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Thesis Tide

Thesis Tide ranks papers based on their relevance to the fields, with the goal of making it easier to find the most relevant papers. It uses AI to analyze the content of papers and rank them!

Reconstruction of caterpillar tanglegrams

A tanglegram consists of two rooted binary trees with the same number of leaves and a perfect matching between the leaves of the trees. Given a size- $n$ tanglegram, i.e., a tanglegram for two ...

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The article presents a unique investigation into the properties of tanglegrams and their reconstruction, focusing on caterpillar trees. The problem is quite specific and addresses open questions in theoretical computer science and bioinformatics regarding tree structures, making it a significant contribution. Its affirmative result enhances understanding in this niche area, which could encourage further exploration into related structures, although the applicability outside theoretical contexts may be limited.

How to Complete Domain Tuning while Keeping General Ability in LLM: Adaptive Layer-wise and Element-wise Regularization

Large Language Models (LLMs) exhibit strong general-purpose language capabilities. However, fine-tuning these models on domain-specific tasks often leads to catastrophic forgetting, where the model ov...

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This article presents a novel and practical solution to an important challenge in the application of LLMs—catastrophic forgetting. Its dual-objective optimization strategy offers a fresh perspective on preserving generalization while adapting to specific tasks. The thorough experimentation across diverse domains strengthens its claims and demonstrates its robust applicability. The efficiency improvements in model training and storage are particularly impactful, suggesting significant potential for adoption in various applications. The provision of released code further enhances its utility for future research.

Reconstructing Quantum States from Local Observation: A Dynamical Viewpoint

We analyze the problem of reconstructing an unknown quantum state of a multipartite system from repeated measurements of local observables. In particular, via a system-theoretic observability analysis...

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The article presents a novel approach to quantum state reconstruction by emphasizing the role of dynamical systems, which has significant implications for how we understand measurement in quantum mechanics. The methodological rigor in utilizing system-theoretic observability is commendable, and the discussion on finite samples adds important real-world applicability, making this work timely and relevant. The concept of reconstructing states from dynamics could inspire future research into more efficient quantum measurement techniques and their applications in quantum computing and quantum information science.

MPG-SAM 2: Adapting SAM 2 with Mask Priors and Global Context for Referring Video Object Segmentation

Referring video object segmentation (RVOS) aims to segment objects in a video according to textual descriptions, which requires the integration of multimodal information and temporal dynamics percepti...

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The proposed MPG-SAM 2 framework introduces significant advancements in the field of referring video object segmentation by effectively integrating multimodal information and enhancing global context awareness. The methodologies employed, including the use of a unified multimodal encoder and hierarchical global-historical aggregation, reflect a high level of innovation and methodological rigor. Its adaptability to existing powerful models (like SAM 2) showcases potential for practical applications and sets a foundation for future explorations in RVOS.

$\infty$ -categorical group quotients via skew group algebras

We describe group quotients of dg-categories and linear stable $\infty$ -categories. Given a group acting on a dg-algebra, we prove that the skew group dg-algebra is Morita equivalent to the dg...

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The article presents a novel approach to understanding group quotients of dg-categories and their connections with $ ext{skew}$ group algebras. The rigorous treatment of Morita equivalence and applications to ring spectra suggests significant methodological depth and potential for advancing research in higher category theory and derived algebraic geometry. The interplay between dg-algebras and $ ext{∞}$-categories represents a fruitful interdisciplinary link, making the findings applicable to a range of theoretical frameworks.

Limits on WIMP dark matter with NaI(Tl) crystals in three years of COSINE-100 data

We report limits on WIMP dark matter derived from three years of data collected by the COSINE-100 experiment with NaI(Tl) crystals, achieving an improved energy threshold of 0.7 keV. This lowered thre...

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The article presents significant advancements in the detection of WIMP dark matter, particularly by providing improved sensitivity and excluding long-debated signals from other experiments like DAMA. The methodological rigor is apparent in the extended reach for low-mass dark matter and the comprehensive analysis of WIMP cross-sections, indicating robust and novel findings that push the boundaries of current research.

Three-dimensional multiscale discrete Radon and John transforms

Two algorithms are introduced for the computation of discrete integral transforms with a multiscale approach operating in discrete three-dimensional (3D) volumes while considering its real-time implem...

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The article introduces novel multiscale algorithms for discrete integral transforms which have practical implications in real-time computing and performance improvements over traditional methods. The significance of applying discrete transforms in three-dimensional data, along with effective algorithm performance, showcases both methodological rigor and applicability, particularly in fields that handle large datasets or require computational efficiency.

Thermodynamics and collisionality in firehose-susceptible high- $β$ plasmas

We study the evolution of collisionless plasmas that, due to their macroscopic evolution, are susceptible to the firehose instability, using both analytic theory and hybrid-kinetic particle-in-cell si...

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This study presents significant advancements in the understanding of firehose instabilities in high-$β$ plasmas, contributing novel insights into the thermodynamic states of collisionless plasmas. The combination of analytic and hybrid-kinetic simulations enhances methodological rigor, while the identification of a new state — the 'Alfvén-enabling' state — has substantial implications for astrophysical contexts, suggesting wider applicability and relevance. Moreover, the energy spectra characterization and effective collision operator insights can inform future research in plasma physics.

A Fast and Accurate Implementation of the Effective Fluid Approximation for Ultralight Axions

We present a numerically efficient and accurate implementation of the Passaglia-Hu effective fluid approximation for ultralight axions (ULAs) within the Boltzmann code CAMB. This method is specificall...

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The article presents a novel implementation of a fluid approximation for ultralight axions within an established cosmological framework (CAMB), enhancing both numerical efficiency and accuracy. Its contributions to the understanding and constraints on axion parameters are significant, given the major relevance of ULAs in cosmology and dark matter studies. The methodological rigor and the open-access nature provide strong support for reproducibility and further research.

Discovery of the richest pulsating ultra-massive white dwarf

The discovery of pulsations in ultra-massive white dwarfs can help to probe their interiors and unveil their core composition and crystallized mass fraction through asteroseismic techniques. To date, ...

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The discovery of 19 pulsation modes in WD J0135+5722 significantly enhances current knowledge of ultra-massive white dwarfs, particularly in terms of their internal structures and compositions. The application of asteroseismic techniques contributes both novelty and methodological rigor. However, while findings are compelling, the broader implications for astrophysics will depend on future confirmatory studies that can reproducibly analyze these asteroseismic signals.

Scattering Insights into Shear-Induced Scission of Rod-like Micelles

Hypothesis Understanding the scission of rod-like micelles under mechanical forces is crucial for optimizing their stability and behavior in industrial applications. This study investigates how mice...

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The article presents novel experimental data on the shear-induced scission of rod-like micelles, using SANS and rheological techniques, which may significantly enhance our understanding of micellar systems under mechanical stress. The combination of experimental and analytical approaches adds methodological robustness, making the findings valuable for both theoretical and applied research. However, the specific industrial applications remain somewhat vague, which slightly limits the immediate practical relevance.

Reduced digital nets

In the recent papers ``The fast reduced QMC matrix-vector product'' (J. Comput. Appl. Math. 440, 115642, 2024) and ``Column reduced digital nets'' (submitted), it w...

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The paper addresses an advanced topic within quasi-Monte Carlo (QMC) methods, presenting novel upper bounds on the quality parameters of reduced digital nets, which is crucial for improving error analysis in integration. The methodological rigor and application potential in computational mathematics make it highly relevant for both theoretical and practical advancements in QMC techniques.

Femtoliter Batch Reactors for Nanofluidic Scattering Spectroscopy Analysis of Catalytic Reactions on Single Nanoparticles

Macroscopic batch reactors are a core concept in chemical synthesis and catalysis due to their ability to ensure high conversion rates of the used reactants. At the nanoscale, such reactors hold promi...

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The article presents a novel approach to analyzing catalytic reactions at the nanoscale through the development of a femtoliter batch reactor. This innovation enhances the understanding of catalytic processes on single nanoparticles, which is crucial for optimizing catalysts in various applications. The methodological rigor and potential for practical applications in nanochemistry and nanotechnology contribute to its high relevance. However, the specificity of its application to certain reactions slightly limits its broader applicability, hence a score of 8.7.

Evolvable Soma Theory of Ageing: Insights from Computer Simulations

Biological evolution continuously refines the design of species, resulting in highly optimised organisms over hundreds of millennia. Intuitively, we expect that random changes-evolution's primary ...

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This article presents a novel theory (ESTA) with a solid basis in evolutionary biology, exploring ageing through a computational lens. The work employs rigorous simulations to support its claims, highlighting its methodological strength. It challenges existing theories and offers new insights that could facilitate further research into evolutionary dynamics and age-related changes in biology. However, the applicability in real biological systems needs further empirical validation.

A search for close binary systems in the SALT survey of hydrogen-deficient stars using {\it TESS}

The {\it TESS} periodograms of the SALT survey catalogue of hydrogen-deficient stars were searched for evidence of short-period variability. Periodic light curve variations were identified in 16 stars...

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The study utilizes advanced observational data from TESS to explore close binary systems among hydrogen-deficient stars, revealing significant findings about variability and binary classifications. However, the identification of only one confirmed binary limits its broader impact. The analyses applied are methodological, and while the outcomes are valuable, the scope of discoveries does not present groundbreaking insights but rather a useful addition to existing knowledge.

Linearization of ergodic McKean SDEs and applications

In this article, we consider McKean stochastic differential equations, as well as their corresponding McKean-Vlasov partial differential equations, which admit a unique stationary state, and we study ...

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This article introduces a novel framework for linearizing McKean stochastic differential equations (SDEs), which is a significant advance given the complexity inherent in nonlinear SDEs. The methodological rigor is evident in the proofs of exponential convergence rates in both relative entropy and Wasserstein distance, which have considerable implications for future research in this domain. Furthermore, the practical application of a linearized maximum likelihood estimator enhances its relevance for data-driven approaches in stochastic processes, thereby broadening its impact and applicability.

Characterizing phase transitions and criticality in non-Hermitian extensions of the XY model

In this work we study non-Hermitian extensions of the paradigmatic spin-1/2 XY chain in a magnetic field. Using the mapping of the model to free fermion form, we provide analytical insights into the e...

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This article presents a novel investigation into non-Hermitian extensions of established models, combining analytical and numerical methods to reveal significant insights into phase transitions and criticality. The work stands out due to its methodological rigor and introduces new concepts such as the relationship between quasienergies and topological invariants, which could inspire further studies in both theoretical and applied contexts.

Towards a parameter-free analysis of the QCD chiral phase transition and its universal critical behavior

To quantify the universal properties of chiral phase transition in (2+1)-flavor QCD, we use an improved, renormalized order parameter for the chiral symmetry breaking. We construct ratios of this dive...

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The article presents a novel and rigorous approach to analyzing the QCD chiral phase transition using a parameter-free method, which could significantly enhance our understanding of the critical behavior associated with this phenomenon. The use of an improved order parameter and the focus on universality adds to the methodological rigor and potential impact of the results. The numerical results provided are crucial for validating the theoretical framework, making the research highly applicable in the field.

LVPruning: An Effective yet Simple Language-Guided Vision Token Pruning Approach for Multi-modal Large Language Models

Multi-modal Large Language Models (MLLMs) have achieved remarkable success by integrating visual and textual modalities. However, they incur significant computational overhead due to the large number ...

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The study introduces a novel approach to reducing computational overhead in multi-modal large language models, addressing a significant limitation in the practicality of these models. The simplicity of implementation without modifying original model parameters is a considerable advantage. The method also shows strong empirical results, indicating both effectiveness in reducing resource demands and minimal impact on model performance. This combination of applicability and performance makes the research highly relevant for current trends in AI.

Compactly supported $p$ -adic pro-étale cohomology of analytic varieties

We study properties of compactly supported $p$ -adic pro-étale cohomology of smooth partially proper rigid analytic varieties. In particular, we prove a comparison theorem, in a stable range, w...

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The article addresses a significant gap in the understanding of $p$-adic pro-étale cohomology in the context of rigid analytic varieties, showcasing methodological rigor through the proof of a comparison theorem. This suggests novel insights that could inform both theoretical developments and practical applications in arithmetic geometry and number theory. Its findings could inspire further exploration into the connections between various cohomological frameworks, leading to potential advancements in the field.