Tootfinder

Multi-State Tracker: Enhancing Efficient Object Tracking via Multi-State Specialization and Interaction
Shilei Wang, Gong Cheng, Pujian Lai, Dong Gao, Junwei Han
https://arxiv.org/abs/2508.11531

Multi-State Tracker: Enhancing Efficient Object Tracking via Multi-State Specialization and Interaction
Efficient trackers achieve faster runtime by reducing computational complexity and model parameters. However, this efficiency often compromises the expense of weakened feature representation capacity, thus limiting their ability to accurately capture target states using single-layer features. To overcome this limitation, we propose Multi-State Tracker (MST), which utilizes highly lightweight state-specific enhancement (SSE) to perform specialized enhancement on multi-state features produced by …

Exploring Expert Specialization through Unsupervised Training in Sparse Mixture of Experts
Strahinja Nikolic, Ilker Oguz, Demetri Psaltis
https://arxiv.org/abs/2509.10025 https:…

Exploring Expert Specialization through Unsupervised Training in Sparse Mixture of Experts
Understanding the internal organization of neural networks remains a fundamental challenge in deep learning interpretability. We address this challenge by exploring a novel Sparse Mixture of Experts Variational Autoencoder (SMoE-VAE) architecture. We test our model on the QuickDraw dataset, comparing unsupervised expert routing against a supervised baseline guided by ground-truth labels. Surprisingly, we find that unsupervised routing consistently achieves superior reconstruction performance. T…

CARGO: A Framework for Confidence-Aware Routing of Large Language Models
Amine Barrak, Yosr Fourati, Michael Olchawa, Emna Ksontini, Khalil Zoghlami
https://arxiv.org/abs/2509.14899

CARGO: A Framework for Confidence-Aware Routing of Large Language Models
As large language models (LLMs) proliferate in scale, specialization, and latency profiles, the challenge of routing user prompts to the most appropriate model has become increasingly critical for balancing performance and cost. We introduce CARGO (Category-Aware Routing with Gap-based Optimization), a lightweight, confidence-aware framework for dynamic LLM selection. CARGO employs a single embedding-based regressor trained on LLM-judged pairwise comparisons to predict model performance, with a…

When should young athletes specialize in a sport? This story may help you decide https://www.nytimes.com/athletic/6616450/2025/09/11/youth-sports-specialization-parents-young-athletes/

"Bypassing" #specialization in #Rust or How I Learned to Stop Worrying and Love Function Pointers
https://

FLUID: Flow-Latent Unified Integration via Token Distillation for Expert Specialization in Multimodal Learning
Van Duc Cuong, Ta Dinh Tam, Tran Duc Chinh, Nguyen Thi Hanh
https://arxiv.org/abs/2508.07264

FLUID: Flow-Latent Unified Integration via Token Distillation for Expert Specialization in Multimodal Learning
Multimodal classification requires robust integration of visual and textual signals, yet common fusion strategies are brittle and vulnerable to modality-specific noise. In this paper, we present \textsc{FLUID}-Flow-Latent Unified Integration via Token Distillation for Expert Specialization, a principled token-level pipeline that improves cross-modal robustness and scalability. \textsc{FLUID} contributes three core elements: (1) \emph{Q-transforms}, learnable query tokens that distill and retain…

Assistant/Associate Professor of Church History
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Fuller Theological Seminary School of Mission and Theology Tenure-Track Faculty Series Position…
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Replaced article(s) found for cs.MA. https://arxiv.org/list/cs.MA/new
[1/1]:
- Predicting Multi-Agent Specialization via Task Parallelizability
Mieczkowski, Mon-Williams, Bramley, Lucas, Velez, Griffiths

Understanding and Leveraging the Expert Specialization of Context Faithfulness in Mixture-of-Experts LLMs
Jun Bai, Minghao Tong, Yang Liu, Zixia Jia, Zilong Zheng
https://arxiv.org/abs/2508.19594

Understanding and Leveraging the Expert Specialization of Context Faithfulness in Mixture-of-Experts LLMs
Context faithfulness is essential for reliable reasoning in context-dependent scenarios. However, large language models often struggle to ground their outputs in the provided context, resulting in irrelevant responses. Inspired by the emergent expert specialization observed in mixture-of-experts architectures, this work investigates whether certain experts exhibit specialization in context utilization, offering a potential pathway toward targeted optimization for improved context faithfulness. …

Trade-offs in Cross-Domain Generalization of Foundation Model Fine-Tuned for Biometric Applications
Tahar Chettaoui, Naser Damer, Fadi Boutros
https://arxiv.org/abs/2509.14921 h…

Trade-offs in Cross-Domain Generalization of Foundation Model Fine-Tuned for Biometric Applications
Foundation models such as CLIP have demonstrated exceptional zero- and few-shot transfer capabilities across diverse vision tasks. However, when fine-tuned for highly specialized biometric tasks, face recognition (FR), morphing attack detection (MAD), and presentation attack detection (PAD), these models may suffer from over-specialization. Thus, they may lose one of their foundational strengths, cross-domain generalization. In this work, we systematically quantify these trade-offs by evaluatin…

TENET: An Efficient Sparsity-Aware LUT-Centric Architecture for Ternary LLM Inference On Edge
Zhirui Huang, Rui Ma, Shijie Cao, Ran Shu, Ian Wang, Ting Cao, Chixiao Chen, Yongqiang Xiong
https://arxiv.org/abs/2509.13765

TENET: An Efficient Sparsity-Aware LUT-Centric Architecture for Ternary LLM Inference On Edge
Ternary quantization has emerged as a powerful technique for reducing both computational and memory footprint of large language models (LLM), enabling efficient real-time inference deployment without significantly compromising model accuracy. Conventional LLM inference platforms (e.g GPUs) cannot capitalize on its benefits, as they (i) lack native support for ternary arithmetic and memory specialization and (ii) remain severely under-utilized in low-batch, real-time scenarios. In this work, we …

Specialization, Complexity & Resilience in Supply Chains
Alessandro Ferrari, Lorenzo Pesaresi
https://arxiv.org/abs/2509.08981 https://arxiv.org/pdf/25…

Specialization, Complexity & Resilience in Supply Chains
Despite growing policy interest, the determinants of supply chain resilience are still not well understood. We propose a new theory of supply chain formation with compatibility frictions: only compatible inputs can be used in final good production. Intermediate producers choose the degree of specialization of their goods, trading off higher productivity against a lower share of compatible final producers. We model supply chains as complex production processes in which multiple complementary inp…

Quiver superconformal index and giant gravitons: asymptotics and expansions
Souradeep Purkayastha, Zishen Qu, Ali Zahabi
https://arxiv.org/abs/2509.12123 https://

Quiver superconformal index and giant gravitons: asymptotics and expansions
We study asymptotics of the $d=4$, $\mathcal{N}=1$ superconformal index for toric quiver gauge theories. Using graph-theoretic and algebraic factorization techniques, we obtain a cycle expansion for the large-$N$ index in terms of the $R$-charge-weighted adjacency matrix. Applying saddle-point techniques at the on-shell $R$-charges, we determine the asymptotic degeneracy in the univariate specialization for $\hat{A}_{m}$, and along the main diagonal for the bivariate index for $\mathcal{N}=4$ a…

(2015) "Visual" cortex responds to spoken language in blind children https://www.jneurosci.org/content/35/33/11674 Now what will the "visual" cortex of blind children do once trained with live imagery (camera views) encoded in sound by The vOICe?

“Visual” Cortex Responds to Spoken Language in Blind Children
Plasticity in the visual cortex of blind individuals provides a rare window into the mechanisms of cortical specialization. In the absence of visual input, occipital (“visual”) brain regions respond to sound and spoken language. Here, we examined the time course and developmental mechanism of this plasticity in blind children. Nineteen blind and 40 sighted children and adolescents (4–17 years old) listened to stories and two auditory control conditions (unfamiliar foreign speech, and musi…

Solomon-Terao polynomials and Castelnouvo-Mumford regularity of hyperplane arrangements
Takuro Abe
https://arxiv.org/abs/2509.10047 https://arxiv.org/pdf/2…

Solomon-Terao polynomials and Castelnouvo-Mumford regularity of hyperplane arrangements
The Solomon-Terao bi-polynomial was introduced by Solomon and Terao which degenerates to the characteristic polynomial of hyperplane arrangements. Also, it was proved recently that the other specialization of the Solomon-Terao bi-polynomial, we call the Solomon-Terao polynomial, coincides with the Poinraré polynomial of the regular nilpotent Hessenberg variety when the arrangement and the variety comes from the same lower ideal in the positive system. Moreover, there are recent developments wi…

On the colored Links--Gould polynomial
Stavros Garoufalidis, Matthew Harper, Rinat Kashaev, Ben-Michael Kohli, Emmanuel Wagner
https://arxiv.org/abs/2509.10911 https://

On the colored Links--Gould polynomial
We give a cabling formula for the Links--Gould polynomial of knots colored with a $4n$-dimensional irreducible representation of $\mathrm{U}^H_q\mathfrak{sl}(2|1)$ and identify them with the $V_n$-polynomial of knots for $n=2$. Using the cabling formula, we obtain genus bounds and a specialization to the Alexander polynomial for the colored Links--Gould polynomial that is independent of $n$, which implies corresponding properties of the $V_n$-polynomial for $n=2$ conjectured in previous wo…

Assistant/Associate Professor of Church History https://churchhistory.org/assistant-associate-professor-of-church-history/

Dirichlet-Prior Shaping: Guiding Expert Specialization in Upcycled MoEs
Leyla Mirvakhabova, Babak Ehteshami Bejnordi, Gaurav Kumar, Hanxue Liang, Wanru Zhao, Paul Whatmough
https://arxiv.org/abs/2510.01185

Dirichlet-Prior Shaping: Guiding Expert Specialization in Upcycled MoEs
Upcycling pre-trained dense models into sparse Mixture-of-Experts (MoEs) efficiently increases model capacity but often suffers from poor expert specialization due to naive weight replication. Our analysis reveals that upcycled MoEs, even with conventional regularization, exhibit low-confidence, weakly differentiated routing, hindering performance. We introduce Dirichlet-Prior Shaping Loss (DPSL), a novel router regularization technique that directly shapes routing probability distributions by …

Hybrid Game Control Envelope Synthesis
Aditi Kabra, Jonathan Laurent, Stefan Mitsch, Andr\'e Platzer
https://arxiv.org/abs/2508.05997 https://arxiv.org…

Hybrid Game Control Envelope Synthesis
Control problems for embedded systems like cars and trains can be modeled by two-player hybrid games. Control envelopes, which are families of safe control solutions, correspond to nondeterministic winning policies of hybrid games, where each deterministic specialization of the policy is a control solution. This paper synthesizes nondeterministic winning policies for hybrid games that are as permissive as possible. It introduces subvalue maps, a compositional representation of such policies tha…

Synchronization Dynamics of Heterogeneous, Collaborative Multi-Agent AI Systems
Chiranjit Mitra
https://arxiv.org/abs/2508.12314 https://arxiv.org/pdf/2508…

Synchronization Dynamics of Heterogeneous, Collaborative Multi-Agent AI Systems
We present a novel interdisciplinary framework that bridges synchronization theory and multi-agent AI systems by adapting the Kuramoto model to describe the collective dynamics of heterogeneous AI agents engaged in complex task execution. By representing AI agents as coupled oscillators with both phase and amplitude dynamics, our model captures essential aspects of agent specialization, influence, and communication within networked systems. We introduce an order parameter to quantify the degree…

Iridescent: A Framework Enabling Online System Implementation Specialization
Vaastav Anand, Deepak Garg, Antoine Kaufmann
https://arxiv.org/abs/2508.16690 https://

Iridescent: A Framework Enabling Online System Implementation Specialization
Specializing systems to specifics of the workload they serve and platform they are running on often significantly improves performance. However, specializing systems is difficult in practice because of compounding challenges: i) complexity for the developers to determine and implement optimal specialization; ii) inherent loss of generality of the resulting implementation, and iii) difficulty in identifying and implementing a single optimal specialized configuration for the messy reality of mode…

The Five Safes as a Privacy Context
James Bailie, Ruobin Gong
https://arxiv.org/abs/2510.05803 https://arxiv.org/pdf/2510.05803

The Five Safes as a Privacy Context
The Five Safes is a framework used by national statistical offices (NSO) for assessing and managing the disclosure risk of data sharing. This paper makes two points: Firstly, the Five Safes can be understood as a specialization of a broader concept $\unicode{x2013}$ contextual integrity $\unicode{x2013}$ to the situation of statistical dissemination by an NSO. We demonstrate this by mapping the five parameters of contextual integrity onto the five dimensions of the Five Safes. Secondly, the Fiv…

Quaternionic families of Heegner points and $p$-adic $L$-functions
Matteo Longo, Paola Magrone, Eduardo Rocha Walchek
https://arxiv.org/abs/2510.04306 https://

Quaternionic families of Heegner points and $p$-adic $L$-functions
Following up a previous article of the authors which studies the interpolation of certain anticyclotomic $p$-adic $L$-functions associated to quaternionic modular forms in a Hida family, we extend the work of F. Castella on the interpolation and specialization of big Heegner points to the quaternionic setting. We prove an explicit reciprocity law relating the big $p$-adic $L$-function to the big Heegner points in this quaternionic setting.

Towards Memory Specialization: A Case for Long-Term and Short-Term RAM
Peijing Li, Muhammad Shahir Abdurraman, Rachel Cleaveland, Sergey Legtchenko, Philip Levis, Ioan Stefanovici, Thierry Tambe, David Tennenhouse, Caroline Trippel
https://arxiv.org/abs/2508.02992

Towards Memory Specialization: A Case for Long-Term and Short-Term RAM
Both SRAM and DRAM have stopped scaling: there is no technical roadmap to reduce their cost (per byte/GB). As a result, memory now dominates system cost. This paper argues for a paradigm shift from today's simple memory hierarchy toward specialized memory architectures that exploit application-specific access patterns. Rather than relying solely on traditional off-chip DRAM and on-chip SRAM, we envisage memory systems equipped with additional types of memory whose performance trade-offs benefit…

Collaborative Medical Triage under Uncertainty: A Multi-Agent Dynamic Matching Approach
Hongyan Cheng, Chengzhang Yu, Yanshu Shi, Chiyue Wang, Cong Liu, Zhanpeng Jin
https://arxiv.org/abs/2507.22504

Collaborative Medical Triage under Uncertainty: A Multi-Agent Dynamic Matching Approach
The post-pandemic surge in healthcare demand, coupled with critical nursing shortages, has placed unprecedented pressure on emergency department triage systems, necessitating innovative AI-driven solutions. We present a multi-agent interactive intelligent system for medical triage that addresses three fundamental challenges in current AI-based triage systems: insufficient medical specialization leading to hallucination-induced misclassifications, heterogeneous department structures across healt…

Back to Bits: Extending Shannon's communication performance framework to computing
Max Hawkins, Richard Vuduc
https://arxiv.org/abs/2508.05621 https://…

Back to Bits: Extending Shannon's communication performance framework to computing
This work proposes a novel computing performance unit grounded in information theory. Modern computing systems are increasingly diverse, supporting low-precision formats, hardware specialization, and emerging paradigms such as analog, quantum, and reversible logic. Traditional metrics like floating-point operations (flops) no longer accurately capture this complexity. We frame computing as the transformation of information through a channel and define performance in terms of the mutual informat…

Exploration on Demand: From Algorithmic Control to User Empowerment
Edoardo Bianchi
https://arxiv.org/abs/2507.21884 https://arxiv.org/pdf/2507.21884

Exploration on Demand: From Algorithmic Control to User Empowerment
Recommender systems often struggle with over-specialization, which severely limits users' exposure to diverse content and creates filter bubbles that reduce serendipitous discovery. To address this fundamental limitation, this paper introduces an adaptive clustering framework with user-controlled exploration that effectively balances personalization and diversity in movie recommendations. Our approach leverages sentence-transformer embeddings to group items into semantically coherent clusters t…

The Social Cost of Intelligence: Emergence, Propagation, and Amplification of Stereotypical Bias in Multi-Agent Systems
Thi-Nhung Nguyen, Linhao Luo, Thuy-Trang Vu, Dinh Phung
https://arxiv.org/abs/2510.10943

The Social Cost of Intelligence: Emergence, Propagation, and Amplification of Stereotypical Bias in Multi-Agent Systems
Bias in large language models (LLMs) remains a persistent challenge, manifesting in stereotyping and unfair treatment across social groups. While prior research has primarily focused on individual models, the rise of multi-agent systems (MAS), where multiple LLMs collaborate and communicate, introduces new and largely unexplored dynamics in bias emergence and propagation. In this work, we present a comprehensive study of stereotypical bias in MAS, examining how internal specialization, underlyi…

UniShield: An Adaptive Multi-Agent Framework for Unified Forgery Image Detection and Localization
Qing Huang, Zhipei Xu, Xuanyu Zhang, Jian Zhang
https://arxiv.org/abs/2510.03161

UniShield: An Adaptive Multi-Agent Framework for Unified Forgery Image Detection and Localization
With the rapid advancements in image generation, synthetic images have become increasingly realistic, posing significant societal risks, such as misinformation and fraud. Forgery Image Detection and Localization (FIDL) thus emerges as essential for maintaining information integrity and societal security. Despite impressive performances by existing domain-specific detection methods, their practical applicability remains limited, primarily due to their narrow specialization, poor cross-domain gen…

Coh zeta functions for inert quadratic orders
Yifeng Huang
https://arxiv.org/abs/2507.21966 https://arxiv.org/pdf/2507.21966…

Coh zeta functions for inert quadratic orders
We study the Coh zeta function for a family of inert quadratic orders, which we conjecture to be given by $t$-deformed Bressoud $q$-series. This completes a trilogy connecting the zeta functions of ramified and split quadratic orders to the classical Andrews--Gordon and Bressoud identities, respectively. We provide strong evidence for this conjecture by deriving the first explicit formulas for the finitized Coh zeta function of the simplest order in the family, and for the $t=1$ specialization …

EnTao-GPM: DNA Foundation Model for Predicting the Germline Pathogenic Mutations
Zekai Lin, Haoran Sun, Yucheng Guo, Yujie Yang, Yanwen Wang, Bozhen Hu, Chonghang Ye, Qirong Yang, Fan Zhong, Xiaoming Zhang, Lei Liu
https://arxiv.org/abs/2507.21706

EnTao-GPM: DNA Foundation Model for Predicting the Germline Pathogenic Mutations
Distinguishing pathogenic mutations from benign polymorphisms remains a critical challenge in precision medicine. EnTao-GPM, developed by Fudan University and BioMap, addresses this through three innovations: (1) Cross-species targeted pre-training on disease-relevant mammalian genomes (human, pig, mouse), leveraging evolutionary conservation to enhance interpretation of pathogenic motifs, particularly in non-coding regions; (2) Germline mutation specialization via fine-tuning on ClinVar and HG…

Affine quantum Schur algebras and $\imath$quantum groups with three parameters
Li Luo, Xirui Yu
https://arxiv.org/abs/2509.23559 https://arxiv.org/pdf/2509…

Affine quantum Schur algebras and $\imath$quantum groups with three parameters
We study the affine quantum Schur algebras corresponding to the affine Hecke algebras of type C with three parameters. Multiplication formulas for semisimple generators are derived for these algebras. We prove that they admit a stabilization property in the sense of Beilinson-Lusztig-MacPherson, by which we construct quasi-split $\imath$quantum groups of affine type AIII with three parameters. Upon specialization of parameters, we recover some known multiplication formulas for affine quantum Sc…

Assistant/Associate Professor of Church History
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Fuller Theological Seminary School of Mission and Theology Tenure-Track Faculty Series Position…
via Input 4 RELCFP htt…

Assistant/Associate Professor of Church History
https://ift.tt/H09eVyQ
Fuller Theological Seminary School of Mission and Theology Tenure-Track Faculty Series Position…
via Input 4 RELCFP htt…

Assistant/Associate Professor of Church History
https://ift.tt/YSC5aXi
Fuller Theological Seminary School of Mission and Theology Tenure-Track Faculty Series Position…
via Input 4 RELCFP htt…

Assistant/Associate Professor of Church History
https://ift.tt/mOH8hKA
Fuller Theological Seminary School of Mission and Theology Tenure-Track Faculty Series Position…
via Input 4 RELCFP htt…

Assistant/Associate Professor of Church History
https://ift.tt/ZJxsqbQ
Fuller Theological Seminary School of Mission and Theology Tenure-Track Faculty Series Position…
via Input 4 RELCFP htt…