Negative / Null Result Report
Muhammad Dawood Mian, Saadullah Jan Khan, Rehana Rani et al. · 2026 · Access Microbiology
Rapid and reliable identification of bacteria is essential in clinical and environmental microbiology. Gram staining remains a widely used method for preliminary classification; however, it may require additional steps and can be difficult…
View details →DOI: 10.1099/acmi.0.000965.v3 Negative / Null Result ReportOpen accessComputer Science
Mike Zhang, Ali Basirat, Desmond Elliott · 2026 · arXiv
Prior work establishes that controlled contrastiveness between self-generated responses from large language models, set via reward scores, improves downstream preference tuning in English. We extend this method to multiple languages and evaluate two models across a total of 14 high and low-resource languages on a diverse set of tasks. Our central finding is that cross-lingual contrastive preference tuning on self-generations (CroCo) transfers without language-specific preference annotation. A reward model trained on English preferences (atop a multilingual base) produces useful within-language
Negative / Null Result ReportOpen accessComputer Science
Zhiwei Jia, Xuanlin Li, Zhan Ling et al. · 2022 · arXiv
Generalization in deep reinforcement learning over unseen environment variations usually requires policy learning over a large set of diverse training variations. We empirically observe that an agent trained on many variations (a generalist) tends to learn faster at the beginning, yet its performance plateaus at a less optimal level for a long time. In contrast, an agent trained only on a few variations (a specialist) can often achieve high returns under a limited computational budget. To have the best of both worlds, we propose a novel generalist-specialist training framework. Specifically, w
Negative / Null Result ReportOpen accessComputer Science
Lily H. Zhang, Rajesh Ranganath · 2023 · arXiv
Methods which utilize the outputs or feature representations of predictive models have emerged as promising approaches for out-of-distribution (OOD) detection of image inputs. However, these methods struggle to detect OOD inputs that share nuisance values (e.g. background) with in-distribution inputs. The detection of shared-nuisance out-of-distribution (SN-OOD) inputs is particularly relevant in real-world applications, as anomalies and in-distribution inputs tend to be captured in the same settings during deployment. In this work, we provide a possible explanation for SN-OOD detection failur
Negative / Null Result Report
Mary Cushman, Suzanne E Judd, Virginia J Howard et al. · 2011 · Circulation
Background. The AHA 2020 Goal includes improving cardiovascular health, defined using a metric consisting of 7 health factors, Life's Simple 7. A central concept of the goal is that small improvements in behavior / lifestyle factors at the…
View details →DOI: 10.1161/circ.124.suppl_21.a17917 Negative / Null Result ReportOpen accessMathematics
Ziling Ma, Ángel López Oriona, Hernando Ombao et al. · 2026 · arXiv
We study adaptive pooling under predictive heterogeneity in high-dimensional multivariate time series forecasting, where global models improve statistical efficiency but may fail to capture heterogeneous predictive structure, while naive specialization can induce negative transfer. We formulate adaptive pooling as a statistical decision problem and propose a validation-driven framework that determines when and how specialization should be applied. Rather than grouping series based on representation similarity, we define partitions through out-of-sample predictive performance, thereby aligning
Negative / Null Result ReportOpen accessComputer Science
Niek Beckers, Edwin van Asseldonk, Herman van der Kooij · 2020 · arXiv
Haptic interaction between two humans, for example, a physiotherapist assisting a patient regaining the ability to grasp a cup, likely facilitates motor skill acquisition. Haptic human-human interaction has been shown to enhance individual performance improvement in a tracking task with a visuomotor rotation perturbation. These results are remarkable given that haptically assisting or guiding an individual rarely benefits their individual improvement when the assistance is removed. We, therefore, replicated a study that reported that haptic interaction between humans was beneficial for individ
Negative / Null Result ReportOpen accessComputer Science
Minwu Kim, Anubhav Shrestha, Safal Shrestha et al. · 2025 · arXiv
Recent studies have shown that reinforcement learning with verifiable rewards (RLVR) enhances overall accuracy (pass@1) but often fails to improve capability (pass@k) of LLMs in reasoning tasks, while distillation can improve both. In this paper, we investigate the mechanisms behind these phenomena. First, we demonstrate that RLVR struggles to improve capability as it focuses on improving the accuracy of the easier questions to the detriment of the accuracy of the most difficult questions. Second, we show that RLVR does not merely increase the success probability for the easier questions, but
Negative / Null Result ReportOpen accessComputer Science
Runtian Zhai, Chen Dan, Zico Kolter et al. · 2022 · arXiv
Empirical risk minimization (ERM) is known in practice to be non-robust to distributional shift where the training and the test distributions are different. A suite of approaches, such as importance weighting, and variants of distributionally robust optimization (DRO), have been proposed to solve this problem. But a line of recent work has empirically shown that these approaches do not significantly improve over ERM in real applications with distribution shift. The goal of this work is to obtain a comprehensive theoretical understanding of this intriguing phenomenon. We first posit the class o
Negative / Null Result ReportOpen accessEngineering
Jiaqi Wu, Jingyi Yuan, Yang Weng et al. · 2025 · arXiv
Power system voltage regulation is crucial to maintain power quality while integrating intermittent renewable resources in distribution grids. However, the system model on the grid edge is often unknown, making it difficult to model physical equations for optimal control. Therefore, previous work proposes structured data-driven methods like input convex neural networks (ICNN) for "optimal" control without relying on a physical model. While ICNNs offer theoretical guarantees based on restrictive assumptions of non-negative neural network parameters, can one improve the approximation power with
Negative / Null Result ReportOpen accessEngineering
Kwon Byung-Ki, Oh Hyun-Bin, Kim Jun-Seong et al. · 2023 · arXiv
Video motion magnification amplifies invisible small motions to be perceptible, which provides humans with a spatially dense and holistic understanding of small motions in the scene of interest. This is based on the premise that magnifying small motions enhances the legibility of motions. In the real world, however, vibrating objects often possess convoluted systems that have complex natural frequencies, modes, and directions. Existing motion magnification often fails to improve legibility since the intricate motions still retain complex characteristics even after being magnified, which may di
Negative / Null Result Report
Ainun Oktavia Sari, Rahayu Sulistyowati, Ita Prihantika · 2020 · Administrativa: Jurnal Birokrasi, Kebijakan dan Pelayanan Publik
The Conditional Cash Transfer (CCT) is a conditional social cash transfer program that provides assistance to Very Poor Households (RTSM) appointed as participants in the Conditional Cash Transfer program which is related to improving the…
View details →DOI: 10.23960/administrativa.v2i3.51 Negative / Null Result ReportOpen accessMathematics
Mark Rubin · 2020 · arXiv
Preregistration entails researchers registering their planned research hypotheses, methods, and analyses in a time-stamped document before they undertake their data collection and analyses. This document is then made available with the published research report to allow readers to identify discrepancies between what the researchers originally planned to do and what they actually ended up doing. This historical transparency is supposed to facilitate judgments about the credibility of the research findings. The present article provides a critical review of 17 of the reasons behind this argument.
Negative / Null Result ReportOpen accessComputer Science
Alex Ayoub, Samuel Robertson, Dawen Liang et al. · 2025 · arXiv
Matrix factorization is a widely used approach for top-N recommendation and collaborative filtering. When implemented on implicit feedback data (such as clicks), a common heuristic is to upweight the observed interactions. This strategy has been shown to improve performance for certain algorithms. In this paper, we conduct a systematic study of various weighting schemes and matrix factorization algorithms. Somewhat surprisingly, we find that training with unweighted data can perform comparably to, and sometimes outperform, training with weighted data, especially for large models. This observat
Negative / Null Result ReportOpen accessMathematics
Andrea Schioppa · 2015 · arXiv
For each $β>1$ we construct a family $F_β$ of metric measure spaces which is closed under the operation of taking weak-tangents (i.e.~blow-ups), and such that each element of $F_β$ admits a $(1,P)$-Poincaré inequality if and only if $P>β$.
Negative / Null Result ReportMedicine
Alshaibani, Kamadjaja, Sitalaksmi et al. · 2026 · Journal of molecular histology
Tooth extraction is a common procedure often followed by alveolar bone resorption, which may compromise future implant placement, prosthetic rehabilitation, esthetics, and periodontal support. Hydroxyapatite-chitosan (HA-Chi) scaffolds…
View details →DOI: 10.1007/s10735-026-10874-4 Negative / Null Result ReportOpen accessEconomics, Econometrics and Finance
Ian Crawford, Carl-Emil Pless · 2026 · arXiv
We study the associations between everyday economic decision-making quality and people's emotional states. Using high-frequency, highly disaggregated consumer "scanner" data, we show that the cost of poor decision-making is substantial, on average equal to around half of day-to-day consumption budgets. While material circumstances help explain decision-making quality, how people feel about those circumstances is equally important. Contrary to evidence that stress and worry impair performance in settings where distraction is costly, we find these same feelings are associated with improved decis
Abandoned Hypothesis
Julia Casañas Cast · 2020 · Royal Conservatoire Research Portal
Many classical musicians can suffer from tension and nervousness during solo performance. This research looks at how practicing improvisation and creative body movement, as well as creating one’s own performance together with a dancer, can…
View details →DOI: 10.22501/koncon.792184 Negative / Null Result Report
Bahadır Kartal, Mehmet Berksun Tutan, Fatih Şahin et al. · 2024 · Hitit Medical Journal
Objective: Gastric cancer surgery, including curative and palliative procedures, is crucial for managing gastric cancer. Accurate assessment of nutritional status is essential for risk stratification and improving patient outcomes. This…
View details →DOI: 10.52827/hititmedj.1516777 Negative / Null Result ReportMedicine
Baudin, Pouyau, Subtil et al. · 2026 · JAMA
Prone positioning has been shown to improve respiratory mechanics and oxygenation, but its clinical benefit in infants with acute viral bronchiolitis receiving high-flow nasal cannula (HFNC) support remains unknown. To investigate whether…
View details →DOI: 10.1001/jama.2026.11078 Negative / Null Result ReportOpen accessComputer Science
Paul K. Mandal · 2025 · arXiv
In this paper, I investigate the effectiveness of dataset cartography for extractive question answering on the SQuAD dataset. I begin by analyzing annotation artifacts in SQuAD and evaluate the impact of two adversarial datasets, AddSent and AddOneSent, on an ELECTRA-small model. Using training dynamics, I partition SQuAD into easy-to-learn, ambiguous, and hard-to-learn subsets. I then compare the performance of models trained on these subsets to those trained on randomly selected samples of equal size. Results show that training on cartography-based subsets does not improve generalization to
Negative / Null Result ReportMedicine
Parirokh, Manochehrifar, Nakahee et al. · 2026 · Iranian endodontic journal
The close relationship between pulp stones in the pulp chamber and pulp neurovascular tissues suggests that the presence of pulp stones may compromise successful anesthesia. The present study assessed the effect of pulp stone presence on…
View details →DOI: 10.22037/iej.v21i1.46586 Negative / Null Result ReportOpen accessMathematics
Mark Rubin · 2024 · arXiv
One justification for preregistering research hypotheses, methods, and analyses is that it improves the transparent evaluation of the severity of hypothesis tests. In this article, I consider two cases in which preregistration does not improve this evaluation. First, I argue that, although preregistration may facilitate the transparent evaluation of severity in Mayo's error statistical philosophy of science, it does not facilitate this evaluation in Popper's theory-centric approach. To illustrate, I show that associated concerns about Type I error rate inflation are only relevant in the error
Negative / Null Result ReportMedicine
Ziltzer, Bulbul, Barry et al. · 2026 · The Laryngoscope
To investigate whether routine involvement of the medical hospitalist service (MHS) in postoperative medical management of head and neck cancer (HNC) patients undergoing major ablative head and neck surgery with free tissue transfer (FTT)…
View details →DOI: 10.1002/lary.70659 Negative / Null Result ReportOpen accessComputer Science
Ab Mosca, Alvitta Ottley, Remco Chang · 2021 · arXiv
Interaction enables users to navigate large amounts of data effectively, supports cognitive processing, and increases data representation methods. However, there have been few attempts to empirically demonstrate whether adding interaction to a static visualization improves its function beyond popular beliefs. In this paper, we address this gap. We use a classic Bayesian reasoning task as a testbed for evaluating whether allowing users to interact with a static visualization can improve their reasoning. Through two crowdsourced studies, we show that adding interaction to a static Bayesian reaso
Negative / Null Result ReportMedicine
Bakhshalipoor, Bolandi, Nahidi et al. · 2026 · Scientific reports
This study evaluated the effects of double nanoemulsions of saffron petal extract (DN-SPE), stabilized with soybean (SPI) and pea protein isolates (PPI), alone or combined with Lepidium sativum L. seed gum (LSG) (SL or PL), on the quality…
View details →DOI: 10.1038/s41598-026-52693-3 Negative / Null Result ReportMedicine
Wang, Li, Zhang et al. · 2026 · Child development
This study examines how center-based parenting interventions aimed at improving early child development in rural China affect the mental health of caregivers. Data from an analytic sample of 615 caregiver-child dyads (children aged 6 to 24…
View details →DOI: 10.1093/chidev/aacag099 Negative / Null Result ReportMedicine
Eminoğlu · 2026 · Food science & nutrition
In this study, yogurt formulations with paraprobiotic (heat inactivated Lactobacillus acidophilus ) and postbiotic (autolyzed and dried Saccharomyces cerevisiae ) additions were developed to improve the techno-functional properties of…
View details →DOI: 10.1002/fsn3.71787 Negative / Null Result ReportOpen accessComputer Science
Joris Dannemann, Gero Junike · 2025 · arXiv
Batch normalization is one of the most important regularization techniques for neural networks, significantly improving training by centering the layers of the neural network. There have been several attempts to provide a theoretical justification for batch ormalization. Santurkar and Tsipras (2018) [How does batch normalization help optimization? Advances in neural information rocessing systems, 31] claim that batch normalization improves initialization. We provide a counterexample showing that this claim s not true, i.e., batch normalization does not improve initialization.
Negative / Null Result ReportOpen accessComputer Science
Cheng Tang, Andrew Arnold · 2020 · arXiv
Recently, Nogueira et al. [2019] proposed a new approach to document expansion based on a neural Seq2Seq model, showing significant improvement on short text retrieval task. However, this approach needs a large amount of in-domain training data. In this paper, we show that this neural document expansion approach can be effectively adapted to standard IR tasks, where labels are scarce and many long documents are present.
