Negative / Null Result ReportOpen accessComputer Science
Stefano Rini · 2012 · arXiv
Proving capacity for networks without feedback or cooperation usually involves two fundamental random coding techniques: superposition coding and binning. Although conceptually very different, these two techniques often achieve the same performance, suggesting an underlying similarity. In this correspondence we propose a new random coding technique that generalizes superposition coding and binning and provides new insight on relationship among the two With this new theoretical tool, we derive new achievable regions for three classical information theoretical models: multi-access channel, broad
Negative / Null Result ReportOpen accessComputer Science
S. Pasini, G. S. Uhrig · 2008 · arXiv
We generalize the problem of the coherent control of small quantum systems to the case where the quantum bit (qubit) is subject to a fully general rotation. Following the ideas developed in Pasini et al (2008 Phys. Rev. A 77, 032315), the systematic expansion in the shortness of the pulse is extended to the case where the pulse acts on the qubit as a general rotation around an axis of rotation varying in time. The leading and the next-leading corrections are computed. For certain pulses we prove that the general rotation does not improve on the simpler rotation with fixed axis.
Negative / Null Result ReportOpen accessComputer Science
Ian Porada, Alessandro Sordoni, Jackie Chi Kit Cheung · 2021 · arXiv
Transformer models pre-trained with a masked-language-modeling objective (e.g., BERT) encode commonsense knowledge as evidenced by behavioral probes; however, the extent to which this knowledge is acquired by systematic inference over the semantics of the pre-training corpora is an open question. To answer this question, we selectively inject verbalized knowledge into the minibatches of a BERT model during pre-training and evaluate how well the model generalizes to supported inferences. We find generalization does not improve over the course of pre-training, suggesting that commonsense knowled
Negative / Null Result ReportOpen accessComputer Science
Mohamed S. Nafea, Karim G. Seddik, Mohammed Nafie et al. · 2012 · arXiv
In this work, we analyze the diversity gain region (DGR) of the single-antenna Rayleigh fading Z-Interference channel (ZIC). More specifically, we characterize the achievable DGR of the fixed-power split Han-Kobayashi (HK) approach under these assumptions. Our characterization comes in a closed form and demonstrates that the HK scheme with only a common message is a singular case, which achieves the best DGR among all HK schemes for certain multiplexing gains. Finally, we show that generalized time sharing, with variable rate and power assignments for the common and private messages, does not
Negative / Null Result ReportOpen accessComputer Science
Yunquan Dong, Zhengchuan Chen, Shanyun Liu et al. · 2018 · arXiv
We consider an M/M/1 update-and-decide system where Poisson distributed decisions are made based on the received updates. We propose to characterize the freshness of the received updates at decision epochs with Age upon Decisions (AuD). Under the first-come-first-served policy (FCFS), the closed form average AuD is derived. We show that the average AuD of the system is determined by the arrival rate and the service rate, and is independent of the decision rate. Thus, merely increasing the decision rate does not improve the timeliness of decisions. Nevertheless, increasing the arrival rate and
Negative / Null Result ReportOpen accessPhysics
M. H. S. Amin, Dmitri V. Averin, James A. Nesteroff · 2007 · arXiv
We have studied the decoherence properties of adiabatic quantum computation (AQC) in the presence of in general non-Markovian, e.g., low-frequency, noise. The developed description of the incoherent Landau-Zener transitions shows that the global AQC maintains its properties even for decoherence larger than the minimum gap at the anticrossing of the two lowest energy levels. The more efficient local AQC, however, does not improve scaling of the computation time with the number of qubits $n$ as in the decoherence-free case. The scaling improvement requires phase coherence throughout the computat
Failed Experiment ReportOpen accessComputer Science
Henrique K. Miyamoto, Sheng Yang · 2026 · arXiv
This paper studies random-coding error exponents of randomised list decoding, in which the decoder randomly selects $L$ messages with probabilities proportional to the decoding metric of the codewords. The exponents (or bounds) are given for mismatched, and then particularised to matched and universal decoding metrics. Two regimes are studied: for fixed list size, we derive an ensemble-tight random-coding error exponent, and show that, for the matched metric, it does not improve the error exponent of ordinary decoding. For list sizes growing exponentially with the block-length, we provide a no
Negative / Null Result ReportMedicine
Hansen-Lewis J, Marcus M · 2025 · American economic journal. Economic policy
Maritime shipping emits as much fine particulate matter as half of global road traffic. We are the first to measure the consequences of US maritime emissions standards on air quality, human health, racial exposure disparities, and…
View details →DOI: 10.1257/pol.20220626 Negative / Null Result ReportOpen accessEconomics, Econometrics and Finance
Alexander L. Brown, Daniel G. Stephenson, Rodrigo A. Velez · 2024 · arXiv
This paper experimentally evaluates four mechanisms intended to achieve the Uniform outcome in rationing problems (Sprumont, 1991). Our benchmark is the dominant-strategy, direct-revelation mechanism of the Uniform rule. A strategically equivalent mechanism that provides non-binding feedback during the reporting period greatly improves performance. A sequential revelation mechanism produces modest improvements despite not possessing dominant strategies. A novel, obviously strategy-proof mechanism, devised by Arribillaga et al. (2023), does not improve performance. We characterize each alternat
Methods Dead-EndOpen accessMathematics
Hao Luo, Alexandre Bouchard-Côté, Gabriela Cohen Freue et al. · 2016 · arXiv
We extend the constrained maximum likelihood estimation theory for parameters of a completely identified model, proposed by Aitchison and Silvey (1958), to parameters arising from a partially identified model. With a partially identified model, some parameters of the model may only be identified through constraints imposed by additional assumptions. We show that, under certain conditions, the constrained maximum likelihood estimator exists and locally maximize the likelihood function subject to constraints. We then study the asymptotic distribution of the estimator and propose a numerical algo
Negative / Null Result ReportOpen accessComputer Science
G. Chiribella, G. M. D'Ariano, P. Perinotti · 2008 · arXiv
A sequential network of quantum operations is efficiently described by its quantum comb, a non-negative operator with suitable normalization constraints. Here we analyze the case of networks enjoying symmetry with respect to the action of a given group of physical transformations, introducing the notion of covariant combs and testers, and proving the basic structure theorems for these objects. As an application, we discuss the optimal alignment of reference frames (without pre-established common references) with multiple rounds of quantum communication, showing that i) allowing an arbitrary am
Negative / Null Result ReportOpen accessComputer Science
M. Viviani, A. Kievsky, S. Rosati et al. · 2001 · arXiv
We present evidence that numerically accurate quantum calculations employing modern internucleon forces do not reproduce the proton analyzing power, A_y, for p-3He elastic scattering at low energies. These calculations underpredict new measured analyzing powers by approximately 30% at E_{c.m.} = 1.20 MeV and by 40% at E_{c.m.} = 1.69 MeV, an effect analogous to a well-known problem in p-d and n-d scattering. The calculations are performed using the complex Kohn variational principle and the (correlated) Hyperspherical Harmonics technique with full treatment of the Coulomb force. The inclusion
Negative / Null Result ReportOpen accessComputer Science
Pierre Epron, Adrien Coulet, Mehwish Alam · 2026 · arXiv
Despite their strong linguistic capabilities, Large Language Models (LLMs) are computationally demanding and require substantial resources for fine-tuning, which is unadapted to privacy and budget constraints of many healthcare settings. To address this, we present an experimental analysis focused on Biomedical Named Entity Recognition using lightweight LLMs, we evaluate the impact of different output formats on model performance. The results reveal that lightweight LLMs can achieve competitive performance compared to the larger models, highlighting their potential as lightweight yet effective
Failed Experiment ReportOpen accessPhysics
Jan Vavřín · 2025 · arXiv
Recently, the mapping approach to surface hopping (MASH) was proposed as a method to simulate the non-adiabatic dynamics of two-level systems. It was shown that the method possesses many desirable qualities, both theoretically and through numerical simulations. We explain this success by proving that, out of similar mapping methods, MASH dynamics is unique in guaranteeing correct thermalisation, but that many different "estimators" can be used on top of it. We also show that MASH can successfully calculate multi-time correlation functions, which can be used for the simulation of 2D spectra. We
Negative / Null Result ReportOpen accessComputer Science
Isabel Segura-Bedmar · 2023 · arXiv
This paper describes our participation in SemEval-2023 Task 10, whose goal is the detection of sexism in social media. We explore some of the most popular transformer models such as BERT, DistilBERT, RoBERTa, and XLNet. We also study different data augmentation techniques to increase the training dataset. During the development phase, our best results were obtained by using RoBERTa and data augmentation for tasks B and C. However, the use of synthetic data does not improve the results for task C. We participated in the three subtasks. Our approach still has much room for improvement, especiall
Negative / Null Result ReportOpen accessComputer Science
Amir Homayounirad, Enrico Liscio, Tong Wang et al. · 2025 · arXiv
Aggregating multiple annotations into a single ground truth label may hide valuable insights into annotator disagreement, particularly in tasks where subjectivity plays a crucial role. In this work, we explore methods for identifying subjectivity in recognizing the human values that motivate arguments. We evaluate two main approaches: inferring subjectivity through value prediction vs. directly identifying subjectivity. Our experiments show that direct subjectivity identification significantly improves the model performance of flagging subjective arguments. Furthermore, combining contrastive l
Negative / Null Result ReportOpen accessComputer Science
Fahd Ahmed Khan, Kamel Tourki, Mohamed-Slim Alouini et al. · 2013 · arXiv
This paper studies the impact of using outdated channel state information for relay selection on the performance of a network where two sources communicate with each other via fixed-gain amplifyand- forward relays. For a Rayleigh faded channel, closed-form expressions for the outage probability, moment generating function and symbol error rate are derived. Simulations results are also presented to corroborate the derived analytical results. It is shown that adding relays does not improve the performance if the channel is substantially outdated. Furthermore, relay location is also taken into co
Negative / Null Result ReportOpen accessComputer Science
Matthew Aitchison · 2019 · arXiv
Although reinforcement learning has made great strides recently, a continuing limitation is that it requires an extremely high number of interactions with the environment. In this paper, we explore the effectiveness of reusing experience from the experience replay buffer in the Deep Q-Learning algorithm. We test the effectiveness of applying learning update steps multiple times per environmental step in the VizDoom environment and show first, this requires a change in the learning rate, and second that it does not improve the performance of the agent. Furthermore, we show that updating less fr
Negative / Null Result ReportOpen accessMathematics
Subha Maity, Debarghya Mukherjee, Mikhail Yurochkin et al. · 2020 · arXiv
Many instances of algorithmic bias are caused by subpopulation shifts. For example, ML models often perform worse on demographic groups that are underrepresented in the training data. In this paper, we study whether enforcing algorithmic fairness during training improves the performance of the trained model in the \emph{target domain}. On one hand, we conceive scenarios in which enforcing fairness does not improve performance in the target domain. In fact, it may even harm performance. On the other hand, we derive necessary and sufficient conditions under which enforcing algorithmic fairness l
Negative / Null Result ReportOpen accessComputer Science
John S. Van Dyke, Zackary White, Gregory Quiroz · 2024 · arXiv
Zero-noise extrapolation (ZNE), a technique to estimate quantum circuit expectation values through noise scaling and extrapolation, is well-studied in the context of quantum computing. We examine the applicability of ZNE to the field of quantum sensing. Focusing on the problem of DC magnetometry using the Ramsey protocol, we show that the sensitivity (in the sense of the minimum detectable signal) does not improve upon using ZNE in the slope detection scheme. On the other hand, signals of sufficiently large magnitude can be estimated more accurately. Our results are robust across various noise
Negative / Null Result ReportOpen accessComputer Science
Baruch Lubinsky, Bekir Genc, Tshilidzi Marwala · 2008 · arXiv
Neural networks are powerful tools for classification and regression in static environments. This paper describes a technique for creating an ensemble of neural networks that adapts dynamically to changing conditions. The model separates the input space into four regions and each network is given a weight in each region based on its performance on samples from that region. The ensemble adapts dynamically by constantly adjusting these weights based on the current performance of the networks. The data set used is a collection of financial indicators with the goal of predicting the future platinu
Negative / Null Result ReportOpen accessComputer Science
Shouman Das, Syed A. Haque, Md. Iftekhar Tanveer · 2021 · arXiv
\emph{Topological data analysis} (TDA) has recently emerged as a new technique to extract meaningful discriminitve features from high dimensional data. In this paper, we investigate the possibility of applying TDA to improve the classification accuracy of public speaking rating. We calculated \emph{persistence image vectors} for the sentence embeddings of TEDtalk data and feed this vectors as additional inputs to our machine learning models. We have found a negative result that this topological information does not improve the model accuracy significantly. In some cases, it makes the accuracy
Negative / Null Result ReportOpen accessComputer Science
Hayato Arai, Yuuya Yoshida, Masahito Hayashi · 2019 · arXiv
We address perfect discrimination of two separable states. When available states are restricted to separable states, we can theoretically consider a larger class of measurements than the class of measurements allowed in quantum theory. The framework composed of the class of separable states and the above extended class of measurements is a typical example of general probabilistic theories. In this framework, we give a necessary and sufficient condition to discriminate two separable pure states perfectly. In particular, we derive measurements explicitly to discriminate two separable pure states
Negative / Null Result ReportOpen accessEconomics, Econometrics and Finance
Michael Pedersen · 2024 · arXiv
The present study applies observations of individual predictions of the first three releases of the US output growth rate to evaluate how the applied judgment affects prediction efficiency and accuracy as well as if judgment is persistent. While the first two issues have been assessed in other studies, there is little evidence on the formation of judgment in macroeconomic projections. Most of the forecasters produce unbiased predictions, but employing the median Bloomberg projection as baseline, it turns out that judgment generally does not improve accuracy. There seems to be persistence in th
Negative / Null Result ReportOpen accessComputer Science
Felix Leditzky, Debbie Leung, Graeme Smith · 2017 · arXiv
We determine both the quantum and the private capacities of low-noise quantum channels to leading orders in the channel's distance to the perfect channel. It has been an open problem for more than 20 years to determine the capacities of some of these low-noise channels such as the depolarizing channel. We also show that both capacities are equal to the single-letter coherent information of the channel, again to leading orders. We thus find that, in the low noise regime, super-additivity and degenerate codes have negligible benefit for the quantum capacity, and shielding does not improve the pr
Negative / Null Result ReportOpen accessMathematics
Alexander Tolmachev · 2024 · arXiv
Determining the maximal density $m_1(\mathbb{R}^2)$ of planar sets without unit distances is a fundamental problem in combinatorial geometry. This paper investigates lower bounds for this quantity. We introduce a novel approach to estimating $m_1(\mathbb{R}^2)$ by reformulating the problem as a Maximal Independent Set (MIS) problem on graphs constructed from flat torus, focusing on periodic sets with respect to two non-collinear vectors. Our experimental results, supported by theoretical justifications of proposed method, demonstrate that for a sufficiently wide range of parameters this approa
Negative / Null Result ReportMedicine
Chilundo, Xinavane, Huo et al. · 2026 · Frontiers in reproductive health
Despite national policies promoting adolescent- and youth-friendly health services, implementation gaps hinder improvements in adolescent sexual and reproductive health outcomes in Mozambique. S-NICE is a structured, participatory…
View details →DOI: 10.3389/frph.2026.1828528 Negative / Null Result ReportMedicine
Zhou, Wang, He et al. · 2026 · JACS Au
DNA origami placement (DOP) exploits shape complementarity between DNA nanostructures and lithographically patterned binding sites to achieve precise spatial positioning, offering a promising route for integrating bottom-up self-assembly…
View details →DOI: 10.1021/jacsau.6c00423 Negative / Null Result ReportMedicine
Boettger, Sedighi, Pallmann et al. · 2026 · Journal of the Intensive Care Society
Thyroid hormone alterations are common in critical illness and may reflect disease severity. Their prognostic significance in infarct-related cardiogenic shock remains incompletely defined. In this prospective cohort study from a…
View details →DOI: 10.1177/17511437261454174 Negative / Null Result ReportMedicine
Argaw, Jingili, Oyelere et al. · 2026 · JMIR XR and spatial computing
Anxiety-related symptoms are prevalent and can negatively affect concentration, motivation, and overall well-being. Traditional treatments such as cognitive behavioral therapy and medication work well for clinical anxiety disorders.…
View details →DOI: 10.2196/66713 