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
Shufan Wang, Yixiao Song, Andrew Drozdov et al. · 2023 · arXiv
In this paper, we study the generation quality of interpolation-based retrieval-augmented language models (LMs). These methods, best exemplified by the KNN-LM, interpolate the LM's predicted distribution of the next word with a distribution formed from the most relevant retrievals for a given prefix. While the KNN-LM and related methods yield impressive decreases in perplexity, we discover that they do not exhibit corresponding improvements in open-ended generation quality, as measured by both automatic evaluation metrics (e.g., MAUVE) and human evaluations. Digging deeper, we find that interp
Negative / Null Result ReportOpen accessComputer Science
Thomas Vogel, Chinh Tran, Lars Grunske · 2019 · arXiv
In search-based software engineering we often use popular heuristics with default configurations, which typically lead to suboptimal results, or we perform experiments to identify configurations on a trial-and-error basis, which may lead to better results for a specific problem. To obtain better results while avoiding trial-and-error experiments, a fitness landscape analysis is helpful in understanding the search problem, and making an informed decision about the heuristics. In this paper, we investigate the search problem of test suite generation for mobile applications (apps) using SAPIENZ w
Negative / Null Result ReportOpen accessPhysics
B. Megyeri, A. Lampis, G. Harvie et al. · 2017 · arXiv
We discuss the prospects for enhancing absorption and scattering of light from a weakly coupled atom in a high-finesse optical cavity by adding a medium with large, positive group index of refraction. The slow-light effect is known to narrow the cavity transmission spectrum and increase the photon lifetime, but the quality factor of the cavity may not be increased in a metrologically useful sense. Specifically, detection of the weakly coupled atom through either cavity ringdown measurements or the Purcell effect fails to improve with the addition of material slow light. A single-atom model of
Negative / Null Result ReportOpen accessComputer Science
Roland S. Zimmermann, Thomas Klein, Wieland Brendel · 2023 · arXiv
In light of the recent widespread adoption of AI systems, understanding the internal information processing of neural networks has become increasingly critical. Most recently, machine vision has seen remarkable progress by scaling neural networks to unprecedented levels in dataset and model size. We here ask whether this extraordinary increase in scale also positively impacts the field of mechanistic interpretability. In other words, has our understanding of the inner workings of scaled neural networks improved as well? We use a psychophysical paradigm to quantify one form of mechanistic inter
Negative / Null Result ReportOpen accessComputer Science
Yu Eric Qian, Wilson S. Geisler, Xue-Xin Wei · 2025 · arXiv
Previous studies have compared neural activities in the visual cortex to representations in deep neural networks trained on image classification. Interestingly, while some suggest that their representations are highly similar, others argued the opposite. Here, we propose a new approach to characterize the similarity of the decision strategies of two observers (models or brains) using decision variable correlation (DVC). DVC quantifies the image-by-image correlation between the decoded decisions based on the internal neural representations in a classification task. Thus, it can capture task-rel
Negative / Null Result ReportOpen accessComputer Science
Kaiyuan Li, Jing-Cheng Pang, Yang Yu · 2026 · arXiv
Reinforcement learning from verifiable rewards (RLVR) stimulates the thinking processes of large language models (LLMs), substantially enhancing their reasoning abilities on verifiable tasks. It is often assumed that similar gains should transfer to general question answering (GQA), but this assumption has not been thoroughly validated. To assess whether RLVR automatically improves LLM performance on GQA, we propose a Cross-Generation evaluation framework that measures the quality of intermediate reasoning by feeding the generated thinking context into LLMs of varying capabilities. Our evaluat
Negative / Null Result ReportOpen accessComputer Science
Courtney Celian, Partha Ryali, Valentino Wilson et al. · 2024 · arXiv
Background: Gravity confounds arm movement ability in post-stroke hemiparesis. Reducing its influence allows effective practice leading to recovery. Yet, there is a scarcity of wearable devices suitable for personalized use across diverse therapeutic activities in the clinic. Objective: In this study, we investigated the safety, feasibility, and efficacy of anti-gravity therapy using the ExoNET device in post-stroke participants. Methods: Twenty chronic stroke survivors underwent six, 45-minute occupational therapy sessions while wearing the ExoNET, randomized into either the treatment (ExoNET
Negative / Null Result ReportOpen accessComputer Science
J. C. Caillon, J. Labarsouque · 1993 · arXiv
In the calculation of the $K^+$-nucleus cross sections, the coupling of the mesons exchanged between the $K^+$ and the target nucleons to the polarization of the Fermi sea has been taken into account. This polarization has been calculated in the one-loop approximation but summed up to all orders (RPA-type calculation). This effect is found to be rather important but does not improve the agreement with experiment.
Negative / Null Result ReportOpen accessPhysics
Maria Patricia Rouelli Sabino, Sze Ter Lim, Michael Tran · 2014 · arXiv
We show by vector network analyzer ferromagnetic resonance measurements that low Gilbert damping α down to 0.006 can be achieved in perpendicularly magnetized MgO/CoFeB/MgO thin films with ultra-thin insertions of Ta in the CoFeB layer. While increasing the number of Ta insertions allows thicker CoFeB layers to remain perpendicular, the effective areal magnetic anisotropy does not improve with more insertions, and also comes with an increase in α.
Negative / Null Result ReportOpen accessComputer Science
Paolo Bellomo, C. R. Stroud, · 1998 · arXiv
We study the dispersion of the "temporally stable" coherent states for the hydrogen atom introduced by Klauder. These are states which under temporal evolution by the hydrogen atom Hamiltonian retain their coherence properties. We show that in the hydrogen atom such wave packets do not move quasi-classically; i.e., they do not follow with no or little dispersion the Keplerian orbits of the classical electron. The poor quantum-classical correspondence does not improve in the semiclassical limit.
Negative / Null Result ReportOpen accessComputer Science
R. N. Stevenson, A. R. R. Carvalho, J. J. Hope · 2010 · arXiv
We examine the theoretical limits of the generation of entanglement in a damped coupled ion-cavity system using jump-based feedback. Using Raman transitions to produce entanglement between ground states reduces the necessary feedback bandwidth, but does not improve the overall effect of the spontaneous emission on the final entanglement. We find that the fidelity of the resulting entanglement will be limited by the asymmetries produced by vibrations in the trap, but that the concurrence remains above 0.88 for realistic ion trap sizes.
Negative / Null Result ReportOpen accessPhysics
Yuto Urano, Xue Mengsong, Kenji Watanabe et al. · 2023 · arXiv
We investigate the valley coherence in high and low-quality monolayer MoSe2 by polarization-resolved photoluminescence spectroscopy. The observed valley coherence is on the order of 10 % regardless of the sample quality, proving that the suppression of extrinsic effects does not improve the valley coherence. The valley decoherence time estimated based on the valley coherence time and exciton lifetime is sub-picosecond at the longest, which suggests that intrinsic scattering sources, such as phonons, strongly limit the valley coherence.
Negative / Null Result ReportOpen accessComputer Science
Jose A. R. Cembranos · 2010 · arXiv
There is a non-trivial four-derivative extension of the gravitational spectrum that is free of ghosts and phenomenologically viable. It is the so called $R^2$-gravity since it is defined by the only addition of a term proportional to the square of the scalar curvature. Just the presence of this term does not improve the ultraviolet behaviour of Einstein gravity but introduces one additional scalar degree of freedom that can account for the dark matter of our Universe.
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 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
