Tootfinder

A Performance Model for Warp Specialization Kernels
Zhengyang Liu, Vinod Grover
https://arxiv.org/abs/2506.11209 https://arxiv.org/pd…

A Performance Model for Warp Specialization Kernels
This paper presents a performance model tailored for warp specialization kernels, focusing on factors such as warp size, tilling size, input matrix size, memory bandwidth, and thread divergence. Our model offers accurate predictions of execution time by leveraging differential equations validated through simulations and experiments. The insights gained from this model not only enhance our understanding of warp specialization techniques but also have practical implications for optimizing GPU-acc…

Characterization of fiberwise bimeromorphism and specialization of bimeromorphic types I: the non-negative Kodaira dimension case
Jian Chen, Sheng Rao, I-Hsun Tsai
https://arxiv.org/abs/2506.12670

Characterization of fiberwise bimeromorphism and specialization of bimeromorphic types I: the non-negative Kodaira dimension case
Inspired by the recent works of M. Kontsevich--Y. Tschinkel and J. Nicaise--J. C. Ottem on specialization of birational types for smooth families (in the scheme category) and J. Koll{á}r's work on fiberwise bimeromorphism, we focus on characterizing the fiberwise bimeromorphism and utilizing the characterization to investigate the specialization of bimeromorphic types for non-smooth families in the complex analytic setting. We provide some criteria for a bimeromorphic map between two families …

The Theory of Economic Complexity
C\'esar A. Hidalgo, Viktor Stojkoski
https://arxiv.org/abs/2506.18829 https://arxiv.org/pdf/250…

The Theory of Economic Complexity
Economic complexity estimates rely on eigenvectors derived from matrices of specialization to explain differences in economic growth, inequality, and sustainability. Yet, despite their widespread use, we still lack a principled theory that can deduce these eigenvectors from first principles and place them in the context of a mechanistic model. Here, we calculate these eigenvectors analytically for a model where the output of an economy in an activity increases with the probability the economy i…

MoE-MLoRA for Multi-Domain CTR Prediction: Efficient Adaptation with Expert Specialization
Ken Yagel, Eyal German, Aviel Ben Siman Tov
https://arxiv.org/abs/2506.07563

MoE-MLoRA for Multi-Domain CTR Prediction: Efficient Adaptation with Expert Specialization
Personalized recommendation systems must adapt to user interactions across different domains. Traditional approaches like MLoRA apply a single adaptation per domain but lack flexibility in handling diverse user behaviors. To address this, we propose MoE-MLoRA, a mixture-of-experts framework where each expert is first trained independently to specialize in its domain before a gating network is trained to weight their contributions dynamically. We evaluate MoE-MLoRA across eight CTR models on Mov…

Instruction-Tuned Video-Audio Models Elucidate Functional Specialization in the Brain
Subba Reddy Oota, Khushbu Pahwa, Prachi Jindal, Satya Sai Srinath Namburi, Maneesh Singh, Tanmoy Chakraborty, Bapi S. Raju, Manish Gupta
https://arxiv.org/abs/2506.08277

Instruction-Tuned Video-Audio Models Elucidate Functional Specialization in the Brain
Recent voxel-wise multimodal brain encoding studies have shown that multimodal large language models (MLLMs) exhibit a higher degree of brain alignment compared to unimodal models in both unimodal and multimodal stimulus settings. More recently, instruction-tuned multimodal models have shown to generate task-specific representations that align strongly with brain activity. However, prior work evaluating the brain alignment of MLLMs has primarily focused on unimodal settings or relied on non-ins…

This https://arxiv.org/abs/2212.05366 has been replaced.
link: https://scholar.google.com/scholar?q=a

Specialization of Difference Equations and High Frobenius Powers
We study valued fields equipped with an automorphism $σ$ which is locally infinitely contracting in the sense that $α\llσα$ for all $0<α\inΓ$. We show that various notions of valuation theory, such as Henselian and strictly Henselian hulls, admit meaningful transformal analogues. We prove canonical amalgamation results, and exhibit the way that transformal wild ramification is controlled by torsors over generalized vector groups. Model theoretically, we determine the model companion: it i…

Replaced article(s) found for cs.PL. https://arxiv.org/list/cs.PL/new
[1/1]:
A Performance Model for Warp Specialization Kernels
https://

This https://arxiv.org/abs/2411.16826 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCY_…

Ideological Fragmentation of the Social Media Ecosystem: From echo chambers to echo platforms
The entertainment-driven nature of social media encourages users to engage with like-minded individuals and consume content aligned with their beliefs, limiting exposure to diverse perspectives. Simultaneously, users migrate between platforms, either due to moderation policies like de-platforming or in search of environments better suited to their preferences. These dynamics drive the specialization of the social media ecosystem, shifting from internal echo chambers to "echo platforms"--entire …

This https://arxiv.org/abs/2008.08520 has been replaced.
link: https://scholar.google.com/scholar?q=a

Endoscopic decompositions and the Hausel-Thaddeus conjecture
We construct natural operators connecting the cohomology of the moduli spaces of stable Higgs bundles with different ranks and genera which, after numerical specialization, recover the topological mirror symmetry conjecture of Hausel-Thaddeus concerning $\mathrm{SL}_n$- and $\mathrm{PGL}_n$-Higgs bundles. This provides a complete description of the cohomology of the moduli space of stable $\mathrm{SL}_n$-Higgs bundles in terms of the tautological classes, and gives a new proof of the Hausel-Tha…