Tootfinder

I want to push back on the idea in the world of tech work that a PIP (performance improvement plan) is about getting rid of someone, that they're not intended to be survivable.
This is completely false. (I'm sure there's instances of it, of course, but the mode and vast majority are, in fact about performance improvement. Sometimes they're shadow layoffs, but that is cruel callous behavior that not everyone will exhibit.)
Now _most people do not survive the PIP process_. This is to be expected: if someone is in fact not performing, and more gentle remedies haven't worked, it's not looking good.
But here's where I get a bit spicy: most performance problems are constitutional problems with management and management style, not individual performance problems. However, since managers are as a class 'in power' somewhat, the individual contributor takes the fall for this structurally.
The intent of a PIP is not to get rid of people. It's to right performance.
However, as a system, PIPs do largely get rid of people who are constitutionally misaligned with management. Even when it's a management problem (and it usually is)

Subtitled Media Adaptations for People with Aphasia: Ongoing Accessibility Barriers and Emerging Design Practices
Zihao You, Michael Crabb
https://arxiv.org/abs/2506.21201

Subtitled Media Adaptations for People with Aphasia: Ongoing Accessibility Barriers and Emerging Design Practices
The consumption of subtitles via TVs, laptops and smartphones has the potential to marginalize people based on their complex accessibility needs. The current one-size-fits-all approach to this accessibility aid is no longer fit for purpose and work is required to look at how it can be adapted to be personalised for individual users based on individual context, content, and consumption habits. People with Aphasia, for example, encounter significant challenges in understanding subtitle texts. W…

Heterogeneous Risk Management Using a Multi-Agent Framework for Supply Chain Disruption Response
Mingjie Bi, Juan-Alberto Estrada-Garcia, Dawn M. Tilbury, Siqian Shen, Kira Barton
https://arxiv.org/abs/2507.19049

Heterogeneous Risk Management Using a Multi-Agent Framework for Supply Chain Disruption Response
In the highly complex and stochastic global, supply chain environments, local enterprise agents seek distributed and dynamic strategies for agile responses to disruptions. Existing literature explores both centralized and distributed approaches, while most work neglects temporal dynamics and the heterogeneity of the risk management of individual agents. To address this gap, this letter presents a heterogeneous risk management mechanism to incorporate uncertainties and risk attitudes into agent …

Aggregated Individual Reporting for Post-Deployment Evaluation
Jessica Dai, Inioluwa Deborah Raji, Benjamin Recht, Irene Y. Chen
https://arxiv.org/abs/2506.18133

Aggregated Individual Reporting for Post-Deployment Evaluation
The need for developing model evaluations beyond static benchmarking, especially in the post-deployment phase, is now well-understood. At the same time, concerns about the concentration of power in deployed AI systems have sparked a keen interest in 'democratic' or 'public' AI. In this work, we bring these two ideas together by proposing mechanisms for aggregated individual reporting (AIR), a framework for post-deployment evaluation that relies on individual reports from the public. An AIR mech…

Consistency and Central Limit Results for the Maximum Likelihood Estimator in the Admixture Model
Carola Sophia Heinzel
https://arxiv.org/abs/2507.19564 https://

Consistency and Central Limit Results for the Maximum Likelihood Estimator in the Admixture Model
In the Admixture Model, the probability of an individual having a certain number of alleles at a specific marker depends on the allele frequencies in $K$ ancestral populations and the fraction of the individual's genome originating from these ancestral populations. This study investigates consistency and central limit results of maximum likelihood estimators (MLEs) for the ancestry and the allele frequencies in the Admixture Model, complimenting previous work by \cite{pfaff2004information, pf…

Yue-Sai Kan is a Chinese-American television host, producer, author, entrepreneur and humanitarian. Renowned for her work in bridging the gap between China and the United States, she has been nicknamed "The Oprah of China". People, The Observer and ABS News have called her "the most famous woman in China".

"Why Antidepressants Work Better for Some"
Key Facts:
Immune Pathways: Toll-like receptor and NF-κB pathways were consistently altered between responders and non-responders.
Neural Mechanisms: Signal transduction and GABAergic synapse pathways showed consistent changes with fluoxetine treatment.
Heterogeneity Noted: Patterns of gene expression varied across tissues, models, and individuals, emphasizing the need for larger, more targeted studies.
Paper: Sou…

Gene expression signatures of response to fluoxetine treatment: systematic review and meta-analyses - Molecular Psychiatry
Genomic (and other ‘omic) data have provided valuable insights on the pharmacological signatures of antidepressant response, but results from individual studies are largely heterogeneous. In this work, we synthesized gene expression data for fluoxetine treatment in both human patients and rodent models, to better understand biological pathways affected by treatment, as well as those that may distinguish clinical or behavioral response. Following the PRISMA guidelines, we searched the Gene Exp…

"Despite good-faith efforts by DSI [dense street imagery] providers to protect individual privacy through blurring faces and license plates, these measures fail to address broader privacy concerns. In this work, we find that increased data density and advancements in artificial intelligence enable harmful group membership inferences from supposedly anonymized data."
via @…

Privacy of Groups in Dense Street Imagery
Spatially and temporally dense street imagery (DSI) datasets have grown unbounded. In 2024, individual companies possessed around 3 trillion unique images of public streets. DSI data streams are only set to grow as companies like Lyft and Waymo use DSI to train autonomous vehicle algorithms and analyze collisions. Academic researchers leverage DSI to explore novel approaches to urban analysis. Despite good-faith efforts by DSI providers to protect individual privacy through blurring faces and l…

Reinforcement Learning Increases Wind Farm Power Production by Enabling Closed-Loop Collaborative Control
Andrew Mole, Max Weissenbacher, Georgios Rigas, Sylvain Laizet
https://arxiv.org/abs/2506.20554

Reinforcement Learning Increases Wind Farm Power Production by Enabling Closed-Loop Collaborative Control
Traditional wind farm control operates each turbine independently to maximize individual power output. However, coordinated wake steering across the entire farm can substantially increase the combined wind farm energy production. Although dynamic closed-loop control has proven effective in flow control applications, wind farm optimization has relied primarily on static, low-fidelity simulators that ignore critical turbulent flow dynamics. In this work, we present the first reinforcement learnin…

Spin-Electric Control of Individual Molecules on Surfaces
Paul Greule, Wantong Huang, M\'at\'e Stark, Kwan Ho Au-Yeung, Johannes Schwenk, Jose Reina-G\'alvez, Christoph S\"urgers, Wolfgang Wernsdorfer, Christoph Wolf, Philip Willke
https://arxiv.org/abs/2507.13699

Spin-Electric Control of Individual Molecules on Surfaces
Individual magnetic molecules are promising building blocks for quantum technologies because of their chemical tunability, nanoscale dimensions, and ability to self-assemble into ordered arrays. However, harnessing their properties in quantum information processing requires precise local control of their spin properties. In this work, we present spin-electric coupling (SEC) for two molecular spin systems, iron phthalocyanine (FePc) and Fe-FePc complexes, adsorbed on a surface. We use electron s…

Balancing utility and cost in dynamic treatment regimes
Kai Chen, Zhang Yuqian
https://arxiv.org/abs/2507.17360 https://arxiv.org/pdf/2507.17360

Balancing utility and cost in dynamic treatment regimes
Dynamic treatment regimes (DTRs) are personalized, adaptive strategies designed to guide the sequential allocation of treatments based on individual characteristics over time. Before each treatment assignment, covariate information is collected to refine treatment decisions and enhance their effectiveness. The more information we gather, the more precise our decisions can be. However, this also leads to higher costs during the data collection phase. In this work, we propose a balanced Q-learnin…

Can GRB Empirical Correlations Be Used for Population Studies?
Emre S. Yorgancioglu, Yun-Fei Du, Shu-Xu Yi, Shuang-Nan Zhang
https://arxiv.org/abs/2507.16192

Can GRB Empirical Correlations Be Used for Population Studies?
Only a small fraction of Gamma-ray bursts (GRBs) have independent redshift measurements, which are essential for understanding their intrinsic properties. For this reason, empirical correlations of GRBs have often been touted as useful distance indicators, for both individual GRBs as well as population studies. Building upon our previous work, we test the ability of the Yonetoku, 3D Dainotti, and the L-T-E correlation to adequately constrain the GRB rate, $Ψ_{GRB}$. Our analysis demonstrates t…

Stark Tuning and Charge State Control in Individual Telecom C-Band Quantum Dots
N. J. Martin, A. J. Brash, A. Tomlinson, E. M. Sala, E. O. Mills, C. L. Phillips, R. Dost, L. Hallacy, P. Millington-Hotze, D. Hallett, K. A. O'Flaherty, J. Heffernan, M. S. Skolnick, A. M Fox, L. R. Wilson
https://arxiv.org/abs/2506.07951…

Stark Tuning and Charge State Control in Individual Telecom C-Band Quantum Dots
Telecom-wavelength quantum dots (QDs) are emerging as a promising solution for generating deterministic single-photons compatible with existing fiber-optic infrastructure. Emission in the low-loss C-band minimizes transmission losses, making them ideal for long-distance quantum communication. In this work, we present the first demonstration of both Stark tuning and charge state control of individual InAs/InP QDs operating within the telecom C-band. These QDs are grown by droplet epitaxy and emb…

Exact static linear response of excited states from ensemble density functional theory
Lucien Dupuy, Emmanuel Fromager
https://arxiv.org/abs/2506.16363 htt…

Exact static linear response of excited states from ensemble density functional theory
Following a recent work [E. Fromager, J. Phys. Chem. A 2025, 129, 4, 1143-1155] on the ensemble density functional theory (DFT) of excited electronic energy levels, we derive in this paper the ensuing static linear response theory, thus allowing for an in-principle exact evaluation of excited-state density-density linear response functions in a completely frequency-independent setting. Once individual-state components of the inverse ensemble linear response function have been introduced, a work…

The proper way to do this for a blind student would surely be some kind of physical manipulatives, not verbal descriptions. The thing is, I don’t have any blind students currently, and if I did, we’d work on individual accommodation and assistance.
With this alt text, I’m just trying to get •something• in there to be at least minimally accessible: head start on those accommodation, something helpful if I ever share this online, etc. If there’s any way for text to convey the spatial relationships, that would be better than the text I have.

ObjectGS: Object-aware Scene Reconstruction and Scene Understanding via Gaussian Splatting
Ruijie Zhu, Mulin Yu, Linning Xu, Lihan Jiang, Yixuan Li, Tianzhu Zhang, Jiangmiao Pang, Bo Dai
https://arxiv.org/abs/2507.15454

ObjectGS: Object-aware Scene Reconstruction and Scene Understanding via Gaussian Splatting
3D Gaussian Splatting is renowned for its high-fidelity reconstructions and real-time novel view synthesis, yet its lack of semantic understanding limits object-level perception. In this work, we propose ObjectGS, an object-aware framework that unifies 3D scene reconstruction with semantic understanding. Instead of treating the scene as a unified whole, ObjectGS models individual objects as local anchors that generate neural Gaussians and share object IDs, enabling precise object-level reconstr…

Choreographic Quick Changes: First-Class Location (Set) Polymorphism
Ashley Samuelson, Andrew K. Hirsch, Ethan Cecchetti
https://arxiv.org/abs/2506.10913 h…

Choreographic Quick Changes: First-Class Location (Set) Polymorphism
Choreographic programming is a promising new paradigm for programming concurrent systems where a developer writes a single centralized program that compiles to individual programs for each node. Existing choreographic languages, however, lack critical features integral to modern systems, like the ability of one node to dynamically compute who should perform a computation and send that decision to others. This work addresses this gap with $λ_{QC}$, the first typed choreographic language with \e…

Feature Intensity Mapping: Polycyclic Aromatic Hydrocarbon Emission from All Galaxies Across Cosmic Time
Yun-Ting Cheng, Brandon S. Hensley, Thomas S. -Y. Lai
https://arxiv.org/abs/2506.13863

Feature Intensity Mapping: Polycyclic Aromatic Hydrocarbon Emission from All Galaxies Across Cosmic Time
Line intensity mapping (LIM) is an emerging technique for probing the aggregate emission of a spectral line from all sources, without requiring individual detections. Through the wavelength-redshift relation, one can map the line-of-sight evolution of the line emission that traces the underlying large-scale structure in a spectral-imaging survey. In this work, we present a new technique -- feature intensity mapping -- as an extension of the LIM formalism to map broad spectral features in 3D, ra…

In-Home Social Robots Design for Cognitive Stimulation Therapy in Dementia Care
Emmanuel Akinrintoyo, Nicole Salomons
https://arxiv.org/abs/2507.13578 http…

In-Home Social Robots Design for Cognitive Stimulation Therapy in Dementia Care
Individual cognitive stimulation therapy (iCST) is a non-pharmacological intervention for improving the cognition and quality of life of persons with dementia (PwDs); however, its effectiveness is limited by low adherence to delivery by their family members. In this work, we present the user-centered design and evaluation of a novel socially assistive robotic system to provide iCST therapy to PwDs in their homes for long-term use. We consulted with 16 dementia caregivers and professionals. Thro…

Shifting from Ranking to Set Selection for Retrieval Augmented Generation
Dahyun Lee, Yongrae Jo, Haeju Park, Moontae Lee
https://arxiv.org/abs/2507.06838 …

Shifting from Ranking to Set Selection for Retrieval Augmented Generation
Retrieval in Retrieval-Augmented Generation(RAG) must ensure that retrieved passages are not only individually relevant but also collectively form a comprehensive set. Existing approaches primarily rerank top-k passages based on their individual relevance, often failing to meet the information needs of complex queries in multi-hop question answering. In this work, we propose a set-wise passage selection approach and introduce SETR, which explicitly identifies the information requirements of a q…

Concept-Based Mechanistic Interpretability Using Structured Knowledge Graphs
Sofiia Chorna, Kateryna Tarelkina, Elo\"ise Berthier, Gianni Franchi
https://arxiv.org/abs/2507.05810

Concept-Based Mechanistic Interpretability Using Structured Knowledge Graphs
While concept-based interpretability methods have traditionally focused on local explanations of neural network predictions, we propose a novel framework and interactive tool that extends these methods into the domain of mechanistic interpretability. Our approach enables a global dissection of model behavior by analyzing how high-level semantic attributes (referred to as concepts) emerge, interact, and propagate through internal model components. Unlike prior work that isolates individual neuro…

WATCH: 49ers' Trent Williams pancakes teammate in return to practice field following ankle injury

https://www.cbssports.com/nfl/news/watch-4

Integer-Clustering Optimization of Hydrogen and Battery EV Fleets Considering DERs
Sijia Geng, Thomas Lee, Dharik Mallapragada, Audun Botterud
https://arxiv.org/abs/2506.09388

Integer-Clustering Optimization of Hydrogen and Battery EV Fleets Considering DERs
Electrified transportation leads to a tighter integration between transportation and energy distribution systems. In this work, we develop scalable optimization models to co-design hydrogen and battery electric vehicle (EV) fleets, distributed energy resources, and fast-charging and hydrogen-fueling infrastructure to efficiently meet transportation demands. A novel integer-clustering formulation is used for optimizing fleet-level EV operation while maintaining accurate individual vehicle dispat…

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

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

This https://arxiv.org/abs/2505.24739 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_ees…

Contrast-Invariant Self-supervised Segmentation for Quantitative Placental MRI
Accurate placental segmentation is essential for quantitative analysis of the placenta. However, this task is particularly challenging in T2*-weighted placental imaging due to: (1) weak and inconsistent boundary contrast across individual echoes; (2) the absence of manual ground truth annotations for all echo times; and (3) motion artifacts across echoes caused by fetal and maternal movement. In this work, we propose a contrast-augmented segmentation framework that leverages complementary infor…

An Accurate and Efficient Vulnerability Propagation Analysis Framework
Bonan Ruan, Zhiwei Lin, Jiahao Liu, Chuqi Zhang, Kaihang Ji, Zhenkai Liang
https://arxiv.org/abs/2506.01342 …

An Accurate and Efficient Vulnerability Propagation Analysis Framework
Identifying the impact scope and scale is critical for software supply chain vulnerability assessment. However, existing studies face substantial limitations. First, prior studies either work at coarse package-level granularity, producing many false positives, or fail to accomplish whole-ecosystem vulnerability propagation analysis. Second, although vulnerability assessment indicators like CVSS characterize individual vulnerabilities, no metric exists to specifically quantify the dynamic impact…

CodeEdu: A Multi-Agent Collaborative Platform for Personalized Coding Education
Jianing Zhao, Peng Gao, Jiannong Cao, Zhiyuan Wen, Chen Chen, Jianing Yin, Ruosong Yang, Bo Yuan
https://arxiv.org/abs/2507.13814

CodeEdu: A Multi-Agent Collaborative Platform for Personalized Coding Education
Large Language Models (LLMs) have demonstrated considerable potential in improving coding education by providing support for code writing, explanation, and debugging. However, existing LLM-based approaches generally fail to assess students' abilities, design learning plans, provide personalized material aligned with individual learning goals, and enable interactive learning. Current work mostly uses single LLM agents, which limits their ability to understand complex code repositories and schedu…

Understanding Community-Level Blocklists in Decentralized Social Media
Owen Xingjian Zhang, Sohyeon Hwang, Yuhan Liu, Manoel Horta Ribeiro, Andr\'es Monroy-Hern\'andez
https://arxiv.org/abs/2506.05522

Understanding Community-Level Blocklists in Decentralized Social Media
Community-level blocklists are key to content moderation practices in decentralized social media. These blocklists enable moderators to prevent other communities, such as those acting in bad faith, from interacting with their own -- and, if shared publicly, warn others about communities worth blocking. Prior work has examined blocklists in centralized social media, noting their potential for collective moderation outcomes, but has focused on blocklists as individual-level tools. To understand h…

This https://arxiv.org/abs/2502.08166 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCY_…

From Individual Experience to Collective Evidence: A Reporting-Based Framework for Identifying Systemic Harms
When an individual reports a negative interaction with some system, how can their personal experience be contextualized within broader patterns of system behavior? We study the reporting database problem, where individual reports of adverse events arrive sequentially, and are aggregated over time. In this work, our goal is to identify whether there are subgroups--defined by any combination of relevant features--that are disproportionately likely to experience harmful interactions with the syste…

Correlation Functions and Chaotic Behavior of the SYK Chain Model in Pure States
Seyyed M. H. Halataei
https://arxiv.org/abs/2506.01100 https://

Correlation Functions and Chaotic Behavior of the SYK Chain Model in Pure States
Recent investigations of Rényi entanglement entropy in the SYK chain of Majorana fermions have indicated that the model exhibits slow thermalization when initialized in certain states. The extent to which the heavy modes -- believed to underlie this behavior -- affect other aspects of the model remains an open question. In this work, I study thermalization and scrambling of information in individual energy eigenstates of the SYK chain using exact diagonalization. I show that two-point correlat…

A Simple Algorithm for Trimmed Multipoint Evaluation
Nick Fischer, Melvin Kallmayer, Leo Wennmann
https://arxiv.org/abs/2507.00196 https://

A Simple Algorithm for Trimmed Multipoint Evaluation
Evaluating a polynomial on a set of points is a fundamental task in computer algebra. In this work, we revisit a particular variant called trimmed multipoint evaluation: given an $n$-variate polynomial with bounded individual degree $d$ and total degree $D$, the goal is to evaluate it on a natural class of input points. This problem arises as a key subroutine in recent algorithmic results [Dinur; SODA '21], [Dell, Haak, Kallmayer, Wennmann; SODA '25]. It is known that trimmed multipoint evaluat…

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

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

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…

Entanglement structure for finite system under dual-unitary dynamics
Gaurav Rudra Malik, Rohit Kumar Shukla, Sudhanva Joshi, S. Aravinda, Sunil Kumar Mishra
https://arxiv.org/abs/2506.09904

Entanglement structure for finite system under dual-unitary dynamics
The dynamics of quantum many-body systems in the chaotic regime are of particular interest due to the associated phenomena of information scrambling and entanglement generation within the system. While these systems are typically intractable using traditional numerical methods, an effective framework can be implemented based on dual-unitary circuits which have emerged as a minimal model for maximally chaotic dynamics. In this work, we investigate how individual two-body operators influence the …

This https://arxiv.org/abs/2506.00168 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qbi…

A novel sensitivity analysis method for agent-based models stratifies \emph{in-silico} tumor spheroid simulations
Agent-based models (ABMs) are widely used in biology to understand how individual actions scale into emergent population behavior. Modelers employ sensitivity analysis (SA) algorithms to quantify input parameters' impact on model outputs, however, it is hard to perform SA for ABMs due to their computational and complex nature. In this work, we develop the \textbf{S}imulate, \textbf{S}ummarize, \textbf{R}educe, \textbf{C}luster, and \textbf{A}nalyze (SSRCA) methodology, a machine-learning based …

exoatlas: friendly Python code for exoplanet populations
Zach K. Berta-Thompson, Patcharapol Wachiraphan, Autumn Stephens, Mirielle Caradonna, Catriona Murray, Valerie Arriero, Jackson Avery, Girish M. Duvvuri, Sebastian Pineda
https://arxiv.org/abs/2507.02210

exoatlas: friendly Python code for exoplanet populations
Planets are complicated. Understanding how they work requires connecting individual objects to the context of broader populations. Exoplanets are easier to picture next to their closest Solar System archetypes, and planets in the Solar System are richer when seen alongside a growing community of known exoplanets in the Milky Way. The `exoatlas` toolkit provides a friendly Python interface for retrieving and working with populations of planets, aiming to simplify the process of placing worlds in…

Offline Reinforcement Learning for Mobility Robustness Optimization
Pegah Alizadeh, Anastasios Giovanidis, Pradeepa Ramachandra, Vasileios Koutsoukis, Osama Arouk
https://arxiv.org/abs/2506.22793

Offline Reinforcement Learning for Mobility Robustness Optimization
In this work we revisit the Mobility Robustness Optimisation (MRO) algorithm and study the possibility of learning the optimal Cell Individual Offset tuning using offline Reinforcement Learning. Such methods make use of collected offline datasets to learn the optimal policy, without further exploration. We adapt and apply a sequence-based method called Decision Transformers as well as a value-based method called Conservative Q-Learning to learn the optimal policy for the same target reward as t…

A statistical theory for polymer elasticity: from molecular kinematics to continuum behavior
Lin Zhan, Siyu Wang, Rui Xiao, Shaoxing Qu, Paul Steinmann
https://arxiv.org/abs/2507.02361

A statistical theory for polymer elasticity: from molecular kinematics to continuum behavior
Predicting the macroscopic mechanical behavior of polymeric materials from the micro-structural features has remained a challenge for decades. Existing theoretical models often fail to accurately capture the experimental data, due to non-physical assumptions that link the molecule kinematics with the macroscopic deformation. In this work, we construct a novel Hamiltonian for chain segments enabling a unified statistical description of both individual macromolecular chains and continuum polymer …

Optimizing information transmission in the canonical Wnt pathway
Olivier Witteveen, Samuel J. Rosen, Ryan S. Lach, Maxwell Z. Wilson, Marianne Bauer
https://arxiv.org/abs/2506.22633

Optimizing information transmission in the canonical Wnt pathway
Populations of cells regulate gene expression in response to external signals, but their ability to make reliable collective decisions is limited by both intrinsic noise in molecular signaling and variability between individual cells. In this work, we use optogenetic control of the canonical Wnt pathway as an example to study how reliably information about an external signal is transmitted to a population of cells, and determine an optimal encoding strategy to maximize information transmission …

Can Orbital Decay of Accreting Binary Pulsars Probe Dark Matter?
Arvind Kumar Mishra
https://arxiv.org/abs/2507.06178 https://arxiv.o…

Can Orbital Decay of Accreting Binary Pulsars Probe Dark Matter?
The merger of binary pulsars in dark matter (DM)-rich environments can result in DM particle accretion, leading to an increase in the individual pulsar masses. In this work, we investigate the effects of DM accretion on the change in orbital period rate of binary pulsars. Our analysis reveals that while DM accretion increases the system's mass, it may also modify the orbital evolution by enhancing the orbital decay rate. By comparing our results with existing binary pulsar data near Earth's loc…

Frame-Level Real-Time Assessment of Stroke Rehabilitation Exercises from Video-Level Labeled Data: Task-Specific vs. Foundation Models
Gon\c{c}alo Mesquita, Ana Rita C\'oias, Artur Dubrawski, Alexandre Bernardino
https://arxiv.org/abs/2506.03752

Frame-Level Real-Time Assessment of Stroke Rehabilitation Exercises from Video-Level Labeled Data: Task-Specific vs. Foundation Models
The growing demands of stroke rehabilitation have increased the need for solutions to support autonomous exercising. Virtual coaches can provide real-time exercise feedback from video data, helping patients improve motor function and keep engagement. However, training real-time motion analysis systems demands frame-level annotations, which are time-consuming and costly to obtain. In this work, we present a framework that learns to classify individual frames from video-level annotations for real…

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

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

Berry Phase Effects of Nuclei in Chemical Reaction Dynamics
Xingyu Zhang, Jinke Yu, Qingyong Meng
https://arxiv.org/abs/2507.05672 https://

Berry Phase Effects of Nuclei in Chemical Reaction Dynamics
In calculations on quantum state-resolved dynamics of a chemical reaction, reactants are usually prepared in separated eigenstates of individual fragments, and their direct-product is then evolved in time. In this work, we focus on the essence in separating them and the Berry phase effects of the nuclear wave function. By the present theory, mechanism of inter/intramolecular energy redistribution is also proposed to deeply understand reactive dynamics with multirovibrational states. To demonstr…

A novel sensitivity analysis method for agent-based models stratifies \emph{in-silico} tumor spheroid simulations
Edward H. Rohr, John T. Nardini
https://arxiv.org/abs/2506.00168 …

A novel sensitivity analysis method for agent-based models stratifies \emph{in-silico} tumor spheroid simulations
Agent-based models (ABMs) are widely used in biology to understand how individual actions scale into emergent population behavior. Modelers employ sensitivity analysis (SA) algorithms to quantify input parameters' impact on model outputs, however, it is hard to perform SA for ABMs due to their computational and complex nature. In this work, we develop the \textbf{S}imulate, \textbf{S}ummarize, \textbf{R}educe, \textbf{C}luster, and \textbf{A}nalyze (SSRCA) methodology, a machine-learning based …

CORA: Coalitional Rational Advantage Decomposition for Multi-Agent Policy Gradients
Mengda Ji, Genjiu Xu, Liying Wang
https://arxiv.org/abs/2506.04265 http…

CORA: Coalitional Rational Advantage Decomposition for Multi-Agent Policy Gradients
This work focuses on the credit assignment problem in cooperative multi-agent reinforcement learning (MARL). Sharing the global advantage among agents often leads to suboptimal policy updates as it fails to account for the distinct contributions of agents. Although numerous methods consider global or individual contributions for credit assignment, a detailed analysis at the coalition level remains lacking in many approaches. This work analyzes the over-updating problem during multi-agent policy…

Judgment as Coordination: A Joint Systems View of Visualization Design Practice
Paul C. Parsons, Arran Ridley
https://arxiv.org/abs/2507.01209 https://

Judgment as Coordination: A Joint Systems View of Visualization Design Practice
Professional visualization design has become an increasingly important area of inquiry, yet much of the field's discourse remains anchored in researcher-centered contexts. Studies of design practice often focus on individual designers' decisions and reflections, offering limited insight into the collaborative and systemic dimensions of professional work. In this paper, we propose a systems-level reframing of design judgment grounded in the coordination and adaptation that sustain progress amid …

A network of parametrically driven silicon nitride mechanical membranes
Luis Mestre, Suyash Singh, Gabriel Margiani, Letizia Catalini, Alexander Eichler, Vincent Dumont
https://arxiv.org/abs/2506.00850

A network of parametrically driven silicon nitride mechanical membranes
Networks of nonlinear resonators offer a promising platform for analog computing and the emulation of complex systems. However, realizing such networks remains challenging, as it requires resonators with high quality factors, individual frequency tunability, and strong inter-resonator coupling. In this work, we present a system that meets all these criteria. Our system is based on metallized silicon nitride membranes that are coupled via their common substrate and controlled capacitively via el…

Contrast-Invariant Self-supervised Segmentation for Quantitative Placental MRI
Xinliu Zhong, Ruiying Liu, Emily S. Nichols, Xuzhe Zhang, Andrew F. Laine, Emma G. Duerden, Yun Wang
https://arxiv.org/abs/2505.24739

Contrast-Invariant Self-supervised Segmentation for Quantitative Placental MRI
Accurate placental segmentation is essential for quantitative analysis of the placenta. However, this task is particularly challenging in T2*-weighted placental imaging due to: (1) weak and inconsistent boundary contrast across individual echoes; (2) the absence of manual ground truth annotations for all echo times; and (3) motion artifacts across echoes caused by fetal and maternal movement. In this work, we propose a contrast-augmented segmentation framework that leverages complementary infor…

Localisation and host galaxy identification of new Fast Radio Bursts with MeerKA
In\'es Pastor-Marazuela, Alexa C. Gordon, Ben Stappers, Ilya S. Khrykin, Nicolas Tejos, Kaustubh Rajwade, Manisha Caleb, Mayuresh P. Surnis, Laura N. Driessen, Sunil Simha, Jun Tian, J. Xavier Prochaska, Ewan Barr, Wen-Fai Fong, Fabian Jankowski, Lordrick Kahinga, Charles D. Kilpatrick, Michael Kramer, Lluis Mas-Ribas

Localisation and host galaxy identification of new Fast Radio Bursts with MeerKA
Accurately localising fast radio bursts (FRBs) is essential for understanding their birth environments and for their use as cosmological probes. Recent advances in radio interferometry, particularly with MeerKAT, have enabled the localisation of individual bursts with arcsecond precision. In this work, we present the localisation of 15 apparently non-repeating FRBs detected with MeerKAT. Two of the FRBs, discovered in 2022, were localised in 8 second images from the projects which MeerTRAP was …

Diffusion of Responsibility in Collective Decision Making
Pavel Naumov, Jia Tao
https://arxiv.org/abs/2506.07935 https://arxiv.org/pd…

Diffusion of Responsibility in Collective Decision Making
The term "diffusion of responsibility'' refers to situations in which multiple agents share responsibility for an outcome, obscuring individual accountability. This paper examines this frequently undesirable phenomenon in the context of collective decision-making mechanisms. The work shows that if a decision is made by two agents, then the only way to avoid diffusion of responsibility is for one agent to act as a "dictator'', making the decision unilaterally. In scenarios with more than two a…

Relaxation pathways and emergence of domains in square artificial spin ice
Matteo Menniti, Na\"emi Leo, Pedro Villalba-Gonz\'alez, Matteo Pancaldi, and Paolo Vavassori
https://arxiv.org/abs/2505.24041

Relaxation pathways and emergence of domains in square artificial spin ice
Multi-domain states of square artificial spin ice show a range of different morphologies ranging from simple stripe-like domains to more organically shaped coral domains. To model the relevant dynamics leading to the emergence of such diverse domain structures, simplified descriptions of the switching behavior of individual nanomagnets are necessary. In this work, we employ kinetic Monte Carlo simulations of the demagnetization of square artificial spin ice toward its ground state, and compare …