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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.

1934 results for "Mpro" · page 25 of 65

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 ReportMedicine

Quality Improvement Analysis of Operative Regimen on Urinary Tract Infections.

Bonglack, Carrel-Lammert, Hoehn et al. · 2026 · Urogynecology (Philadelphia, Pa.)

Acute urinary tract infections (UTIs) are common after prolapse and anti-incontinence surgery, with incidence rates varying from 14% to 64%. The objective was to decrease rates of symptomatic urinary tract infections in patients undergoing…

View details →DOI: 10.1097/spv.0000000000001742
Negative / Null Result ReportOpen accessComputer Science

Self-Consistency Falls Short! The Adverse Effects of Positional Bias on Long-Context Problems

Adam Byerly, Daniel Khashabi · 2024 · arXiv

Self-consistency (SC) improves the performance of large language models (LLMs) across various tasks and domains that involve short content. However, does this support its effectiveness for long-context problems? We challenge the assumption that SC's benefits generalize to long-context settings, where LLMs often struggle with position bias, the systematic over-reliance on specific context regions-which hinders their ability to utilize information effectively from all parts of their context. Through comprehensive experimentation with varying state-of-the-art models, tasks, and SC formulations, w

Negative / Null Result ReportMedicine

Patient Trust in Healthcare Providers among People on Methadone Maintenance Treatment Using Methamphetamine in Vietnam.

Vu, Nguyen, Nguyen et al. · 2026 · Substance use & misuse

Patient trust in healthcare providers (PTP) is critical for improving treatment adherence and outcomes in substance use disorders. As concurrent opioid and methamphetamine use increasingly complicates methadone maintenance treatment (MMT),…

View details →DOI: 10.1080/10826084.2026.2676993
Negative / Null Result ReportMedicine

Association Between Early Versus Delayed Outpatient Follow-Up After Hospital Discharge and Short-Term Healthcare Utilization Among ICU Survivors.

Oletu, Oladimeji, Osueni et al. · 2026 · Cureus

Intensive care unit (ICU) survivors experience high rates of healthcare utilization after hospital discharge, including readmissions and emergency department (ED) visits. Timely outpatient follow-up has been proposed to improve care…

View details →DOI: 10.7759/cureus.107746
Negative / Null Result ReportMedicine

Reliability and patient-centered feasibility of the Gross Motor Function Measure in children diagnosed with central nervous system tumor.

Mantovani, Chagas, Horiquini-Barbosa · 2026 · Developmental neurorehabilitation

Children diagnosed with central nervous system (CNS) tumors frequently present with persistent motor impairments that compromise independence and participation. Although the Gross Motor Function Measure (GMFM-88) is widely used in…

View details →DOI: 10.1080/17518423.2026.2679487
Negative / Null Result ReportOpen accessComputer Science

Adaptation Odyssey in LLMs: Why Does Additional Pretraining Sometimes Fail to Improve?

Fırat Öncel, Matthias Bethge, Beyza Ermis et al. · 2024 · arXiv

In the last decade, the generalization and adaptation abilities of deep learning models were typically evaluated on fixed training and test distributions. Contrary to traditional deep learning, large language models (LLMs) are (i) even more overparameterized, (ii) trained on unlabeled text corpora curated from the Internet with minimal human intervention, and (iii) trained in an online fashion. These stark contrasts prevent researchers from transferring lessons learned on model generalization and adaptation in deep learning contexts to LLMs. To this end, our short paper introduces empirical ob

Negative / Null Result ReportMedicine

The effectiveness of vitrified zygote banking for managing the severe diminished ovarian reserve in infertile women: A retrospective cohort study.

Huang, Tsai, Lin et al. · 2026 · Taiwanese journal of obstetrics & gynecology

A higher oocyte yield is generally associated with improved outcomes in assisted reproductive technology (ART). Vitrification enables the accumulation of oocytes, zygotes, or embryos across multiple cycles, offering a potential strategy to…

View details →DOI: 10.1016/j.tjog.2025.06.010
Negative / Null Result ReportOpen accessComputer Science

Towards Geo-Culturally Grounded LLM Generations

Piyawat Lertvittayakumjorn, David Kinney, Vinodkumar Prabhakaran et al. · 2025 · arXiv

Generative large language models (LLMs) have demonstrated gaps in diverse cultural awareness across the globe. We investigate the effect of retrieval augmented generation and search-grounding techniques on LLMs' ability to display familiarity with various national cultures. Specifically, we compare the performance of standard LLMs, LLMs augmented with retrievals from a bespoke knowledge base (i.e., KB grounding), and LLMs augmented with retrievals from a web search (i.e., search grounding) on multiple cultural awareness benchmarks. We find that search grounding significantly improves the LLM p

Negative / Null Result ReportMedicine

Telemedicine-Assisted vs Conventional Telephone Instruction in Cardiopulmonary Resuscitation: The TACTIC Cluster Randomized Trial.

Riyapan, Laopran, Chantanakomes et al. · 2026 · Resuscitation

Dispatcher-assisted cardiopulmonary resuscitation (DA-CPR) has been shown to increase bystander CPR rates and improve outcomes after out-of-hospital cardiac arrest (OHCA). However, dispatchers cannot directly visualize the scene, which may…

View details →DOI: 10.1016/j.resuscitation.2026.111191
Failed Experiment ReportOpen accessComputer Science

How to Fine-Tune a Reasoning Model? A Teacher-Student Cooperation Framework to Synthesize Student-Consistent SFT Data

Zixian Huang, Kaichen Yang, Xu Huang et al. · 2026 · arXiv

A widely adopted strategy for model enhancement is to use synthetic data generated by a stronger model for supervised fine-tuning (SFT). However, for emerging reasoning models like Qwen3-8B, this approach often fails to improve reasoning capabilities and can even lead to a substantial drop in performance. In this work, we identify substantial stylistic divergence between teacher generated data and the distribution of student as a major factor impacting SFT. To bridge this gap, we propose a Teacher-Student Cooperation Data Synthesis framework (TESSY), which interleaves teacher and student model

Negative / Null Result ReportMedicine

Effectiveness of intravenous infusion protocol in improving quality of care and reducing complications among hospitalized patients.

Ani, Hameed · 2026 · Wiadomosci lekarskie (Warsaw, Poland : 1960)

Aim: This study aimed to evaluate the effectiveness of a structured intravenous infusion protocol in improving the quality of care and reducing IV-related complications among hospitalized patients. Materials and Methods: A purposive sample…

View details →DOI: 10.36740/wlek/219896
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 accessEngineering

From KAN to GR-KAN: Advancing Speech Enhancement with KAN-Based Methodology

Haoyang Li, Yuchen Hu, Chen Chen et al. · 2024 · arXiv

Deep neural network (DNN)-based speech enhancement (SE) usually uses conventional activation functions, which lack the expressiveness to capture complex multiscale structures needed for high-fidelity SE. Group-Rational KAN (GR-KAN), a variant of Kolmogorov-Arnold Networks (KAN), retains KAN's expressiveness while improving scalability on complex tasks. We adapt GR-KAN to existing DNN-based SE by replacing dense layers with GR-KAN layers in the time-frequency (T-F) domain MP-SENet and adapting GR-KAN's activations into the 1D CNN layers in the time-domain Demucs. Results on Voicebank-DEMAND sho

Negative / Null Result ReportOpen accessComputer Science

The Adverse Effects of Omitting Records in Differential Privacy: How Sampling and Suppression Degrade the Privacy--Utility Tradeoff (Long Version)

Àlex Miranda-Pascual, Javier Parra-Arnau, Thorsten Strufe · 2026 · arXiv

Sampling is renowned for its privacy amplification in differential privacy (DP), and is often assumed to improve the utility of a DP mechanism by allowing a noise reduction. In this paper, we further show that this last assumption is flawed: When measuring utility at equal privacy levels, sampling as preprocessing consistently yields penalties due to utility loss from omitting records over all canonical DP mechanisms -- Laplace, Gaussian, exponential, and report noisy max -- , as well as recent applications of sampling, such as clustering. Extending this analysis, we investigate suppression as

Negative / Null Result ReportOpen accessMedicine

Mechanical Tuning of the Cell Microenvironment Using a Biomimetic Hydrogel System for Articular Cartilage Tissue Engineering.

van Mourik M, Spierings J, Koca P et al. · 2026 · Journal of tissue engineering and regenerative medicine

Providing a functional pericellular matrix (PCM) by fine-tuning the microenvironment of the articular chondrocytes (ACs) can greatly improve the outcomes of articular cartilage tissue engineering. While harvesting ACs with their PCM…

View details →DOI: 10.1155/term/9947868
Negative / Null Result ReportOpen accessComputer Science

Uncovering the Impact of Chain-of-Thought Reasoning for Direct Preference Optimization: Lessons from Text-to-SQL

Hanbing Liu, Haoyang Li, Xiaokang Zhang et al. · 2025 · arXiv

Direct Preference Optimization (DPO) has proven effective in complex reasoning tasks like math word problems and code generation. However, when applied to Text-to-SQL datasets, it often fails to improve performance and can even degrade it. Our investigation reveals the root cause: unlike math and code tasks, which naturally integrate Chain-of-Thought (CoT) reasoning with DPO, Text-to-SQL datasets typically include only final answers (gold SQL queries) without detailed CoT solutions. By augmenting Text-to-SQL datasets with synthetic CoT solutions, we achieve, for the first time, consistent and

Negative / Null Result ReportOpen accessMedicine

Effect of implant position on clinical outcomes of two implant overdentures: a 3-year randomized clinical trial.

Raafat MH, Mourad KE, Elsyad MA · 2026 · BMC oral health

Background Reviewing the literature, the optimal implant position for 2-implant retained mandibular overdentures, which would be associated with improved peri-implant tissues, higher retention values, and better patient satisfaction,…

View details →DOI: 10.1186/s12903-026-08441-0
Negative / Null Result ReportOpen accessMathematics

ScoreStop: Gradient-based early stopping using functional score tests

Oliver J. Hines, Christian L. Hines · 2026 · arXiv

Gradient boosted decision trees require a stopping rule to avoid overfitting. The standard rule monitors a validation loss and stops if the loss fails to improve for a fixed patience period. However, the patience parameter has no interpretable scale and validation losses can be noisy or implicitly defined by a user-specified gradient. We propose ScoreStop, a gradient-based early-stopping rule that casts the stopping decision at each iteration as a test of the null hypothesis that the current predictor is the population risk minimizer. We use a functional score test, computed on validation data

Negative / Null Result ReportOpen accessMedicine

'To improve is to change'-but is it safe? A single surgeon's transition from lateral to vertical hemispherotomy.

Salim O, Chari A, Tahir MZ · 2026 · Child's nervous system : ChNS : official journal of the International Society for Pediatric Neurosurgery

Purpose Hemispherotomy is an established treatment for children with drug-resistant epilepsy. Recent reports have suggested a superiority of outcomes with the vertical approach compared to the traditional lateral approach. This study…

View details →DOI: 10.1007/s00381-026-07353-2
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 Report

Under-correction is not advisable in valgus knee and lateral approach is more feasible than medial approach to achieve this: A 5-year follow-up study

Li S, Chai H, Bao W et al. · 2026 · Preprint

Abstract Background: It is commonly recommended to restore the mechanical axis to within –0° ± 3° in valgus knee. However, the situation is quite different when the alignment is –3° or 3° in the presence of a compromised MCL in Ranawat…

View details →DOI: 10.21203/rs.3.rs-9715753/v1
Negative / Null Result ReportOpen accessComputer Science

InsCLR: Improving Instance Retrieval with Self-Supervision

Zelu Deng, Yujie Zhong, Sheng Guo et al. · 2021 · arXiv

This work aims at improving instance retrieval with self-supervision. We find that fine-tuning using the recently developed self-supervised (SSL) learning methods, such as SimCLR and MoCo, fails to improve the performance of instance retrieval. In this work, we identify that the learnt representations for instance retrieval should be invariant to large variations in viewpoint and background etc., whereas self-augmented positives applied by the current SSL methods can not provide strong enough signals for learning robust instance-level representations. To overcome this problem, we propose InsCL

Negative / Null Result ReportOpen accessMedicine

Dexmedetomidine for improving postpartum sleep quality following cesarean section in women: a randomized controlled trial.

Gao J, Hu CC, Wang XY et al. · 2026 · Frontiers in medicine

Background Perinatal sleep disturbance is highly prevalent among women undergoing elective cesarean section. Dexmedetomidine has been proven effective in improving sleep quality in patients undergoing general surgery, and this study aimed…

View details →DOI: 10.3389/fmed.2026.1823100
Negative / Null Result ReportOpen accessComputer Science

Not How Many, But Which: Parameter Placement in Low-Rank Adaptation

Arijit Sehanobish, Charles Lovering · 2026 · arXiv

We study the \textit{parameter placement problem}: given a fixed budget of $k$ trainable entries within the B matrix of a LoRA adapter (A frozen), does the choice of which $k$ matter? Under supervised fine-tuning, random and informed subsets achieve comparable performance. Under GRPO on base models, random placement fails to improve over the base model, while gradient-informed placement recovers standard LoRA accuracy. This regime dependence traces to gradient structure: SFT gradients are low-rank and directionally stable, so any subset accumulates coherent updates; GRPO gradients are high-ran