Negative / Null Result ReportOpen accessMathematics
Ruiwen Fan, Zhangyin Dai, Shixiang Tian et al. · 2022 · arXiv
As an indispensable spatial direction information indicator for emergency evacuation, the spatial relationship between safety evacuation signs and evacuees will affect the response time of evacuees and the evacuation efficiency. This paper takes 2 kinds of common safety evacuation signs, hangtag-type and embedded, as the research object and designs space direction information transmission efficiency and capability simulation experiment and fire drill, the efficiency and capability of spatial direction information transmission of safety evacuation signs are studied. The results show that the sp
View details →Negative / Null Result ReportOpen accessComputer Science
Zuo-Ming Ding, Qi Huang, Jun He · 2025 · arXiv
This study investigates the three-body decay process $B^+ \to D^{*+} D^- K^+$, aiming to explore the possible origins of $T^*_{\bar{c}\bar{s}0}(2870)^0$ and $χ_{c1}(3872)$ as intermediate states. Within the molecular state framework, $T^*_{\bar{c}\bar{s}0}(2870)^0$ and $χ_{c1}(3872)$ are considered as possible $\bar{D}^{*}K^{}$ and $D^*\bar{D}$ molecular states, respectively. Using effective Lagrangians, the interaction kernels of the $\bar{D}^{*}K^{*}$ and $D^*\bar{D}$ systems are constructed within the one-boson-exchange model. The corresponding rescattering amplitudes and pole positions are
View details →Negative / Null Result ReportOpen accessPhysics
Man Qiao, Xian Zhong Zheng, Antonios Katsianis et al. · 2024 · arXiv
Dust attenuation in star-forming galaxies (SFGs), as parameterized by the infrared excess (IRX $\equiv L_{\rm IR}/L_{\rm UV}$), is found to be tightly correlated with star formation rate (SFR), metallicity and galaxy size, following a universal IRX relation up to $z=3$. This scaling relation can provide a fundamental constraint for theoretical models to reconcile galaxy star formation, chemical enrichment, and structural evolution across cosmic time. We attempt to reproduce the universal IRX relation over $0.1\leq z\leq 2.5$ using the EAGLE hydrodynamical simulations and examine sensitive para
View details →Negative / Null Result ReportOpen accessPhysics
C. R. Keeton, C. S. Kochanek, U. Seljak · 1996 · arXiv
Galaxies modeled as singular isothermal ellipsoids with an axis ratio distribution similar to the observed axis ratio distribution of E and S0 galaxies are statistically consistent with both the observed numbers of two-image and four-image lenses and the inferred ellipticities of individual lenses. However, no four-image lens is well fit by the model (typical $χ^2/N_{dof} \sim 20$), the axis ratio of the model can be significantly different from that of the observed lens galaxy, and the major axes of the model and the galaxy may be slightly misaligned. We found that models with a second, indep
View details →Negative / Null Result ReportOpen accessEconomics, Econometrics and Finance
Claudiu Tiberiu Albulescu, Daniel Goyeau · 2016 · arXiv
Inside the EU, the commercial integration of the CEE countries has gained remarkable momentum before the crisis appearance, but it has slightly slowed down afterwards. Consequently, the interest in identifying the factors supporting the commercial integration process is high. Recent findings in the new trade theory suggest that FDI influence the trade intensity but the studies approaching this relationship for the CEE countries present mixed evidence, and investigate the commercial integration of CEE countries with the old EU members. Against this background, the purpose of this paper is to as
View details →Negative / Null Result ReportOpen accessComputer Science
Filippo Betello, Federico Siciliano, Pushkar Mishra et al. · 2023 · arXiv
Sequential Recommender Systems (SRSs) are widely employed to model user behavior over time. However, their robustness in the face of perturbations in training data remains a largely understudied yet critical issue. A fundamental challenge emerges in previous studies aimed at assessing the robustness of SRSs: the Rank-Biased Overlap (RBO) similarity is not particularly suited for this task as it is designed for infinite rankings of items and thus shows limitations in real-world scenarios. For instance, it fails to achieve a perfect score of 1 for two identical finite-length rankings. To address
View details →Negative / Null Result ReportOpen accessPhysics
V. B. Barbeta, R. F. Jardim, M. S. Torikachvili et al. · 2010 · arXiv
Oxides RNiO3 (R = rare-earth, R # La) exhibit a metal-insulator (MI) transition at a temperature TMI and an antiferromagnetic (AF) transition at TN. Specific heat (CP) and anelastic spectroscopy measurements were performed in samples of Nd1-xEuxNiO3, 0 = 0.25, differences between cooling and warming curves are negligible, and two well defined peaks are clearly observed: one at lower temperatures, that define TN, and t
View details →Negative / Null Result ReportMedicine
Ruan, Wu, Liao et al. · 2026 · Journal of neuroengineering and rehabilitation
Functional constipation (FCon) involves central nervous system dysregulation, particularly in brain regions responsible for visceral sensation, emotional processing, and autonomic control. Using functional near-infrared spectroscopy…
View details →Negative / Null Result ReportOpen accessPhysics
Benjamin O. Mummery, Ian G. McCarthy, Simeon Bird et al. · 2017 · arXiv
We use the cosmo-OWLS and BAHAMAS suites of cosmological hydrodynamical simulations to explore the separate and combined effects of baryon physics (particularly feedback from active galactic nuclei, AGN) and free-streaming of massive neutrinos on large-scale structure. We focus on five diagnostics: i) the halo mass function; ii) halo mass density profiles; iii) the halo mass-concentration relation; iv) the clustering of haloes; and v) the clustering of matter; and we explore the extent to which the effects of baryon physics and neutrino free-streaming can be treated independently. Consistent w
View details →Negative / Null Result ReportOpen accessPhysics
Anatoly Golub, Baruch Horovitz · 1997 · arXiv
We study a flux lattice which is parallel to superconducting layers, allowing for dislocations and for disorder of both short wavelength and long wavelength. We find that the long wavelength disorder has a significant effect on the phase diagram -- it produces a first order transition within the Bragg glass phase and leads to melting at strong disorder. This then allows a Friedel scenario of 2D superconductivity.
View details →Negative / Null Result ReportOpen accessPhysics
Ankit Kumar, Mousumi Das, Sandeep Kumar Kataria · 2021 · arXiv
Galaxy flybys are as common as mergers in low redshift universe and are important for galaxy evolution as they involve the exchange of significant amounts of mass and energy. In this study we investigate the effect of minor flybys on the bulges, disks, and spiral arms of Milky Way mass galaxies for two types of bulges - classical bulges and boxy/peanut pseudobulges. Our N-body simulations comprise of two disk galaxies of mass ratios 10:1 and 5:1, where the disks of the galaxies lie in their orbital plane and the pericenter distance is varied. We performed photometric and kinematic bulge-disk d
View details →Negative / Null Result ReportOpen accessComputer Science
Julien Mercier, N. Chabloz, G. Dozot et al. · 2023 · arXiv
Abstract. While the use of location-based augmented reality (AR) for education has demonstrated benefits on participants' motivation, engagement, and on their physical activity, geolocation data inaccuracy causes augmented objects to jitter or drift, which is a factor in downgrading user experience. We developed a free and open source web AR application and conducted a comparative user test (n = 54) in order to assess the impact of geolocation data on usability, exploration, and focus. A control group explored biodiversity in nature using the system in combination with embedded GNSS data, and
View details →Negative / Null Result ReportOpen accessPhysics
Philip Rosenfield, Paola Marigo, Leo Girardi et al. · 2014 · arXiv
The evolution and lifetimes of thermally pulsating asymptotic giant branch (TP-AGB) stars suffer from significant uncertainties. In this work, we analyze the numbers and luminosity functions of TP-AGB stars in six quiescent, low metallicity ([Fe/H] $\lesssim -0.86$) galaxies taken from the ANGST sample, using HST photometry in both optical and near-infrared filters. The galaxies contain over 1000 TP-AGB stars (at least 60 per field). We compare the observed TP-AGB luminosity functions and relative numbers of TP-AGB and RGB stars, to models generated from different suites of TP-AGB evolutionary
View details →Negative / Null Result ReportOpen accessComputer Science
Kerem Cankocak, Aytekin Aydemir, Ramazan Sever · 2004 · arXiv
We compute the rates for pp annihilation into chargino-pairs via Drell-Yan process taking into account the effects of supersymmetric soft phases, at proton-proton collider. In particular, the phase of the mu parameter gains direct accessibility via the production of dissimilar charginos. The phases of the trilinear soft masses do not have a significant effect on the cross sections.
View details →Negative / Null Result ReportOpen accessComputer Science
Song Tae-Eun · 2026 · arXiv
Cross-Context Review (CCR) improves LLM verification by separating production and review into independent sessions. A natural extension is multi-turn review: letting the reviewer ask follow-up questions, receive author responses, and review again. We call this Dynamic Cross-Context Review (D-CCR). In a controlled experiment with 30 artifacts and 150 injected errors, we tested four D-CCR variants against the single-pass CCR baseline. Single-pass CCR (F1 = 0.376) significantly outperformed all multi-turn variants, including D-CCR-2b with question-and-answer exchange (F1 = 0.303, $p < 0.001$, $d
View details →Negative / Null Result ReportOpen accessComputer Science
Marco Cognetta, Tatsuya Hiraoka, Naoaki Okazaki et al. · 2024 · arXiv
We explore threshold vocabulary trimming in Byte-Pair Encoding subword tokenization, a postprocessing step that replaces rare subwords with their component subwords. The technique is available in popular tokenization libraries but has not been subjected to rigorous scientific scrutiny. While the removal of rare subwords is suggested as best practice in machine translation implementations, both as a means to reduce model size and for improving model performance through robustness, our experiments indicate that, across a large space of hyperparameter settings, vocabulary trimming fails to improv
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Janarthanan Rajendran, Jonathan K. Kummerfeld, Satinder Singh · 2021 · arXiv
For each goal-oriented dialog task of interest, large amounts of data need to be collected for end-to-end learning of a neural dialog system. Collecting that data is a costly and time-consuming process. Instead, we show that we can use only a small amount of data, supplemented with data from a related dialog task. Naively learning from related data fails to improve performance as the related data can be inconsistent with the target task. We describe a meta-learning based method that selectively learns from the related dialog task data. Our approach leads to significant accuracy improvements in
View details →Negative / Null Result ReportOpen accessComputer Science
Dhruvi Khandelwal, Anurag Basistha, Ayushi Jolotia et al. · 2026 · arXiv
Deep learning proxies for Alternating Current Optimal Power Flow (ACOPF) lack systematic methods for determining architectural size. This paper conducts a constructive thought experiment to answer a fundamental inquiry: how wide must a neural network be to almost accurately approximate the ACOPF manifold? We introduce a Loss-Guided Neural Densification (LG-ND) algorithm that incrementally discovers necessary capacity by expanding only when the current deep neural network topology fails to improve further. Empirical results across various IEEE systems show that LG-ND achieves performance parity
View details →Negative / Null Result ReportOpen accessComputer Science
Runzhe Zhan, Xuebo Liu, Derek F. Wong et al. · 2021 · arXiv
Meta-learning has been sufficiently validated to be beneficial for low-resource neural machine translation (NMT). However, we find that meta-trained NMT fails to improve the translation performance of the domain unseen at the meta-training stage. In this paper, we aim to alleviate this issue by proposing a novel meta-curriculum learning for domain adaptation in NMT. During meta-training, the NMT first learns the similar curricula from each domain to avoid falling into a bad local optimum early, and finally learns the curricula of individualities to improve the model robustness for learning dom
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Arijit Sehanobish, Charles Lovering · 2026 · arXiv
We study the \textit{parameter placement problem}: given a fixed budget of $k$ trainable entries within the B matrix of a LoRA adapter (A frozen), does the choice of which $k$ matter? Under supervised fine-tuning, random and informed subsets achieve comparable performance. Under GRPO on base models, random placement fails to improve over the base model, while gradient-informed placement recovers standard LoRA accuracy. This regime dependence traces to gradient structure: SFT gradients are low-rank and directionally stable, so any subset accumulates coherent updates; GRPO gradients are high-ran
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Can Cui, Imran Ahamad Sheikh, Mostafa Sadeghi et al. · 2024 · arXiv
Distant-microphone meeting transcription is a challenging task. State-of-the-art end-to-end speaker-attributed automatic speech recognition (SA-ASR) architectures lack a multichannel noise and reverberation reduction front-end, which limits their performance. In this paper, we introduce a joint beamforming and SA-ASR approach for real meeting transcription. We first describe a data alignment and augmentation method to pretrain a neural beamformer on real meeting data. We then compare fixed, hybrid, and fully neural beamformers as front-ends to the SA-ASR model. Finally, we jointly optimize the
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Zelu Deng, Yujie Zhong, Sheng Guo et al. · 2021 · arXiv
This work aims at improving instance retrieval with self-supervision. We find that fine-tuning using the recently developed self-supervised (SSL) learning methods, such as SimCLR and MoCo, fails to improve the performance of instance retrieval. In this work, we identify that the learnt representations for instance retrieval should be invariant to large variations in viewpoint and background etc., whereas self-augmented positives applied by the current SSL methods can not provide strong enough signals for learning robust instance-level representations. To overcome this problem, we propose InsCL
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Shayne Longpre, Yi Lu, Christopher DuBois · 2020 · arXiv
Recent work (Feng et al., 2018) establishes the presence of short, uninterpretable input fragments that yield high confidence and accuracy in neural models. We refer to these as Minimal Prediction Preserving Inputs (MPPIs). In the context of question answering, we investigate competing hypotheses for the existence of MPPIs, including poor posterior calibration of neural models, lack of pretraining, and "dataset bias" (where a model learns to attend to spurious, non-generalizable cues in the training data). We discover a perplexing invariance of MPPIs to random training seed, model architecture
View details →Negative / Null Result ReportOpen accessMathematics
Oliver J. Hines, Christian L. Hines · 2026 · arXiv
Gradient boosted decision trees require a stopping rule to avoid overfitting. The standard rule monitors a validation loss and stops if the loss fails to improve for a fixed patience period. However, the patience parameter has no interpretable scale and validation losses can be noisy or implicitly defined by a user-specified gradient. We propose ScoreStop, a gradient-based early-stopping rule that casts the stopping decision at each iteration as a test of the null hypothesis that the current predictor is the population risk minimizer. We use a functional score test, computed on validation data
View details →Negative / Null Result ReportOpen accessComputer Science
Hanbing Liu, Haoyang Li, Xiaokang Zhang et al. · 2025 · arXiv
Direct Preference Optimization (DPO) has proven effective in complex reasoning tasks like math word problems and code generation. However, when applied to Text-to-SQL datasets, it often fails to improve performance and can even degrade it. Our investigation reveals the root cause: unlike math and code tasks, which naturally integrate Chain-of-Thought (CoT) reasoning with DPO, Text-to-SQL datasets typically include only final answers (gold SQL queries) without detailed CoT solutions. By augmenting Text-to-SQL datasets with synthetic CoT solutions, we achieve, for the first time, consistent and
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Àlex Miranda-Pascual, Javier Parra-Arnau, Thorsten Strufe · 2026 · arXiv
Sampling is renowned for its privacy amplification in differential privacy (DP), and is often assumed to improve the utility of a DP mechanism by allowing a noise reduction. In this paper, we further show that this last assumption is flawed: When measuring utility at equal privacy levels, sampling as preprocessing consistently yields penalties due to utility loss from omitting records over all canonical DP mechanisms -- Laplace, Gaussian, exponential, and report noisy max -- , as well as recent applications of sampling, such as clustering. Extending this analysis, we investigate suppression as
View details →Negative / Null Result ReportOpen accessEngineering
Haoyang Li, Yuchen Hu, Chen Chen et al. · 2024 · arXiv
Deep neural network (DNN)-based speech enhancement (SE) usually uses conventional activation functions, which lack the expressiveness to capture complex multiscale structures needed for high-fidelity SE. Group-Rational KAN (GR-KAN), a variant of Kolmogorov-Arnold Networks (KAN), retains KAN's expressiveness while improving scalability on complex tasks. We adapt GR-KAN to existing DNN-based SE by replacing dense layers with GR-KAN layers in the time-frequency (T-F) domain MP-SENet and adapting GR-KAN's activations into the 1D CNN layers in the time-domain Demucs. Results on Voicebank-DEMAND sho
View details →Negative / Null Result ReportMedicine
Duman Aydin, Küçükosman, Mohamed et al. · 2026 · BMC medical education
Although oxygen therapy (OT) is a fundamental and life-saving intervention in the management of hypoxemia, it may lead to serious complications when applied incorrectly or in an uncontrolled manner. The aim of this study is to evaluate the…
View details →Negative / Null Result ReportOpen accessComputer Science
Piyawat Lertvittayakumjorn, David Kinney, Vinodkumar Prabhakaran et al. · 2025 · arXiv
Generative large language models (LLMs) have demonstrated gaps in diverse cultural awareness across the globe. We investigate the effect of retrieval augmented generation and search-grounding techniques on LLMs' ability to display familiarity with various national cultures. Specifically, we compare the performance of standard LLMs, LLMs augmented with retrievals from a bespoke knowledge base (i.e., KB grounding), and LLMs augmented with retrievals from a web search (i.e., search grounding) on multiple cultural awareness benchmarks. We find that search grounding significantly improves the LLM p
View details →Negative / Null Result ReportOpen accessEconomics, Econometrics and Finance
Francis X. Diebold, Maximilian Goebel, Philippe Goulet Coulombe · 2022 · arXiv
We use "glide charts" (plots of sequences of root mean squared forecast errors as the target date is approached) to evaluate and compare fixed-target forecasts of Arctic sea ice. We first use them to evaluate the simple feature-engineered linear regression (FELR) forecasts of Diebold and Goebel (2021), and to compare FELR forecasts to naive pure-trend benchmark forecasts. Then we introduce a much more sophisticated feature-engineered machine learning (FEML) model, and we use glide charts to evaluate FEML forecasts and compare them to a FELR benchmark. Our substantive results include the freque
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