deployed. However, the client-server integration architecture inherent in MCP may expand the attack surface against LLM Agent systems, introducing new vulnerabilities that allow attackers to exploit by designing malicious MCP servers. In th…

If you're a storyteller of any kind, without any context, which of these terms do you find more appealing?
Optional: in a comment -- share your associations with the term(s), or why you prefer one or the other, or another you prefer!
Thank you!

Very high-order accurate finite volume scheme for the streamfunction-vorticity formulation of incompressible fluid flows with polygonal meshes on arbitrary curved boundaries
Ricardo Costa (Institute for Polymers and Composites, University of Minho, Azur\'em Campus, 4804-058 Guimar\~aes, Portugal, Department of Polymer Engineering, University of Minho, Azur\'em Campus, 4804-058 Guimar\~aes, Portugal), St\'ephane Clain (Centre of Mathematics, University of Coimbra, 3000-143 C…

Very high-order accurate finite volume scheme for the streamfunction-vorticity formulation of incompressible fluid flows with polygonal meshes on arbitrary curved boundaries
Conventional mathematical models for simulating incompressible fluid flow problems are based on the Navier-Stokes equations expressed in terms of pressure and velocity. In this context, pressure-velocity coupling is a key issue, and countless numerical techniques and methods have been developed over the decades to solve these equations efficiently and accurately. In two dimensions, an alternative approach is to rewrite the Navier-Stokes equations regarding two scalar quantities: the streamfunct…

Leveraging In-Context Learning for Political Bias Testing of LLMs
Patrick Haller, Jannis Vamvas, Rico Sennrich, Lena A. J\"ager
https://arxiv.org/abs/2506.22232

Leveraging In-Context Learning for Political Bias Testing of LLMs
A growing body of work has been querying LLMs with political questions to evaluate their potential biases. However, this probing method has limited stability, making comparisons between models unreliable. In this paper, we argue that LLMs need more context. We propose a new probing task, Questionnaire Modeling (QM), that uses human survey data as in-context examples. We show that QM improves the stability of question-based bias evaluation, and demonstrate that it may be used to compare instruct…

Universal thermodynamic topological classes of static black holes in Conformal Killing Gravity
Hao Chen, Di Wu, Meng-Yao Zhang, Soroush Zare, Hassan Hassanabadi, Bekir Can L\"utf\"uo\u{g}lu, Zheng-Wen Long
https://arxiv.org/abs/2506.03695

Universal thermodynamic topological classes of static black holes in Conformal Killing Gravity
In this study, we develop a universal thermodynamic topological classes for the static black holes in the context of the Conformal Killing Gravity. Our findings indicate that the Conformal Killing Gravity significantly reconstructs the thermodynamic properties of both the smallest inner black hole state and the largest outer black hole state. Additionally, it considerably alters the thermodynamic stability of black holes across both high-temperature and low-temperature regimes. This analysis sh…

Position Auctions in AI-Generated Content
Santiago Balseiro, Kshipra Bhawalkar, Yuan Deng, Zhe Feng, Jieming Mao, Aranyak Mehta, Vahab Mirrokni, Renato Paes Leme, Di Wang, Song Zuo
https://arxiv.org/abs/2506.03309

Position Auctions in AI-Generated Content
We consider an extension to the classic position auctions in which sponsored creatives can be added within AI generated content rather than shown in predefined slots. New challenges arise from the natural requirement that sponsored creatives should smoothly fit into the context. With the help of advanced LLM technologies, it becomes viable to accurately estimate the benefits of adding each individual sponsored creatives into each potential positions within the AI generated content by properly t…

This https://arxiv.org/abs/2501.01444 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Local isometric immersions of pseudospherical surfaces described by a class of third order differential equations
We discuss a specific type of pseudospherical surfaces defined by a class of third order differential equations, of the form $u_t - u_{xxt} = λu^2 u_{xxx} + G(u, u_x, u_{xx})$, and poses a question about the dependence of the triples $\{a,b,c\}$ of the second fundamental form in the context of local isometric immersion in $\mathbb{E}^3$. It is demonstrated that the triples $\{a,b,c\}$ of the second fundamental form are not influenced by a jet of finite order of $u$. Instead, they are shown to …

This https://arxiv.org/abs/2505.18715 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_…

Cloud and Haze Parameterization in Atmospheric Retrievals: Insights from Titan's Cassini Data and JWST Observations of Hot Jupiters
Context: Before JWST, telescope observations were not sensitive enough to constrain the nature of clouds in exo-atmospheres. Recent observations, however, have inferred cloud signatures as well as haze-enhanced scattering slopes motivating the need for modern inversion techniques and a deeper understanding of the JWST information content. Aims: We aim to investigate the information content of JWST exoplanet spectra. We particularly focus on designing an inversion technique able to handle a wi…

Quantum Cognition Machine Learning for Forecasting Chromosomal Instability
Giuseppe Di Caro, Vahagn Kirakosyan, Alexander G. Abanov, Luca Candelori, Nadine Hartmann, Ernest T. Lam, Kharen Musaelian, Ryan Samson, Dario Villani, Martin T. Wells, Richard J. Wenstrup, Mengjia Xu
https://arxiv.org/abs/2506.03199

Quantum Cognition Machine Learning for Forecasting Chromosomal Instability
The accurate prediction of chromosomal instability from the morphology of circulating tumor cells (CTCs) enables real-time detection of CTCs with high metastatic potential in the context of liquid biopsy diagnostics. However, it presents a significant challenge due to the high dimensionality and complexity of single-cell digital pathology data. Here, we introduce the application of Quantum Cognition Machine Learning (QCML), a quantum-inspired computational framework, to estimate morphology-pred…

Europium, we have a problem. Modelling r-process enrichment across Local Group galaxies
Marco Palla, Marta Molero, Donatella Romano, Alessio Mucciarelli
https://arxiv.org/abs/2506.04066

Europium, we have a problem. Modelling r-process enrichment across Local Group galaxies
Context: Europium (Eu) serves as a crucial tracer to understand the origin of rapid neutron-capture process (r-process) elements. An extensive effort was made in the last decade to model the chemical evolution of this element in the Galaxy. However, less attention was reserved to Eu in different galaxies of the Local Group (LG). Aims: By employing detailed and well-tested chemical evolution models, we investigate Eu enrichment across LG dwarf spheroidal galaxies, allowing for a direct compariso…

This https://arxiv.org/abs/2410.19585 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

On the computation of accurate initial conditions for linear higher-index differential-algebraic equations and its application in initial value solvers
In contrast to regular ordinary differential equations, the problem of accurately setting initial conditions just emerges in the context of differential-algebraic equations where the dynamic degree of freedom of the system is smaller than the absolute dimension of the described process, and the actual lower-dimensional configuration space of the system is deeply implicit. For linear higher-index differential-algebraic equations, we develop an appropriate numerical method based on properties of …

Differentiable Fuzzy Cosmic-Web for Field Level Inference
P. Rossell\'o, F. -S. Kitaura, D. Forero-S\'anchez, F. Sinigaglia, G. Favole
https://arxiv.org/abs/2506.03969

Differentiable Fuzzy Cosmic-Web for Field Level Inference
A comprehensive analysis of the cosmological large-scale structure derived from galaxy surveys involves field-level inference, which requires a forward modelling framework that simultaneously accounts for structure formation and tracer bias. While structure formation models are well-understood, the development of an effective field-level bias model remains imprecise, particularly in the context of tracer perturbation theory within Bayesian reconstruction methods, which we address in this work. …

Linear Attention with Global Context: A Multipole Attention Mechanism for Vision and Physics
Alex Colagrande, Paul Caillon, Eva Feillet, Alexandre Allauzen
https://arxiv.org/abs/2507.02748

Linear Attention with Global Context: A Multipole Attention Mechanism for Vision and Physics
Transformers have become the de facto standard for a wide range of tasks, from image classification to physics simulations. Despite their impressive performance, the quadratic complexity of standard Transformers in both memory and time with respect to the input length makes them impractical for processing high-resolution inputs. Therefore, several variants have been proposed, the most successful relying on patchification, downsampling, or coarsening techniques, often at the cost of losing the f…

The president of El Salvador would not recognize Justice if it indicted him in The Hague and sentenced him for his crimes.
But let’s do it anyway just to be sure.
Context: https://apnews.com/article/kilmar-abrego-…

Multi-Focus Probes for Context-Preserving Network Exploration and Interaction in Immersive Analytics
Eric Zimmermann, Stefan Bruckner
https://arxiv.org/abs/2507.01140

Multi-Focus Probes for Context-Preserving Network Exploration and Interaction in Immersive Analytics
Immersive visualization of network data enables users to physically navigate and interact with complex structures, but managing transitions between detailed local (egocentric) views and global (exocentric) overviews remains a major challenge. We present a multifocus probe technique for immersive environments that allows users to instantiate multiple egocentric subgraph views while maintaining persistent links to the global network context. Each probe acts as a portable local focus, enabling fin…

This https://arxiv.org/abs/2505.11292 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_hepe…

Status of the International Linear Collider
This paper is not a proposal for a CERN future project but provides information on the International Linear Collider (ILC) considered for Japan in order to facilitate the European Strategy discussion in a global context. It describes progress to date, ongoing engineering studies, updated cost estimate for the machine at $\sqrt{s}=250~\rm GeV$ and the situation in Japan. The physics of the ILC is not presented here, but jointly for all Linear Collider projects in a separate document ``A Linear C…

This https://arxiv.org/abs/2308.07803 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Misspecified Bernstein-Von Mises theorem for hierarchical models
We derive a Bernstein von-Mises theorem in the context of misspecified, non-i.i.d., hierarchical models parametrized by a finite-dimensional parameter of interest. We apply our results to hierarchical models containing non-linear operators, including the squared integral operator, and PDE-constrained inverse problems. More specifically, we consider the elliptic, time-independent Schrödinger equation with parametric boundary condition and general parabolic PDEs with parametric potential and bou…

in case i need to ask something outside the context of the reddit-posting or video:
- generate a temporary URL (with the full posting/video transcript)
- call perplexity by URL and add the URL as context
with that, i can ask everything (full context included) that needs a search 😍
#php #laravel

@… https://mastodon.bsd.cafe/@grahamperrin/114609903145977883 might help to put it in context … the bug used to bug me (not automatically scrollin…

Did someone find a setup where their #NextcloudAssistant performs sensible tasks?
I have context agent running. It seems to provide general access to some #Nextcloud apps as I am asked if I want to create bogus calendar entries when asking the example commands like "list my calendars&qu…

Lattice and Orientational Defects Mediate Collective Transport of Confluent Cells
Jiusi Zhang, Chung Wing Chan, Bo Li, Rui Zhang
https://arxiv.org/abs/2506.04068

Lattice and Orientational Defects Mediate Collective Transport of Confluent Cells
Confluent tissues are a type of foam-like biological active matter. There is a recent interest in using active nematic liquid crystal framework to understand confluent cells, where topological (orientational) defects are believed to play a crucial role. However, how to reconcile the physical picture of lattice defects in Voronoi polygons with that of orientational defects in the nematic field$-$particularly in the context of cellular transport$-$remains elusive. Here, we employ the Active Verte…

3D Holographic Flow Cytometry Measurements of Microalgae: Strategies for Angle Recovery in Complex Rotation Patterns
Francesca Borrelli, Giusy Giugliano, Emilie Houliez, Jaromir Behal, Daniele Pirone, Leonilde Roselli, Angela Sardo, Valerio Zupo, Maria Costantini, Lisa Miccio, Pasquale Memmolo, Vittorio Bianco, Pietro Ferraro
https://

3D Holographic Flow Cytometry Measurements of Microalgae: Strategies for Angle Recovery in Complex Rotation Patterns
Marine ecosystems are in the spotlight, because environmental changes are threatening biodiversity and ecological functions. In this context, microalgae play key ecological roles both in planktonic and benthic ecosystems. Consequently, they are considered indispensable targets for global monitoring programs. However, due to a high spatial and temporal variability and to difficulties of species identification (still relying on microscopy observations), the assessment of roles played by these com…

Associative triple trisystems and standard embeddings
Ra\'ul Felipe, Guillermo Vera de Salas
https://arxiv.org/abs/2506.04191 https://

Associative triple trisystems and standard embeddings
Building on the established theories of Jordan triple disystems and Leibniz triple systems, we introduce and develop the theory of associative triple trisystems, filling a significant gap in the existing framework. We establish the classical relationships between associative, Jordan, and Lie triple systems within the context of trisystems. We present a significant example by equipping the space of matrices with a non-trivial associative dialgebra structure. We conclude defining the concept of d…

The term "context engineering" is gaining traction over "prompt engineering" as it better describes the skill of providing LLMs with the necessary information (Simon Willison/Simon Willison's Weblog)
https://simonwillison.net/2025/Jun/27/context-…

Deadlock-free Context-free Session Types
Andreia Mordido, Jorge A. P\'erez
https://arxiv.org/abs/2506.20356 https://arxiv.org/pdf…

Deadlock-free Context-free Session Types
We consider the problem of statically ensuring that message-passing programs never run into deadlocks. We focus on concurrent functional programs governed by context-free session types, which can express rich tree-like structures not expressible in standard session types. Existing techniques based on context-free session types enforce protocol conformance but not deadlock freedom. We propose a type system that enhances context-free session types with a priority-based approach to deadlock freedo…

Having legal protection insurance is always a good idea to, but IMHO it’s absolutely essential for professors due to the particular context in which we work. But I find that it’s hardly ever discussed.
An obvious example is the question of the limits of academic freedom, but many potential issues are way more trivial. ⇢
#AcademicChatter

Having legal protection insurance is always a good idea to, but IMHO it’s absolutely essential for professors due to the particular context in which we work. But I find that it’s hardly ever discussed.
An obvious example is the question of the limits of academic freedom, but many potential issues are way more trivial. ⇢
#AcademicChatter

Having legal protection insurance is always a good idea to, but IMHO it’s absolutely essential for professors due to the particular context in which we work. But I find that it’s hardly ever discussed.
An obvious example is the question of the limits of academic freedom, but many potential issues are way more trivial. ⇢
#AcademicChatter

An Open-source Capping Machine Suitable for Confined Spaces
Francisco Munguia-Galeano, Louis Longley, Satheeshkumar Veeramani, Zhengxue Zhou, Rob Clowes, Hatem Fakhruldeen, Andrew I. Cooper
https://arxiv.org/abs/2506.03743

An Open-source Capping Machine Suitable for Confined Spaces
In the context of self-driving laboratories (SDLs), ensuring automated and error-free capping is crucial, as it is a ubiquitous step in sample preparation. Automated capping in SDLs can occur in both large and small workspaces (e.g., inside a fume hood). However, most commercial capping machines are designed primarily for large spaces and are often too bulky for confined environments. Moreover, many commercial products are closed-source, which can make their integration into fully autonomous wo…

From Standalone LLMs to Integrated Intelligence: A Survey of Compound Al Systems
Jiayi Chen, Junyi Ye, Guiling Wang
https://arxiv.org/abs/2506.04565 https:…

From Standalone LLMs to Integrated Intelligence: A Survey of Compound Al Systems
Compound Al Systems (CAIS) is an emerging paradigm that integrates large language models (LLMs) with external components, such as retrievers, agents, tools, and orchestrators, to overcome the limitations of standalone models in tasks requiring memory, reasoning, real-time grounding, and multimodal understanding. These systems enable more capable and context-aware behaviors by composing multiple specialized modules into cohesive workflows. Despite growing adoption in both academia and industry, …

Context-Aware Code Wiring Recommendation with LLM-based Agent
Taiming Wang, Yanjie Jiang, Chunhao Dong, Yuxia Zhang, Hui Liu
https://arxiv.org/abs/2507.01315

Context-Aware Code Wiring Recommendation with LLM-based Agent
Copy-paste-modify is a widespread and pragmatic practice in software development, where developers adapt reused code snippets, sourced from platforms such as Stack Overflow, GitHub, or LLM outputs, into their local codebase. A critical yet underexplored aspect of this adaptation is code wiring, which involves substituting unresolved variables in the pasted code with suitable ones from the surrounding context. Existing solutions either rely on heuristic rules or historical templates, often faili…

Learning to Explore: An In-Context Learning Approach for Pure Exploration
Alessio Russo, Ryan Welch, Aldo Pacchiano
https://arxiv.org/abs/2506.01876 https:…

Learning to Explore: An In-Context Learning Approach for Pure Exploration
In this work, we study the active sequential hypothesis testing problem, also known as pure exploration, where the goal is to actively control a data collection process to efficiently identify the correct hypothesis underlying a decision problem. While relevant across multiple domains, devising adaptive exploration strategies remains challenging, particularly due to difficulties in encoding appropriate inductive biases. Existing Reinforcement Learning (RL)-based methods often underperform when …

Weak or strong: coupling of mixed oscillation modes on the red-giant branch
T. van Lier (Heidelberg Institute for Theoretical Studies, Zentrum f\"ur Astronomie Heidelberg), J. M\"uller (Heidelberg Institute for Theoretical Studies, Zentrum f\"ur Astronomie Heidelberg), S. Hekker (Heidelberg Institute for Theoretical Studies, Zentrum f\"ur Astronomie Heidelberg)

Weak or strong: coupling of mixed oscillation modes on the red-giant branch
Context. The high precision of recent asteroseismic observations of red-giant stars has revealed the presence of mixed dipole modes in their oscillation spectra. These modes allow for a look inside the stars. Among the parameters used to characterize mixed modes is the coupling strength q, which is sensitive to the stellar structure in the evanescent zone near the bottom of the convective envelope. Aims. The aim of this work is to probe the validity of the weak and strong coupling approximati…

The Data Dilemma: Authors' Intentions and Recognition of Research Data in Educational Technology Research
Sandra Schulz, Natalie Kiesler
https://arxiv.org/abs/2506.04954

The Data Dilemma: Authors' Intentions and Recognition of Research Data in Educational Technology Research
Educational Technology (EdTec) research is conducted by multiple disciplines, some of which annually meet at the DELFI conference. Due to the heterogeneity of involved researchers and communities, it is our goal to identify categories of research data overseen in the context of EdTec research. Therefore, we analyze the author's perspective provided via EasyChair where authors specified whether they had research data to share. We compared this information with an analysis of the submitted articl…

Visual Contextual Attack: Jailbreaking MLLMs with Image-Driven Context Injection
Ziqi Miao, Yi Ding, Lijun Li, Jing Shao
https://arxiv.org/abs/2507.02844 h…

Visual Contextual Attack: Jailbreaking MLLMs with Image-Driven Context Injection
With the emergence of strong visual-language capabilities, multimodal large language models (MLLMs) have demonstrated tremendous potential for real-world applications. However, the security vulnerabilities exhibited by the visual modality pose significant challenges to deploying such models in open-world environments. Recent studies have successfully induced harmful responses from target MLLMs by encoding harmful textual semantics directly into visual inputs. However, in these approaches, the v…

This https://arxiv.org/abs/2506.00605 has been replaced.
link: https://scholar.google.com/scholar?q=a

ABCDEFGH: An Adaptation-Based Convolutional Neural Network-CycleGAN Disease-Courses Evolution Framework Using Generative Models in Health Education
With the advancement of modern medicine and the development of technologies such as MRI, CT, and cellular analysis, it has become increasingly critical for clinicians to accurately interpret various diagnostic images. However, modern medical education often faces challenges due to limited access to high-quality teaching materials, stemming from privacy concerns and a shortage of educational resources (Balogh et al., 2015). In this context, image data generated by machine learning models, partic…

A Dynamic Framework for Semantic Grouping of Common Data Elements (CDE) Using Embeddings and Clustering
Madan Krishnamurthy, Daniel Korn, Melissa A Haendel, Christopher J Mungall, Anne E Thessen
https://arxiv.org/abs/2506.02160

A Dynamic Framework for Semantic Grouping of Common Data Elements (CDE) Using Embeddings and Clustering
This research aims to develop a dynamic and scalable framework to facilitate harmonization of Common Data Elements (CDEs) across heterogeneous biomedical datasets by addressing challenges such as semantic heterogeneity, structural variability, and context dependence to streamline integration, enhance interoperability, and accelerate scientific discovery. Our methodology leverages Large Language Models (LLMs) for context-aware text embeddings that convert CDEs into dense vectors capturing semant…

On the Role of Early-Termination for Age of Information in Tree-Based Random Access Protocols
Andrea Munari, Cedomir Stefanovic
https://arxiv.org/abs/2506.04793

On the Role of Early-Termination for Age of Information in Tree-Based Random Access Protocols
Age of Information (AoI) has emerged as a key metric for assessing data freshness in IoT applications, where a large number of devices report time-stamped updates to a monitor. Such systems often rely on random access protocols based on variations of ALOHA at the link layer, where collision resolution algorithms play a fundamental role to enable reliable delivery of packets. In this context, we provide the first analytical characterization of average AoI for the classical Capetanakis tree-based…

This https://arxiv.org/abs/2403.06708 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Tikhonov Regularization for Stochastic Non-Smooth Convex Optimization in Hilbert Spaces
To solve convex optimization problems with a noisy gradient input, we analyze the global behavior of subgradient-like flows under stochastic errors. The objective function is composite, being equal to the sum of two convex functions, one being differentiable and the other potentially non-smooth. We then use stochastic differential inclusions where the drift term is minus the subgradient of the objective function, and the diffusion term is either bounded or square-integrable. In this context, un…

This https://arxiv.org/abs/2503.05651 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_grqc_…

Inverting no-hair theorems: How requiring General Relativity solutions restricts scalar-tensor theories
Black hole solutions in general scalar-tensor theories are known to permit hair, i.e. non-trivial scalar profiles and/or metric solutions different from the ones of General Relativity (GR). Imposing that some such solutions$\unicode{x2013}$e.g. Schwarzschild or de Sitter solutions motivated in the context of black hole physics or cosmology$\unicode{x2013}$should exist, the space of scalar-tensor theories is strongly restricted. Here we investigate precisely what these restrictions are within ge…

This https://arxiv.org/abs/2506.02576 has been replaced.
link: https://scholar.google.com/scholar?q=a

ADFormer: Aggregation Differential Transformer for Passenger Demand Forecasting
Passenger demand forecasting helps optimize vehicle scheduling, thereby improving urban efficiency. Recently, attention-based methods have been used to adequately capture the dynamic nature of spatio-temporal data. However, existing methods that rely on heuristic masking strategies cannot fully adapt to the complex spatio-temporal correlations, hindering the model from focusing on the right context. These works also overlook the high-level correlations that exist in the real world. Effectively …

Spatial Coordinates as a Cell Language: A Multi-Sentence Framework for Imaging Mass Cytometry Analysis
Chi-Jane Chen, Yuhang Chen, Sukwon Yun, Natalie Stanley, Tianlong Chen
https://arxiv.org/abs/2506.01918

Spatial Coordinates as a Cell Language: A Multi-Sentence Framework for Imaging Mass Cytometry Analysis
Image mass cytometry (IMC) enables high-dimensional spatial profiling by combining mass cytometry's analytical power with spatial distributions of cell phenotypes. Recent studies leverage large language models (LLMs) to extract cell states by translating gene or protein expression into biological context. However, existing single-cell LLMs face two major challenges: (1) Integration of spatial information: they struggle to generalize spatial coordinates and effectively encode spatial context as …

The Onset of Feedback in Abell 1885: Evidence for Large-Scale Quenching Despite a Young Central AGN
Laurel White, Michael McDonald, Francesco Ubertosi, Massimo Gaspari, Julie Hlavacek-Larrondo, Helen Russell, Taweewat Somboonpanyakul
https://arxiv.org/abs/2506.03277

The Onset of Feedback in Abell 1885: Evidence for Large-Scale Quenching Despite a Young Central AGN
We present a new 8.5 ks Chandra observation of Abell 1885, obtained as part of the Cluster Evolution Reference Ensemble At Low-z (CEREAL) survey of ~200 low-z galaxy groups and clusters. These data reveal that Abell 1885 is a strong cool core, with a central cooling time of 0.43 Gyr, and that the central galaxy hosts an X-ray luminous point source at its center (L=2.3x10^42 erg/s), indicative of a rapidly accreting supermassive black hole. In the context of the larger CEREAL sample, we constrai…

Context, Credibility, and Control: User Reflections on AI Assisted Misinformation Tools
Varun Sangwan, Heidi Makitalo
https://arxiv.org/abs/2506.22940 http…

Context, Credibility, and Control: User Reflections on AI Assisted Misinformation Tools
This paper investigates how collaborative AI systems can enhance user agency in identifying and evaluating misinformation on social media platforms. Traditional methods, such as personal judgment or basic fact-checking, often fall short when faced with emotionally charged or context-deficient content. To address this, we designed and evaluated an interactive interface that integrates collaborative AI features, including real-time explanations, source aggregation, and debate-style interaction. T…

This https://arxiv.org/abs/2412.03293 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csRO_…

Diffusion-VLA: Generalizable and Interpretable Robot Foundation Model via Self-Generated Reasoning
In this paper, we present DiffusionVLA, a novel framework that seamlessly combines the autoregression model with the diffusion model for learning visuomotor policy. Central to our approach is a next-token prediction objective, enabling the model to reason effectively over the user's query in the context of current observations. Subsequently, a diffusion model is attached to generate robust action outputs. To enhance policy learning through self-reasoning, we introduce a novel reasoning injectio…

On Automating Security Policies with Contemporary LLMs
Pablo Fern\'andez Saura, K. R. Jayaram, Vatche Isahagian, Jorge Bernal Bernab\'e, Antonio Skarmeta
https://arxiv.org/abs/2506.04838

On Automating Security Policies with Contemporary LLMs
The complexity of modern computing environments and the growing sophistication of cyber threats necessitate a more robust, adaptive, and automated approach to security enforcement. In this paper, we present a framework leveraging large language models (LLMs) for automating attack mitigation policy compliance through an innovative combination of in-context learning and retrieval-augmented generation (RAG). We begin by describing how our system collects and manages both tool and API specification…

Jet-Feedback on kpc scales: a review
Dipanjan Mukherjee
https://arxiv.org/abs/2506.03888 https://arxiv.org/pdf/2506.03888

Jet-Feedback on kpc scales: a review
Relativistic jets from AGN are an important driver of feedback in galaxies. They interact with their environments over a wide range of physical scales during their lifetime, and an understanding of these interactions is crucial for unraveling the role of supermassive blackholes in shaping galaxy evolution. The impact of such jets have been traditionally considered in the context of heating the large-scale environments. However, in the last few decades there has been additional focus on the imme…

Enhancing Customer Service Chatbots with Context-Aware NLU through Selective Attention and Multi-task Learning
Subhadip Nandi, Neeraj Agrawal, Anshika Singh, Priyanka Bhatt
https://arxiv.org/abs/2506.01781

Enhancing Customer Service Chatbots with Context-Aware NLU through Selective Attention and Multi-task Learning
Customer service chatbots are conversational systems aimed at addressing customer queries, often by directing them to automated workflows. A crucial aspect of this process is the classification of the customer's intent. Presently, most intent classification models for customer care utilise only customer query for intent prediction. This may result in low-accuracy models, which cannot handle ambiguous queries. An ambiguous query like "I didn't receive my package" could indicate a delayed order, …

Bayesian ages of local young stellar associations I. Through the expansion rate method
J. Olivares, N. Miret-Roig, P. A. B. Galli, H. Bouy
https://arxiv.org/abs/2506.05130

Bayesian ages of local young stellar associations I. Through the expansion rate method
Context. Local young stellar associations (LYSAs <50 Myr and <150 pc) are important laboratories to test predictions from star-formation theories. Estimating their ages through various dating techniques with minimal biases is thus of paramount importance. Aims. We aim at determining the ages of LYSAs with the expansion rate dating technique. Methods. We estimate the ages of the LYSAs using literature membership lists, publicly available data (astrometry and radial velocities), and a recent open…

DCMF: A Dynamic Context Monitoring and Caching Framework for Context Management Platforms
Ashish Manchanda, Prem Prakash Jayaraman, Abhik Banerjee, Kaneez Fizza, Arkady Zaslavsky
https://arxiv.org/abs/2506.17226

DCMF: A Dynamic Context Monitoring and Caching Framework for Context Management Platforms
The rise of context-aware IoT applications has increased the demand for timely and accurate context information. Context is derived by aggregating and inferring from dynamic IoT data, making it highly volatile and posing challenges in maintaining freshness and real-time accessibility. Caching is a potential solution, but traditional policies struggle with the transient nature of context in IoT (e.g., ensuring real-time access for frequent queries or handling fast-changing data). To address this…

Bug Fixing with Broader Context: Enhancing LLM-Based Program Repair via Layered Knowledge Injection
Ramtin Ehsani, Esteban Parra, Sonia Haiduc, Preetha Chatterjee
https://arxiv.org/abs/2506.24015

Bug Fixing with Broader Context: Enhancing LLM-Based Program Repair via Layered Knowledge Injection
Prompting LLMs with bug-related context (e.g., error messages, stack traces) improves automated program repair, but many bugs still remain unresolved. In real-world projects, developers often rely on broader repository and project-level context beyond the local code to resolve such bugs. In this paper, we investigate how automatically extracting and providing such knowledge can improve LLM-based program repair. We propose a layered knowledge injection framework that incrementally augments LLMs …

This https://arxiv.org/abs/2502.03503 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_sta…

Analyzing limits for in-context learning
We examine limits of in-context learning (ICL) in transformer models trained from scratch, focusing on function approximation tasks as a controlled setting to uncover fundamental behaviors. While we show empirically that transformer models can generalize, approximating unseen classes of polynomial (non linear) functions, they cannot generalize beyond certain values. We provide both empirical and mathematical arguments explaining that these limitations stem from architectural components, namely …

Towards Human-like Preference Profiling in Sequential Recommendation
Zhongyu Ouyang, Qianlong Wen, Chunhui Zhang, Yanfang Ye, Soroush Vosoughi
https://arxiv.org/abs/2506.02261

Towards Human-like Preference Profiling in Sequential Recommendation
Sequential recommendation systems aspire to profile users by interpreting their interaction histories, echoing how humans make decisions by weighing experience, relative preference strength, and situational relevance. Yet, existing large language model (LLM)-based recommenders often fall short of mimicking the flexible, context-aware decision strategies humans exhibit, neglecting the structured, dynamic, and context-aware mechanisms fundamental to human behaviors. To bridge this gap, we propose…

Exposing and Mitigating Calibration Biases and Demographic Unfairness in MLLM Few-Shot In-Context Learning for Medical Image Classification
Xing Shen, Justin Szeto, Mingyang Li, Hengguan Huang, Tal Arbel
https://arxiv.org/abs/2506.23298

Exposing and Mitigating Calibration Biases and Demographic Unfairness in MLLM Few-Shot In-Context Learning for Medical Image Classification
Multimodal large language models (MLLMs) have enormous potential to perform few-shot in-context learning in the context of medical image analysis. However, safe deployment of these models into real-world clinical practice requires an in-depth analysis of the accuracies of their predictions, and their associated calibration errors, particularly across different demographic subgroups. In this work, we present the first investigation into the calibration biases and demographic unfairness of MLLMs'…

This https://arxiv.org/abs/2504.09460 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_grqc_…

Imprints of extra dimensions in eccentric eccentric extreme-mass-ratio inspirals gravitational waveforms
Studies regarding extra-dimensions have been of great interest in modern theoretical physics, including their observational consequences from future gravitational wave (GW) observatories. In this direction, extreme-mass-ratio inspirals (EMRIs), attracting considerable interest in GW astronomy and fundamental physics, can potentially provide a useful platform for the search of extra dimensions. In this paper, we examine a rotating braneworld black hole in the context of equatorial eccentric EMRI…

Totoro spoilers
Re the quoted post from @…:
The very first time I saw My Neighbor Totoro, it was because a friend cajoled me into attending the student anime club’s showing with absolutely no context whatsoever except “you •have• to see this movie, Paul.” I had no idea what genre it was. I had no idea that it was a movie considered suitable for kids. The last anime I’d seen was IIRC Ghost in the Shell; I was ready for anything.
When Mei went missing, I thought, “omg, is this a tragedy? I think this story is a tragedy!” The whole time they were looking for her, I was absolutely terrified. I thought for sure they’d found her sandal. I still tear up when they find her now, on every rewatching.
I’m so glad for that first viewing. It’s a much better movie that way. When you’re expecting an innocent movie about cute forest plushies, you see that. But when you see that it could be a tragedy — the mother’s shadowy illness, the lost child — it hits hard. https://wandering.shop/@Violinknitter/114792748619083661

IC-Custom: Diverse Image Customization via In-Context Learning
Yaowei Li, Xiaoyu Li, Zhaoyang Zhang, Yuxuan Bian, Gan Liu, Xinyuan Li, Jiale Xu, Wenbo Hu, Yating Liu, Lingen Li, Jing Cai, Yuexian Zou, Yancheng He, Ying Shan
https://arxiv.org/abs/2507.01926

IC-Custom: Diverse Image Customization via In-Context Learning
Image customization, a crucial technique for industrial media production, aims to generate content that is consistent with reference images. However, current approaches conventionally separate image customization into position-aware and position-free customization paradigms and lack a universal framework for diverse customization, limiting their applications across various scenarios. To overcome these limitations, we propose IC-Custom, a unified framework that seamlessly integrates position-awa…

Going Bayesian on the ages of nearby young stellar systems I. The expansion rate method
J. Olivares, A. Berihuete, H. Bouy
https://arxiv.org/abs/2506.05110

Going Bayesian on the ages of nearby young stellar systems I. The expansion rate method
Context. Determining the ages of young stellar systems is fundamental to test and validate current star-formation theories. Aims. We aim at developing a Bayesian version of the expansion rate method that incorporates the a priori knowledge on the stellar system's age and solves some of the caveats of the traditional frequentist approach. Methods. We upgrade an existing Bayesian hierarchical model with additional parameter hierarchies that include, amongst others, the system's age. For this late…

Test of conformal gravity as an alternative to dark matter from the observations of elliptical galaxies
Li-Xue Yue, Da-Ming Chen
https://arxiv.org/abs/2506.03955

Test of conformal gravity as an alternative to dark matter from the observations of elliptical galaxies
As an alternative gravitational theory to General Relativity (GR), the Conformal Gravity (CG) has recently been successfully verified by observations of Type Ia supernovae (SN Ia) and the rotation curves of spiral galaxies. The observations of galaxies only pertain to the non-relativistic form of gravity. In this context, within the framework of the Newtonian theory of gravity (the non-relativistic form of GR), dark matter is postulated to account for the observations. On the other hand, the no…

Context-Driven Knowledge Graph Completion with Semantic-Aware Relational Message Passing
Siyuan Li, Ruitong Liu, Yan Wen, Te Sun
https://arxiv.org/abs/2506.23141

Context-Driven Knowledge Graph Completion with Semantic-Aware Relational Message Passing
Semantic context surrounding a triplet $(h, r, t)$ is crucial for Knowledge Graph Completion (KGC), providing vital cues for prediction. However, traditional node-based message passing mechanisms, when applied to knowledge graphs, often introduce noise and suffer from information dilution or over-smoothing by indiscriminately aggregating information from all neighboring edges. To address this challenge, we propose a semantic-aware relational message passing. A core innovation of this framework …

Principal Context-aware Diffusion Guided Data Augmentation for Fault Localization
Shihao Fu, Yan Lei
https://arxiv.org/abs/2505.24079 https://

Principal Context-aware Diffusion Guided Data Augmentation for Fault Localization
Test cases are indispensable for conducting effective fault localization (FL). However, test cases in practice are severely class imbalanced, i.e. the number of failing test cases (i.e. minority class) is much less than that of passing ones (i.e. majority class). The severe class imbalance between failing and passing test cases have hindered the FL effectiveness. To address this issue, we propose PCD-DAug: a Principal Context-aware Diffusion guided Data Augmentation approach that generate syn…

A Generative Adaptive Replay Continual Learning Model for Temporal Knowledge Graph Reasoning
Zhiyu Zhang, Wei Chen, Youfang Lin, Huaiyu Wan
https://arxiv.org/abs/2506.04083

A Generative Adaptive Replay Continual Learning Model for Temporal Knowledge Graph Reasoning
Recent Continual Learning (CL)-based Temporal Knowledge Graph Reasoning (TKGR) methods focus on significantly reducing computational cost and mitigating catastrophic forgetting caused by fine-tuning models with new data. However, existing CL-based TKGR methods still face two key limitations: (1) They usually one-sidedly reorganize individual historical facts, while overlooking the historical context essential for accurately understanding the historical semantics of these facts; (2) They preserv…

This https://arxiv.org/abs/2402.02160 has been replaced.
link: https://scholar.google.com/scholar?q=a

Data Poisoning for In-context Learning
In the domain of large language models (LLMs), in-context learning (ICL) has been recognized for its innovative ability to adapt to new tasks, relying on examples rather than retraining or fine-tuning. This paper delves into the critical issue of ICL's susceptibility to data poisoning attacks, an area not yet fully explored. We wonder whether ICL is vulnerable, with adversaries capable of manipulating example data to degrade model performance. To address this, we introduce ICLPoison, a speciali…

This https://arxiv.org/abs/2505.08861 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_…

Marvelous Metals: Surveying the Circumgalactic Medium of Simulated Dwarf Galaxies
Dwarf galaxies are uniquely sensitive to energetic feedback processes and are known to experience substantial mass and metal loss from their disk. Here, we investigate the circumgalactic medium (CGM) of 64 isolated dwarf galaxies ($6.0<$log(M$_*/M_{\odot}$)$<9.5$) at $z=0$ from the Marvel-ous Dwarfs and Marvelous Massive Dwarfs hydrodynamic simulations. Our galaxies produce column densities broadly consistent with current observations. We investigate these column densities in the context of mas…

CooT: Learning to Coordinate In-Context with Coordination Transformers
Huai-Chih Wang, Hsiang-Chun Chuang, Hsi-Chun Cheng, Dai-Jie Wu, Shao-Hua Sun
https://arxiv.org/abs/2506.23549

CooT: Learning to Coordinate In-Context with Coordination Transformers
Effective coordination among artificial agents in dynamic and uncertain environments remains a significant challenge in multi-agent systems. Existing approaches, such as self-play and population-based methods, either generalize poorly to unseen partners or require extensive training. To overcome these limitations, we propose Coordination Transformers (CooT), a novel in-context coordination framework that uses recent interaction histories to adapt to unseen partners rapidly. Unlike previous appr…

Understanding and Improving Length Generalization in Recurrent Models
Ricardo Buitrago Ruiz, Albert Gu
https://arxiv.org/abs/2507.02782 https://

Understanding and Improving Length Generalization in Recurrent Models
Recently, recurrent models such as state space models and linear attention have become popular due to their linear complexity in the sequence length. Thanks to their recurrent nature, in principle they can process arbitrarily long sequences, but their performance sometimes drops considerably beyond their training context lengths-i.e. they fail to length generalize. In this work, we provide comprehensive empirical and theoretical analysis to support the unexplored states hypothesis, which posits…

In-context learning for the classification of manipulation techniques in phishing emails
Antony Dalmiere (LAAS-TRUST, LAAS), Guillaume Auriol (LAAS-TRUST, INSA Toulouse), Vincent Nicomette (LAAS-TSF, LAAS), Pascal Marchand (LERASS)
https://arxiv.org/abs/2506.22515

In-context learning for the classification of manipulation techniques in phishing emails
Traditional phishing detection often overlooks psychological manipulation. This study investigates using Large Language Model (LLM) In-Context Learning (ICL) for fine-grained classification of phishing emails based on a taxonomy of 40 manipulation techniques. Using few-shot examples with GPT-4o-mini on real-world French phishing emails (SignalSpam), we evaluated performance against a human-annotated test set (100 emails). The approach effectively identifies prevalent techniques (e.g., Baiting, …

This https://arxiv.org/abs/2505.21863 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCV_…

GETReason: Enhancing Image Context Extraction through Hierarchical Multi-Agent Reasoning
Publicly significant images from events hold valuable contextual information, crucial for journalism and education. However, existing methods often struggle to extract this relevance accurately. To address this, we introduce GETReason (Geospatial Event Temporal Reasoning), a framework that moves beyond surface-level image descriptions to infer deeper contextual meaning. We propose that extracting global event, temporal, and geospatial information enhances understanding of an image's significanc…

A Large-Scale Evolvable Dataset for Model Context Protocol Ecosystem and Security Analysis
Zhiwei Lin, Bonan Ruan, Jiahao Liu, Weibo Zhao
https://arxiv.org/abs/2506.23474

A Large-Scale Evolvable Dataset for Model Context Protocol Ecosystem and Security Analysis
The Model Context Protocol (MCP) has recently emerged as a standardized interface for connecting language models with external tools and data. As the ecosystem rapidly expands, the lack of a structured, comprehensive view of existing MCP artifacts presents challenges for research. To bridge this gap, we introduce MCPCorpus, a large-scale dataset containing around 14K MCP servers and 300 MCP clients. Each artifact is annotated with 20+ normalized attributes capturing its identity, interface conf…

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…

From Long Videos to Engaging Clips: A Human-Inspired Video Editing Framework with Multimodal Narrative Understanding
Xiangfeng Wang, Xiao Li, Yadong Wei, Xueyu Song, Yang Song, Xiaoqiang Xia, Fangrui Zeng, Zaiyi Chen, Liu Liu, Gu Xu, Tong Xu
https://arxiv.org/abs/2507.02790

From Long Videos to Engaging Clips: A Human-Inspired Video Editing Framework with Multimodal Narrative Understanding
The rapid growth of online video content, especially on short video platforms, has created a growing demand for efficient video editing techniques that can condense long-form videos into concise and engaging clips. Existing automatic editing methods predominantly rely on textual cues from ASR transcripts and end-to-end segment selection, often neglecting the rich visual context and leading to incoherent outputs. In this paper, we propose a human-inspired automatic video editing framework (HIVE)…