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Failure-mode index

Search what already failed

A searchable index of real negative results, null findings, and replication failures from the published literature — so you can learn what didn't work before repeating it.

WASTE indexes published research — it does not host or republish full papers. Each entry is a metadata record (title, authors, DOI) compiled from open scholarly databases, with the abstract shown in full only where the paper is openly licensed (e.g. Creative Commons); otherwise a short excerpt is shown for reference under fair use. WASTE classifies each work by failure type; classifications are automated and approximate.

1894 results for "Mpro" · page 22 of 64

Negative / Null Result ReportOpen accessAgricultural and Biological Sciences

Modeling the mobility of living organisms in heterogeneous landscapes: Does memory improve foraging success?

Denis Boyer, Peter D. Walsh · 2010 · arXiv

Thanks to recent technological advances, it is now possible to track with an unprecedented precision and for long periods of time the movement patterns of many living organisms in their habitat. The increasing amount of data available on single trajectories offers the possibility of understanding how animals move and of testing basic movement models. Random walks have long represented the main description for micro-organisms and have also been useful to understand the foraging behaviour of large animals. Nevertheless, most vertebrates, in particular humans and other primates, rely on sophistic

Negative / Null Result ReportOpen accessComputer Science

Does Editing Improve Answer Quality on Stack Overflow? A Data-Driven Investigation

Saikat Mondal, Chanchal K. Roy · 2025 · arXiv

High-quality answers in technical Q&A platforms like Stack Overflow (SO) are crucial as they directly influence software development practices. Poor-quality answers can introduce inefficiencies, bugs, and security vulnerabilities, and thus increase maintenance costs and technical debt in production software. To improve content quality, SO allows collaborative editing, where users revise answers to enhance clarity, correctness, and formatting. Several studies have examined rejected edits and identified the causes of rejection. However, prior research has not systematically assessed whether acce

Negative / Null Result ReportOpen accessComputer Science

Does Multimodality Improve Recommender Systems as Expected? A Critical Analysis and Future Directions

Hongyu Zhou, Yinan Zhang, Aixin Sun et al. · 2025 · arXiv

Multimodal recommendation systems are increasingly popular for their potential to improve performance by integrating diverse data types. However, the actual benefits of this integration remain unclear, raising questions about when and how it truly enhances recommendations. In this paper, we propose a structured evaluation framework to systematically assess multimodal recommendations across four dimensions: Comparative Efficiency, Recommendation Tasks, Recommendation Stages, and Multimodal Data Integration. We benchmark a set of reproducible multimodal models against strong traditional baseline

Negative / Null Result ReportOpen accessPhysics

Does H2O improve the catalytic activity of Au1-4/MgO towards CO oxidation?

Martin Amft, Natalia V. Skorodumova · 2011 · arXiv

The present density functional theory study addresses the question whether the presence of H2O influences the catalytic activity of small gold clusters, Au1-4/MgO(100), towards the oxidation of carbon monoxide. To this end, we studied the (co-)adsorption of H2O and CO/O2 on these gold clusters. The ground state structures in the presence of all three molecular species, that we found, are Au1O2/MgO and Au2-4CO/MgO with H2O adsorbed on the surface in the proximity of the clusters-molecule complex. In this configuration the catalytic activity of Au1-4/MgO is indifferent to the presence of H2O. We

Negative / Null Result ReportOpen accessComputer Science

The Wisdom of Deliberating AI Crowds: Does Deliberation Improve LLM-Based Forecasting?

Paul Schneider, Amalie Schramm · 2025 · arXiv

Structured deliberation has been found to improve the performance of human forecasters. This study investigates whether a similar intervention, i.e. allowing LLMs to review each other's forecasts before updating, can improve accuracy in large language models (GPT-5, Claude Sonnet 4.5, Gemini Pro 2.5). Using 202 resolved binary questions from the Metaculus Q2 2025 AI Forecasting Tournament, accuracy was assessed across four scenarios: (1) diverse models with distributed information, (2) diverse models with shared information, (3) homogeneous models with distributed information, and (4) homogene

Negative / Null Result ReportOpen accessPhysics

Forget metamaterial: It does not improve sound absorption performance as it claims

Chao Shen, Yu Liu, Tianquan Tang et al. · 2023 · arXiv

The term `sub-wavelength' is commonly used to describe innovative sound-absorbing structures usually labeled as `metamaterials'. Such structures, however, inherently do not bring groundbreaking advancements. This study addresses the limitations imposed by the thickness criterion of Yang et al. by introducing the concept of equivalent mass-spring-damping parameters within the resonator framework. This innovative approach introduces an index of `half-absorption bandwidth' to effectively overcome the thickness restriction. Four practical cases are then presented to correct prevalent misleading co

Negative / Null Result ReportOpen accessComputer Science

Indefinite causal order strategy does not improve the estimation of group action

Masahito Hayashi · 2025 · arXiv

We consider estimation of unknown unitary operation when the set of possible unitary operations is given by a projective unitary representation of a compact group. We show that neither indefinite causal order strategy nor adaptive strategy improves the performance of this estimation when error function satisfies group covariance. That is, the optimal parallel strategy gives the optimal performance even under indefinite causal order strategy and adaptive strategy. To study this problem, we newly introduce the concept of generalized positive operator valued measure (GPOVM), and its convariance c

Negative / Null Result ReportOpen accessComputer Science

What does RL improve for Visual Reasoning? A Frankenstein-Style Analysis

Xirui Li, Ming Li, Tianyi Zhou · 2026 · arXiv

Reinforcement learning (RL) with verifiable rewards has become a standard post-training stage for boosting visual reasoning in vision-language models, yet it remains unclear what capabilities RL actually improves compared with supervised fine-tuning as cold-start initialization (IN). End-to-end benchmark gains conflate multiple factors, making it difficult to attribute improvements to specific skills. To bridge the gap, we propose a Frankenstein-style analysis framework including: (i) functional localization via causal probing; (ii) update characterization via parameter comparison; and (iii) t

Negative / Null Result ReportOpen accessComputer Science

Scale Alone Does not Improve Mechanistic Interpretability in Vision Models

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 accessPhysics

Why material slow light does not improve cavity-enhanced atom detection

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

Does Diversity Improve the Test Suite Generation for Mobile Applications?

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 accessComputer Science

KNN-LM Does Not Improve Open-ended Text Generation

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 Report

Modified string test to improve and confirm by molecular characterization for bacterial identification

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 Report

Abstract 17917: Is Small Change Significant? Association of Small Differences in Life's Simple 7 and Mortality: the Reasons for Geographic and Racial Differences in Stroke (REGARDS) Cohort

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 accessComputer Science

Haptic human-human interaction does not improve individual visuomotor adaptation

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

Understanding Why Generalized Reweighting Does Not Improve Over ERM

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 Report

Dampak Sosial Ekonomi pada Keluaga Penerima Manfaat (KPM) Program Keluarga Harapan (PKH) Exit Mandiri di Kecamatan Pagelaran Kabuoaten Pringsewu dalam Perspektif The Most Significant Change Technique (MSCt)

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

Does preregistration improve the credibility of research findings?

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

Does Weighting Improve Matrix Factorization for Recommender Systems?

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

The Poincaré Inequality does not improve with blow-up

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 ReportOpen accessEconomics, Econometrics and Finance

Does Anxiety Improve Economic Decision-Making?

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

How can I find my own voice through my instrument

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 ReportOpen accessComputer Science

When is dataset cartography ineffective? Using training dynamics does not improve robustness against Adversarial SQuAD

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 ReportOpen accessMathematics

Preregistration does not improve the transparent evaluation of severity in Popper's philosophy of science or when deviations are allowed

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 ReportOpen accessComputer Science

Does Interaction Improve Bayesian Reasoning with Visualization?

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 ReportOpen accessComputer Science

Batch normalization does not improve initialization

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

Neural document expansion for ad-hoc information retrieval

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.