Negative / Null Result ReportOpen accessMathematics
William Paul Heath, Joaquin Carrasco, Jingfan Zhang · 2021 · arXiv
We present a phase condition under which there is no suitable multiplier for a given continuous-time plant. The condition can be derived from either the duality approach or from the frequency interval approach. The condition has a simple graphical interpretation, can be tested in a numerically efficient manner and may be applied systematically. Numerical examples show significant improvement over existing results in the literature. The condition is used to demonstrate a third order system with delay that is a counterexample to the Kalman Conjecture.
Negative / Null Result ReportOpen accessComputer Science
S. Schneider, J. Haidenbauer, C. Hanhart et al. · 2002 · arXiv
We study pion absorption on 3He employing trinucleon wave functions calculated from modern realistic NN interactions (Paris, CD Bonn). Even though the use of the new wave functions leads to a significant improvement over older calculations with regard to both cross section and polarization data, there are hints that polarization data with quasifree kinematics cannot be described by just two-nucleon absorption mechanisms.
Negative / Null Result ReportOpen accessPhysics
Ingvild Dalehaug, Kirsten Nygaard Bolstad, Daniel Aadnevik et al. · 2017 · arXiv
Purpose: Siemens has developed several iterative reconstruction (IR) algorithms on their CT scanners. SAFIRE is available on most of their CT scanners. The latest algorithm, ADMIRE, is available on their newest high-end CT scanners. The aim of our study was to compare the noise reduction properties of the two IR algorithms using objective methods. Methods and Materials: The homogeneous module of the Catphan phantom was scanned on a Siemens AS+ and a Siemens Flash CT scanner using an axial abdomen protocol with fixed tube current at two dose levels. The images were reconstructed with an abdomen
Negative / Null Result ReportOpen accessPhysics
Dominic M. Bowman, Daniel L. Holdsworth · 2019 · arXiv
Context. Modern space telescopes are currently providing high-precision light curves for a large fraction of the sky, such that many new variable stars are being discovered. However, some stars have periodic variability with periods of order minutes and require high-cadence photometry to probe the physical mechanisms responsible. A cadence of less than a minute is often required to remove Nyquist ambiguities and confirm rapid variability which forces observers to obtain high-cadence ground-based photometry. Aims. We aim to provide a modern software package to reduce ground-based photometric ti
Negative / Null Result ReportOpen accessEconomics, Econometrics and Finance
Francisco Rodríguez · 2022 · arXiv
We revisit the results of a recent paper by Equipo Anova, who claim to find evidence of an improvement in Venezuelan imports of food and medicines associated with the adoption of U.S. financial sanctions towards Venezuela in 2017. We show that their results are consequence of data coding errors and questionable methodological choices, including the use an unreasonable functional form that implies a counterfactual of negative imports in the absence of sanctions, the omission of data accounting for four-fifths of the country's food imports at the time of sanctions and incorrect application of re
Negative / Null Result ReportOpen accessPhysics
Sarbani Basu, H. M. Antia · 1999 · arXiv
Ring diagram analysis can be used to study large scale velocity fields in the outer part of the solar convection zone. All previous works assume that the peak profiles in the solar oscillation power spectrum are symmetric. However, it has now been demonstrated that the peaks are not symmetric. In this work we study how the explicit use of asymmetric peak profiles in ring-diagram analysis influences the estimated velocity fields. We find that the use of asymmetric profiles leads to significant improvement in the fits, but the estimated velocity fields are not substantially different from those
Negative / Null Result ReportOpen accessPhysics
Xian-Yu Wang, Yong-Hao Wang, Songhu Wang et al. · 2021 · arXiv
We present 127 new transit light curves for 39 hot Jupiter systems, obtained over the span of five years by two ground-based telescopes. A homogeneous analysis of these newly collected light curves together with archived spectroscopic, photometric, and Doppler velocimetric data using EXOFASTv2 leads to a significant improvement in the physical and orbital parameters of each system. All of our stellar radii are constrained to accuracies of better than 3\%. The planetary radii for 37 of our 39 targets are determined to accuracies of better than $5\%$. Compared to our results, the literature ecce
Negative / Null Result ReportOpen accessComputer Science
Andreas Hocker · 2001 · arXiv
The recent precise measurement of the muon magnetic anomaly (g-2)_{mu} at BNL opens a window into possible new physics, provided the contribution from hadronic vacuum polarization is well understood. This talk summarizes the development in the evaluation of the leading order hadronic contributions. Significant improvement has been achieved in a series of analyses which is presented historically in three steps: (1), use of tau spectral functions in addition to e+e- cross sections, (2), extended use of perturbative QCD and (3), application of QCD sum rule techniques. The uncertainties, in partic
Negative / Null Result ReportOpen accessComputer Science
Shreya Chandrasekhar, Chieh-Yang Huang, Ting-Hao 'Kenneth' Huang · 2023 · arXiv
The rapid growth of scientific publications, particularly during the COVID-19 pandemic, emphasizes the need for tools to help researchers efficiently comprehend the latest advancements. One essential part of understanding scientific literature is research aspect classification, which categorizes sentences in abstracts to Background, Purpose, Method, and Finding. In this study, we investigate the impact of different datasets on model performance for the crowd-annotated CODA-19 research aspect classification task. Specifically, we explore the potential benefits of using the large, automatically
Negative / Null Result ReportOpen accessComputer Science
Egor Shevchenko, Elena Bruches · 2026 · arXiv
Data quality is a critical factor in the effectiveness of machine learning models. Label errors, present even in widely used benchmarks, introduce noise into training data and reduce model generalization. In this work, we conduct a comparative analysis of two automatic label error detection methods - Confident Learning and Dataset Cartography - on three Russian text classification corpora of varying size, number of classes, and domain: ru_emotion_e-culture (49,123 examples, emotion classification), RuCoLA (8,524 examples, linguistic acceptability), and TERRa (2,337 examples, textual entailment
Negative / Null Result ReportOpen accessPhysics
Mohamed M. Fadlallah, Ulrich Eckern · 2017 · arXiv
The structural, electronic, and optical properties of metal (Si, Ge, Sn, and Pb) mono- and co-doped anatase TiO$_{2}$ nanotubes are investigated, in order to elucidate their potential for photocatalytic applications. It is found that Si doped TiO$_{2}$ nanotubes are more stable than those doped with Ge, Sn, or Pb. All dopants lower the band gap, except the (Ge, Sn) co-doped structure, the decrease depending on the concentration and the type of dopant. Correspondingly, a redshift in the optical properties for all kinds of dopings is obtained. Even though a Pb mono- and co-doped TiO$_{2}$ nanotu
Negative / Null Result ReportOpen accessPhysics
Chris Pankow, Laura Sampson, Leah Perri et al. · 2016 · arXiv
The detection of electromagnetic counterparts to gravitational waves has great promise for the investigation of many scientific questions. It has long been hoped that in addition to providing extra, non-gravitational information about the sources of these signals, the detection of an electromagnetic signal in conjunction with a gravitational wave could aid in the analysis of the gravitational signal itself. That is, knowledge of the sky location, inclination, and redshift of a binary could break degeneracies between these extrinsic, coordinate-dependent parameters and the physical parameters,
Negative / Null Result ReportOpen accessPhysics
Sergei Manzhos, Pavlo Golub · 2020 · arXiv
We study the dependence of kinetic energy densities (KED) on density-dependent variables that have been suggested in previous works on kinetic energy functionals (KEF) for orbital-free DFT (OF-DFT). We focus on the role of data distribution and on data and regressor selection. We compare unweighted and weighted linear and Gaussian process regressions of KED for light metals and a semiconductor. We find that good quality linear regression resulting in good energy-volume dependence is possible over density-dependent variables suggested in previous literature. This is achieved with weighted fitti
Negative / Null Result ReportOpen accessComputer Science
Mario Sanz-Guerrero, Katharina von der Wense · 2025 · arXiv
In-context learning (ICL) has transformed the use of large language models (LLMs) for NLP tasks, enabling few-shot learning by conditioning on labeled examples without finetuning. Despite its effectiveness, ICL is prone to errors, especially for challenging examples. With the goal of improving the performance of ICL, we propose corrective in-context learning (CICL), an approach that incorporates a model's incorrect predictions alongside ground truth corrections into the prompt, aiming to enhance classification accuracy through self-correction. However, contrary to our hypothesis, extensive exp
Negative / Null Result ReportOpen accessComputer Science
Hui Zhang, Kiduk Yang, Elin Jacob · 2015 · arXiv
Despite limited success, information retrieval (IR) systems today are not intelligent or reliable. IR systems return poor search results when users formulate their information needs into incomplete or ambiguous queries (i.e., weak queries). Therefore, one of the main challenges in modern IR research is to provide consistent results across all queries by improving the performance on weak queries. However, existing IR approaches such as query expansion are not overly effective because they make little effort to analyze and exploit the meanings of the queries. Furthermore, word sense disambiguati
Negative / Null Result ReportOpen accessComputer Science
Philippe Laban, Tobias Schnabel, Jennifer Neville · 2026 · arXiv
Large Language Models (LLMs) are poised to disrupt knowledge work, with the emergence of delegated work as a new interaction paradigm (e.g., vibe coding). Delegation requires trust - the expectation that the LLM will faithfully execute the task without introducing errors into documents. We introduce DELEGATE-52 to study the readiness of AI systems in delegated workflows. DELEGATE-52 simulates long delegated workflows that require in-depth document editing across 52 professional domains, such as coding, crystallography, and music notation. Our large-scale experiment with 19 LLMs reveals that cu
Negative / Null Result ReportOpen accessComputer Science
Gokhan Alkac, Luca Basanisi, Ercan Kilicarslan et al. · 2017 · arXiv
We revisit the problem of the bulk-boundary unitarity clash in 2 + 1 dimensional gravity theories, which has been an obstacle in providing a viable dual two-dimensional conformal field theory for bulk gravity in anti-de Sitter (AdS) spacetime. Chiral gravity, which is a particular limit of cosmological topologically massive gravity (TMG), suffers from pertur- bative log-modes with negative energies inducing a non-unitary logarithmic boundary field theory. We show here that any f(R) extension of TMG does not improve the situation. We also study the perturbative modes in the metric formulation o
Negative / Null Result ReportOpen accessComputer Science
Tom Kouwenhoven, Max Peeperkorn, Bram van Dijk et al. · 2024 · arXiv
Natural language has the universal properties of being compositional and grounded in reality. The emergence of linguistic properties is often investigated through simulations of emergent communication in referential games. However, these experiments have yielded mixed results compared to similar experiments addressing linguistic properties of human language. Here we address representational alignment as a potential contributing factor to these results. Specifically, we assess the representational alignment between agent image representations and between agent representations and input images.
Negative / Null Result ReportOpen accessComputer Science
Luigi Giannelli, Ralf Betzholz, Laura Kreiner et al. · 2016 · arXiv
We theoretically analyse the cooling dynamics of a high-Q mode of a mechanical resonator, when the structure is also an optical cavity and is coupled with a NV center. The NV center is driven by a laser and interacts with the cavity photon field and with the strain field of the mechanical oscillator, while radiation pressure couples mechanical resonator and cavity field. Starting from the full master equation we derive the rate equation for the mechanical resonator's motion, whose coefficients depend on the system parameters and on the noise sources. We then determine the cooling regime, the c
Negative / Null Result ReportOpen accessComputer Science
Elias Hossain, Md Mehedi Hasan Nipu, Maleeha Sheikh et al. · 2025 · arXiv
Clinical language models often assign high confidence to incorrect predictions, particularly in high-severity and out-of-distribution cases. We present MedBayes-Lite, a retraining-free uncertainty governance layer for transformer-based clinical predictors. It combines Monte Carlo dropout, predictive calibration, and confidence-guided abstention to defer low-confidence predictions for human review, adding no trainable parameters. Evaluated on MedMCQA and MedQA-USMLE, MedBayes-Lite reduces expected calibration error by 0.23 to 0.33 and drives harmful overconfident errors (confident, incorrect, h
Negative / Null Result ReportOpen accessComputer Science
Lei Wang · 2026 · arXiv
The endpoint region $ζ\to1$ of the NLO forward jet vertex has not been systematically separated from BFKL energy-scale terms in Mueller-Navelet phenomenology. Starting from the small-cone NLO vertex, we isolate the quark and gluon plus distributions and construct a BFKL-aware threshold matching scheme that preserves exact NLO accuracy. The conservative Scheme-II exponent resums only the ordinary endpoint logarithms and leaves the $χ(n,γ)\ln\bar N$ term in the fixed-order coefficient, avoiding an uncontrolled tower of mixed endpoint-BFKL logarithms. In fixed-baseline CMS tests, this matched ver
Negative / Null Result ReportOpen accessPhysics
Jaroslaw Zdebik · 2008 · arXiv
The work was carried out in the framework of the KLOE collaboration studying the decays of the phi meson produced in the DAFNE accelerator in the collisions of electron and positron. The main aim of this thesis was investigation of the influence of the merging and splitting of clusters in decays with the high multiplicity of gamma quanta, which are at most biased by these effects. For this aim we implemented the full geometry and realistic material composition of the barrel electromagnetic calorimeter in FLUKA package. The prepared Monte Carlo based simulation program permits to achieve a fast
Negative / Null Result ReportOpen accessComputer Science
Silas L. Fong, Vincent Y. F. Tan · 2017 · arXiv
This paper investigates the asymptotic expansion for the maximum rate of fixed-length codes over a parallel Gaussian channel with feedback under the following setting: A peak power constraint is imposed on every transmitted codeword, and the average error probability of decoding the transmitted message is non-vanishing as the blocklength increases. It is well known that the presence of feedback does not increase the first-order asymptotics of the channel, i.e., capacity, in the asymptotic expansion, and the closed-form expression of the capacity can be obtained by the well-known water-filling
Negative / Null Result ReportOpen accessComputer Science
Jennifer Haase, Jana Gonnermann-Müller, See Heng Yim et al. · 2026 · arXiv
Large language model (LLM)-based simulations of clinical patients are increasingly used for research and training, yet their validity requires persona stability: coherent maintenance of an assigned psychological profile across and within conversations. We evaluate this prerequisite using eating disorder personas grounded in five published case vignettes, a dual-assessment framework (self-report + independent observer ratings), and validated psychometric instruments (EDE-Q) with known ground-truth scores. Across six LLMs and two experiments (between-conversation stability (Exp. I) and within-co
Negative / Null Result ReportOpen accessComputer Science
Vitaly Kurin, Maximilian Igl, Tim Rocktäschel et al. · 2020 · arXiv
Multitask Reinforcement Learning is a promising way to obtain models with better performance, generalisation, data efficiency, and robustness. Most existing work is limited to compatible settings, where the state and action space dimensions are the same across tasks. Graph Neural Networks (GNN) are one way to address incompatible environments, because they can process graphs of arbitrary size. They also allow practitioners to inject biases encoded in the structure of the input graph. Existing work in graph-based continuous control uses the physical morphology of the agent to construct the inpu
Negative / Null Result ReportOpen accessPhysics
Atsushi Taruya, Takahiro Nishimichi, Donghui Jeong · 2021 · arXiv
Perturbation theory (PT) has been used to interpret the observed nonlinear large-scale structure statistics at the quasi-linear regime. To facilitate the PT-based analysis, we have presented the GridSPT algorithm, a grid-based method to compute the nonlinear density and velocity fields in standard perturbation theory (SPT) from a given linear power spectrum. Here, we further put forward the approach by taking the redshift-space distortions into account. With the new implementation, we have, for the first time, generated the redshift-space density field to the fifth order and computed the next-
Negative / Null Result ReportOpen accessComputer Science
Jin Zeng, Yang Liu, Gene Cheung et al. · 2022 · arXiv
A graph convolutional network (GCN) employs a graph filtering kernel tailored for data with irregular structures. However, simply stacking more GCN layers does not improve performance; instead, the output converges to an uninformative low-dimensional subspace, where the convergence rate is characterized by the graph spectrum -- this is the known over-smoothing problem in GCN. In this paper, we propose a sparse graph learning algorithm incorporating a new spectrum prior to compute a graph topology that circumvents over-smoothing while preserving pairwise correlations inherent in data. Specifica
Negative / Null Result ReportOpen accessComputer Science
Wentao Zhao, Dalin Zhou, Xinguo Qiu et al. · 2020 · arXiv
Graph neural networks (GNNs) have been investigated for potential applicability in multiple fields that employ graph data. However, there are no standard training settings to ensure fair comparisons among new methods, including different model architectures and data augmentation techniques. We introduce a standard, reproducible benchmark to which the same training settings can be applied for node classification. For this benchmark, we constructed 9 datasets, including both small- and medium-scale datasets from different fields, and 7 different models. We design a k-fold model assessment strate
Negative / Null Result ReportOpen accessComputer Science
Charles Jin, Melinda Sun, Martin Rinard · 2021 · arXiv
We propose a novel clustering mechanism based on an incompatibility property between subsets of data that emerges during model training. This mechanism partitions the dataset into subsets that generalize only to themselves, i.e., training on one subset does not improve performance on the other subsets. Leveraging the interaction between the dataset and the training process, our clustering mechanism partitions datasets into clusters that are defined by--and therefore meaningful to--the objective of the training process. We apply our clustering mechanism to defend against data poisoning attacks,
Negative / Null Result ReportOpen accessPhysics
Fabien Robineau, Frédéric Boy, Jean-Pierre Orliaguet et al. · 2006 · arXiv
Performing minimal-invasive surgical punctures require guiding a needle toward an intracorporeal clinically-defined target. As this technique does not involve cutting the body open, a visualization system is employed to provide the surgeon with indirect visual spatial information about the intracorporeal positions of the tool. One may consider that such systems reduce the ergonomics of the situation as they generate a decorrelation between the actual movement of the needle and the displayed information about this movement. The present study aims at assessing the guidance of an intracorporeal p
