Negative / Null Result ReportOpen accessMathematics
Utkarsh, Chris Elrod, Yingbo Ma et al. · 2022 · arXiv
Numerically solving ordinary differential equations (ODEs) is a naturally serial process and as a result the vast majority of ODE solver software are serial. In this manuscript we developed a set of parallelized ODE solvers using extrapolation methods which exploit "parallelism within the method" so that arbitrary user ODEs can be parallelized. We describe the specific choices made in the implementation of the explicit and implicit extrapolation methods which allow for generating low overhead static schedules to then exploit with optimized multi-threaded implementations. We demonstrate that wh
Negative / Null Result ReportOpen accessPhysics
Andrew C. Collazzi, Bradley E. Schaefer · 2008 · arXiv
Firmani et al. proposed a new Gamma Ray Burst (GRB) luminosity relation that showed a significant improvement over the L_iso-E_peak relation. The new proposed relation simply modifies the E_peak value by multiplying it by a power of T_0.45, where T_0.45 is a particular measure of the GRB duration. We begin by reproducing the results of Firmani for his 19 bursts. We then test the Firmani relation for the same 19 bursts except that we use independently measured values for L_iso, T_0.45, and E_peak, and we find that the relation deteriorates substantially. We further test the relation by using 60
Failed Experiment ReportOpen accessComputer Science
Sándor Kisfaludi-Bak, Jesper Nederlof, Erik Jan van Leeuwen · 2018 · arXiv
The Planar Steiner Tree problem is one of the most fundamental NP-complete problems as it models many network design problems. Recall that an instance of this problem consists of a graph with edge weights, and a subset of vertices (often called terminals); the goal is to find a subtree of the graph of minimum total weight that connects all terminals. A seminal paper by Erickson et al. [Math. Oper. Res., 1987] considers instances where the underlying graph is planar and all terminals can be covered by the boundary of $k$ faces. Erickson et al. show that the problem can be solved by an algorithm
Negative / Null Result ReportOpen accessPhysics
Alexander Contreras-Payares, Pablo G. Lustemberg, M. Verónica Ganduglia-Pirovano · 2025 · arXiv
The vibrational frequency of carbon monoxide (CO) adsorbed on ceria-based catalysts serves as a sensitive probe for identifying exposed surface facets, provided that experimental reference data on well-defined single-crystal surfaces and reliable theoretical assignments are available. Previous studies have shown that the hybrid DFT approach using the HSE06 functional yields good agreement with experimental observations, whereas the generalized gradient approximation (GGA) with PBE+U does not. In this work, we assess the performance of different exchange-correlation functionals by comparing the
Negative / Null Result ReportOpen accessComputer Science
Seyed Amir Kasaei, Arash Marioriyad, Mahbod Khaleti et al. · 2026 · arXiv
Large Vision-Language Models (LVLMs) have achieved remarkable proficiency in explicit visual recognition, effectively describing what is directly visible in an image. However, a critical cognitive gap emerges when the visual input serves only as a clue rather than the answer. We identify that current models struggle with the complex, multi-step reasoning required to solve problems where information is not explicitly depicted. Successfully solving a rebus puzzle requires a distinct cognitive workflow: the model must extract visual and textual attributes, retrieve linguistic prior knowledge (suc
Negative / Null Result ReportOpen accessPhysics
Alberto Nardin, Eddy Ardonne, Leonardo Mazza · 2022 · arXiv
We prove a generic spin-statistics relation for the fractional quasiparticles that appear in abelian quantum Hall states on the disk. The proof is based on an efficient way for computing the Berry phase acquired by a generic quasiparticle translated in the plane along a circular path, and on the crucial fact that once the gauge-invariant generator of rotations is projected onto a Landau level, it fractionalizes among the quasiparticles and the edge. Using these results we define a measurable quasiparticle fractional spin that satisfies the spin-statistics relation. As an application, we predic
Negative / Null Result ReportOpen accessComputer Science
Tristan Piater, Niklas Penzel, Gideon Stein et al. · 2024 · arXiv
A substantial body of research has focused on developing systems that assist medical professionals during labor-intensive early screening processes, many based on convolutional deep-learning architectures. Recently, multiple studies explored the application of so-called self-attention mechanisms in the vision domain. These studies often report empirical improvements over fully convolutional approaches on various datasets and tasks. To evaluate this trend for medical imaging, we extend two widely adopted convolutional architectures with different self-attention variants on two different medical
Negative / Null Result ReportOpen accessComputer Science
Yining Lu, Dixuan Wang, Tianjian Li et al. · 2024 · arXiv
As LLMs become increasingly prevalent, it is interesting to consider how ``creative'' these models can be. From cognitive science, creativity consists of at least two key characteristics: \emph{convergent} thinking (purposefulness to achieve a given goal) and \emph{divergent} thinking (adaptability to explore new environments or constraints) \citep{runco2003critical}. In this work, we introduce a framework for quantifying LLM creativity that incorporates the two design ingredients: (1) We introduce DENIAL PROMPTING which pushes LLMs to develop more creative solutions to a given problem by incr
Negative / Null Result ReportOpen accessComputer Science
Jason Dury · 2026 · arXiv
Dense retrieval systems rank passages by embedding similarity to a query, but multi-hop questions require passages that are associatively related through shared reasoning chains. We introduce Association-Augmented Retrieval (AAR), a lightweight transductive reranking method that trains a small MLP (4.2M parameters) to learn associative relationships between passages in embedding space using contrastive learning on co-occurrence annotations. At inference time, AAR reranks an initial dense retrieval candidate set using bi-directional association scoring. On HotpotQA, AAR improves passage Recall@
Negative / Null Result ReportOpen accessComputer Science
Xiaolong Jin, Xuandong Zhao, Wenbo Guo et al. · 2026 · arXiv
Reinforcement learning with verifiable rewards (RLVR) has driven substantial progress in large language model reasoning, but relies on ground-truth supervision that is costly or infeasible, especially in coding tasks. Recent work addresses this by deriving rewards from a model's own signals, such as majority voting or confidence-based scores, achieving notable success on mathematical reasoning benchmarks. However, code generation poses distinct challenges: programs are structurally complex, semantically equivalent solutions may differ syntactically, and verification typically requires executio
Negative / Null Result ReportOpen accessMathematics
Nguyen Ngoc Hung · 2015 · arXiv
A classical theorem of John Thompson on character degrees asserts that if the degree of every ordinary irreducible character of a finite group $G$ is 1 or divisible by a prime $p$, then $G$ has a normal $p$-complement. We obtain a significant improvement of this result by considering the average of $p'$-degrees of irreducible characters. We also consider fields of character values and prove several improvements of earlier related results.
Negative / Null Result ReportOpen accessEngineering
Max Langtry, Vijja Wichitwechkarn, Rebecca Ward et al. · 2024 · arXiv
Data is required to develop forecasting models for use in Model Predictive Control (MPC) schemes in building energy systems. However, data is costly to both collect and exploit. Determining cost optimal data usage strategies requires understanding of the forecast accuracy and resulting MPC operational performance it enables. This study investigates the performance of both simple and state-of-the-art machine learning prediction models for MPC in multi-building energy systems using a simulated case study with historic building energy data. The impact on forecast accuracy of measures to improve m
Negative / Null Result ReportOpen accessComputer Science
Jimmy Lin, Daniel Campos, Nick Craswell et al. · 2021 · arXiv
Leaderboards are a ubiquitous part of modern research in applied machine learning. By design, they sort entries into some linear order, where the top-scoring entry is recognized as the "state of the art" (SOTA). Due to the rapid progress being made in information retrieval today, particularly with neural models, the top entry in a leaderboard is replaced with some regularity. These are touted as improvements in the state of the art. Such pronouncements, however, are almost never qualified with significance testing. In the context of the MS MARCO document ranking leaderboard, we pose a specific
Negative / Null Result ReportOpen accessPhysics
Jordan M. Slagowski, Erik Pearson, Rajit Tummala et al. · 2025 · arXiv
Techniques for preclinical intensity modulated radiation therapy are being developed to improve translation by replicating the clinical paradigm. This study presents the first treatment planning comparison between small animal IMRT (SA-IMRT) and three-dimensional conformal radiotherapy (CRT) in a model application, oxygen-guided dose painting of tumor hypoxia, using actual mouse data. A novel compensator-based platform was employed to generate SA-IMRT and CRT plans with 2-15 beam angles for seventeen mice with fibrosarcoma tumors. The whole tumor received a dose of 22.5 Gy, with a simultaneous
Negative / Null Result ReportOpen accessPhysics
Timothy Garn, Philip Best · 2010 · arXiv
We investigate how the typical dust extinction of H-alpha luminosity from a star-forming galaxy depends upon star formation rate (SFR), metallicity and stellar mass independently, using a sample of ~90,000 galaxies from Data Release 7 of the Sloan Digital Sky Survey (SDSS). We measure extinctions directly from the Balmer decrement of each source, and while higher values of extinction are associated with an increase in any of the three parameters, we demonstrate that the fundamental property that governs extinction is stellar mass. After this mass-dependent relationship is removed, there is ver
Negative / Null Result ReportOpen accessComputer Science
Jason Z Wang · 2026 · arXiv
We introduce MIRROR, a benchmark comprising eight experiments across four metacognitive levels that evaluates whether large language models can use self-knowledge to make better decisions. We evaluate 16 models from 8 labs across approximately 250,000 evaluation instances using five independent behavioral measurement channels. Core experiments are run across the full model roster; experiments with specialized infrastructure requirements report explicitly marked model subsets. We find two phenomena with direct implications for agentic deployment: (1) compositional self-prediction fails universa
Negative / Null Result ReportOpen accessComputer Science
Mohd Zaki, Jayadeva, Mausam et al. · 2023 · arXiv
Information extraction and textual comprehension from materials literature are vital for developing an exhaustive knowledge base that enables accelerated materials discovery. Language models have demonstrated their capability to answer domain-specific questions and retrieve information from knowledge bases. However, there are no benchmark datasets in the materials domain that can evaluate the understanding of the key concepts by these language models. In this work, we curate a dataset of 650 challenging questions from the materials domain that require the knowledge and skills of a materials st
Negative / Null Result ReportOpen accessComputer Science
Mohammed Hossny, Julie Iskander, Mohammed Attia et al. · 2020 · arXiv
In this paper, we propose enhancing actor-critic reinforcement learning agents by parameterising the final actor layer which produces the actions in order to accommodate the behaviour discrepancy of different actuators, under different load conditions during interaction with the environment. We propose branching the action producing layer in the actor to learn the tuning parameter controlling the activation layer (e.g. Tanh and Sigmoid). The learned parameters are then used to create tailored activation functions for each actuator. We ran experiments on three OpenAI Gym environments, i.e. Pend
Failed Experiment ReportOpen accessPhysics
Ying-Dan Wang, Xiao-Bo Yan, Stefano Chesi · 2016 · arXiv
Using a perturbative treatment, we quantify the influence of non-adiabatic leakage and system dissipation on the transfer fidelity of a stimulated Raman adiabatic passage (STIRAP) process. We find that, optimizing transfer time rather than coupling profiles, leads to a significant improvement of the transfer fidelity. The upper bound of the fidelity has been found as a simple analytical function of system cooperativities. We also provide a systematic approach to reach this upper bound efficiently.
Negative / Null Result ReportOpen accessMathematics
Kunyu Guo, Hansong Huang · 2013 · arXiv
In studying commutants of analytic Toeplitz operators, Thomson proved a remarkable theorem which states that under a mild condition, the commutant of an analytic Toeplitz operator is equal to that of Toeplitz operator defined by a finite Blaschke product. Cowen gave an significant improvement of Thosom's result. In this paper, we will present examples in Cowen's class which does not lie in Thomson's class.
Negative / Null Result ReportOpen accessComputer Science
Amir Yunus, Peng Rend Gay, Oon Teng Lee · 2025 · arXiv
This study examines the development and deployment of a Generative AI proof-of-concept (POC) designed to support lecturers in a vocational education setting in Singapore. Employing a user-centred, mixed-methods design process, we co-developed an AI chatbot with lecturers to address recurring instructional challenges during exam preparation, specifically managing repetitive questions and scaling feedback delivery. The POC achieved its primary operational goals: lecturers reported streamlined workflows, reduced cognitive load, and observed improved student confidence in navigating course content
Negative / Null Result ReportOpen accessPhysics
Aishrila Mazumder, Laura Wolz, Zhaoting Chen et al. · 2025 · arXiv
We present the first results of the HI intensity mapping power spectrum analysis with the MeerKAT International GigaHertz Tiered Extragalactic Exploration (MIGHTEE) survey. We use data covering $\sim$4 square degrees in the COSMOS field using a frequency range 962.5 MHz to 1008.42 MHz, equivalent to HI emission in $0.4<z<0.48$. The data consists of 15 pointings with a total of 94.2 hours on-source. We verify the suitability of the MIGHTEE data for HI intensity mapping by testing for residual systematics across frequency, baselines and pointings. We also vary the window used for HI signal measu
Negative / Null Result ReportOpen accessAgricultural and Biological Sciences
Muhammad Zeeshan, Saima Masood, Saima Ashraf et al. · 2023 · arXiv
The objective of the current study was to assess the effect of dietary supplementations of mannan-oligosaccharide, live yeast, and a combination of these two additives on growth performance, histo-morphology of the rumen, and muscle morphometric attributes in buffalo calves. A total of twenty buffalo calves (average weight of 25 kg) having 3 months of age were distributed according to a complete randomized design. All animals were individually stalled in the shed and were fed ad-libitum. Experimental animals were divided into four groups for 67 days: Control group(without the inclusion of diet
Negative / Null Result ReportOpen accessComputer Science
Andru P. Twinanda, Didier Mutter, Jacques Marescaux et al. · 2016 · arXiv
The tool presence detection challenge at M2CAI 2016 consists of identifying the presence/absence of seven surgical tools in the images of cholecystectomy videos. Here, we propose to use deep architectures that are based on our previous work where we presented several architectures to perform multiple recognition tasks on laparoscopic videos. In this technical report, we present the tool presence detection results using two architectures: (1) a single-task architecture designed to perform solely the tool presence detection task and (2) a multi-task architecture designed to perform jointly phase
Negative / Null Result ReportOpen accessComputer Science
Antoni Ramos-Buades, Patricia Schmidt, Geraint Pratten et al. · 2020 · arXiv
The current paradigm for constructing waveforms from precessing compact binaries is to first construct a waveform in a non-inertial, co-precessing binary source frame followed by a time-dependent rotation to map back to the physical, inertial frame. A key insight in the construction of these models is that the co-precessing waveform can be effectively mapped to some equivalent aligned spin waveform. Secondly, the time-dependent rotation implicitly introduces $m$-mode mixing, necessitating an accurate description of higher-order modes in the co-precessing frame. We assess the efficacy of this m
Negative / Null Result Report
Mohamad Arief Rafsanjani · 2022 · AL-ISHLAH: Jurnal Pendidikan
This research aims to look into theories about teacher competency, educational background, and training, where the hypothesis claims that educational background and training involvement has a positive link with teacher competence. This is…
View details →DOI: 10.35445/alishlah.v14i3.1704 Negative / Null Result ReportOpen accessComputer Science
Dou Liu, Ying Long, Sophia Zuoqiu et al. · 2025 · arXiv
Creating high-quality clinical Chains-of-Thought (CoTs) is crucial for explainable medical Artificial Intelligence (AI) while constrained by data scarcity. Although Large Language Models (LLMs) can synthesize medical data, their clinical reliability remains unverified. This study evaluates the reliability of LLM-generated CoTs and investigates prompting strategies to enhance their quality. In a blinded comparative study, senior clinicians in Assisted Reproductive Technology (ART) evaluated CoTs generated via three distinct strategies: Zero-shot, Random Few-shot (using shallow examples), and Se
Negative / Null Result ReportOpen accessComputer Science
J. Rehacek, Z. Hradil, M. Dusek et al. · 1999 · arXiv
An experimental comparison of several operational phase concepts is presented. In particular, it is shown that statistically motivated evaluation of experimental data may lead to a significant improvement in phase fitting upon the conventional Noh, Fouge'res and Mandel procedure. The analysis is extended to the asymptotic limit of large intensities, where a strong evidence in favor of multi--dimensional estimation procedures has been found.
Replication FailureOpen accessMathematics
Georg Ostrovski · 2011 · arXiv
Let X and Y be compact, simply connected and locally connected subsets of R^2, and let f : X -> Y be a homeomorphism isotopic to the identity on X. Generalizing Brouwer's plane translation theorem for self-maps of the plane, we prove that f has no recurrent (in particular, no periodic) points if it has no fixed points.
Negative / Null Result ReportOpen accessPhysics
Rebecca J. Smethurst, Karen L. Masters, Brooke D. Simmons et al. · 2021 · arXiv
The galaxy population is strongly bimodal in both colour and morphology, and the two measures correlate strongly, with most blue galaxies being late-types (spirals) and most early-types, typically ellipticals, being red. This observation has led to the use of colour as a convenient selection criteria to make samples which are then labelled by morphology. Such use of colour as a proxy for morphology results in necessarily impure and incomplete samples. In this paper, we make use of the morphological labels produced by Galaxy Zoo to measure how incomplete and impure such samples are, considering
