Negative / Null Result ReportOpen accessComputer Science
Andrei Liviu Nicolicioiu, Mohammad Pezeshki, Aaron Courville · 2026 · arXiv
On-policy self-distillation achieves strong pass@1 accuracy by using a single model as both teacher and student, with the teacher conditioned on a correct demonstration to provide dense token-level feedback. We show that this could come at a hidden cost: rollout diversity decreases and pass@k curves flatten (i.e., generating more rollouts fails to improve accuracy). We trace this to compounding biases in the design of self-distillation with sampled demonstrations. The teacher scores each student rollout while conditioned on a sampled correct rollout, channeling its feedback through the model's
Negative / Null Result ReportMedicine
Yao, Mamone, Wu et al. · 2026 · Frontiers in psychology
Age-related declines in muscle strength are partly attributable to altered neural drive and agonist-antagonist coordination. This study aimed to evaluate the effects of motor imagery training (MIT) on maximal force production and…
View details →DOI: 10.3389/fpsyg.2026.1817866 Negative / Null Result ReportMedicine
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 ReportMedicine
Prajapati, Gupta, Mathew et al. · 2026 · The Indian journal of tuberculosis
Tuberculosis (TB) is a significant health issue in the world, and lack of health literacy has resulted in delayed care-seeking practices, non-compliance with treatment regimens, and subsequent stigma in communities with the infection. The…
View details →DOI: 10.1016/j.ijtb.2026.02.014 Negative / Null Result ReportOpen accessComputer Science
Lennart Luettgau, Vanessa Cheung, Magda Dubois et al. · 2025 · arXiv
People increasingly seek personal advice from large language models (LLMs), yet whether humans follow their advice, and its consequences for their well-being, remains unknown. In a longitudinal randomised controlled trial with a representative UK sample (N = 6,474), we found that up to 79% of participants who had a 20-minute discussion with one of three AI chatbots (GPT-4o, LLama-3.3-70B, Gemini 3 Pro) about health, careers or relationships subsequently reported following its advice. Advice-following remained above 60% even for high-stakes recommendations, suggesting that users only weakly cal
Negative / Null Result ReportMedicine
Trevethan, Doig, Patterson et al. · 2026 · Lymphology
ICG lymphography is a lymphatic imaging tool that can inform lymphedema treatment, including self-management. Self-management requires patient engagement in a multimodal treatment program. However, lack of knowledge about lymphedema,…
Negative / Null Result ReportOpen accessComputer Science
Ruth Cohen, Lu Feng, Ayala Bloch et al. · 2026 · arXiv
While natural-language explanations from large language models (LLMs) are widely adopted to improve transparency and trust, their impact on objective human-AI team performance remains poorly understood. We identify a Persuasion Paradox: fluent explanations systematically increase user confidence and reliance on AI without reliably improving, and in some cases undermining, task accuracy. Across three controlled human-subject studies spanning abstract visual reasoning (RAVEN matrices) and deductive logical reasoning (LSAT problems), we disentangle the effects of AI predictions and explanations u
Negative / Null Result ReportMedicine
Tsiotsios, Vamvakas, Labropoulou et al. · 2026 · Acta haematologica
Introduction Patients with homozygous β-thalassemia show continuously improved survival, which has contributed to the development of kidney complications, predominantly expressed as increased albuminuria. In particular, patients with…
View details →DOI: 10.1159/000552285 Negative / Null Result ReportOpen accessComputer Science
Amanpreet Singh, Mike D'Arcy, Arman Cohan et al. · 2022 · arXiv
Learned representations of scientific documents can serve as valuable input features for downstream tasks without further fine-tuning. However, existing benchmarks for evaluating these representations fail to capture the diversity of relevant tasks. In response, we introduce SciRepEval, the first comprehensive benchmark for training and evaluating scientific document representations. It includes 24 challenging and realistic tasks, 8 of which are new, across four formats: classification, regression, ranking and search. We then use this benchmark to study and improve the generalization ability o
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
Sheikh, Singh, Smith et al. · 2026 · Frontiers in cardiovascular medicine
The impact of catheter-directed thrombolysis (CDT), catheter-directed embolectomy (CDE) and surgical pulmonary embolectomy (SPE) on long term RV function among patients with acute PE remains unclear. We investigated the association of…
View details →DOI: 10.3389/fcvm.2026.1767184 Negative / Null Result ReportMedicine
Navidifar, Kaveh, Hosseini et al. · 2026 · Veterinary and animal science
Efficient estrus synchronization is important for improving reproductive performance in dairy herds; however, variations in ovarian activity among cows of different parities may influence responses to synchronization protocols. The present…
View details →DOI: 10.1016/j.vas.2026.100739 Negative / Null Result ReportOpen accessComputer Science
Chunliang Li, Tianze Cao, Sanyuan Zhao · 2026 · arXiv
Visual Autoregressive (VAR) modeling inefficiently applies a fixed computational depth to each position when generating high-resolution images. While existing methods accelerate inference by pruning tokens using frequency maps, their binary hard-pruning approach is fundamentally limited and fails to improve quality even with better frequency estimation. Observing that VAR models possess significant depth redundancy, we propose a paradigm shift from pruning entire tokens to adaptively allocating per-token computational depth. To this end, we introduce DepthVAR, a training-free framework that dy
Negative / Null Result ReportOpen accessComputer Science
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 ReportOpen accessComputer Science
Aaron B. Wagner, Nirmal V. Shende, Yücel Altuğ · 2019 · arXiv
We introduce a novel mechanism, called timid/bold coding, by which feedback can be used to improve coding performance. For a certain class of DMCs, called compound-dispersion channels, we show that timid/bold coding allows for an improved second-order coding rate compared with coding without feedback. For DMCs that are not compound dispersion, we show that feedback does not improve the second-order coding rate. Thus we completely determine the class of DMCs for which feedback improves the second-order coding rate. An upper bound on the second-order coding rate is provided for compound-dispersi
Negative / Null Result ReportOpen accessMedicine
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 accessAgricultural and Biological Sciences
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
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 ReportOpen accessComputer Science
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 Report
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 accessEngineering
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 accessMedicine
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
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
Wei C, An J, Lin Y et al. · 2026 · PeerJ
Background Badminton is a physically demanding sport requiring a combination of aerobic endurance, anaerobic power, agility, and explosive strength. Repeated sprint training (RST) has emerged as a time-efficient strategy for improving…
View details →DOI: 10.7717/peerj.21111 Negative / Null Result ReportOpen accessComputer Science
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
William Coley, Sree Rayavarapu, Jack H van der Meulen et al. · 2013 · PLoS ONE
BACKGROUND: Current treatments for idiopathic inflammatory myopathies (collectively called myositis) focus on the suppression of an autoimmune inflammatory response within the skeletal muscle. However, it has been observed that there is a poor correlation between the successful suppression of muscle inflammation and an improvement in muscle function. Some evidence in the literature suggests that metabolic abnormalities in the skeletal muscle underlie the weakness that continues despite successful immunosuppression. We have previously shown that decreased expression of a purine nucleotide cycle
View details →DOI: 10.1371/journal.pone.0065970 Negative / Null Result ReportOpen accessOphthalmology
V S Vijitha, Tarjani Vivek Dave, Somasheila I Murthy et al. · 2021 · Indian Journal of Ophthalmology
Purpose: To describe a series of sight-threatening ocular and adnexal involvement associated with dengue hemorrhagic fever and their treatment options. Methods: Retrospective, interventional, non-comparative case series. Medical records of patients who presented with ocular symptoms attributed to dengue hemorrhagic fever were reviewed. Demography, presenting features, and treatment outcomes were recorded. Outcome measures assessed included globe salvage, vision salvage, and visual improvement. The outcome was deemed as favorable if vision salvage was possible and unfavorable if the vision was
View details →DOI: 10.4103/ijo.ijo_1588_20 Negative / Null Result ReportOpen accessPublic aspects of medicine
Rob Horne, Caroline Sabin, Trudie Chalder et al. · 2025 · Programme Grants for Applied Research
Background Antiretroviral therapy has transformed human immunodeficiency virus infection intoa chronic condition associated with normal life expectancy. In the United Kingdom, the uptake of antiretroviral therapy is generally high, but a delay in starting antiretroviral therapy and non-adherence compromise the health and well-being of people living with human immunodeficiency virus, increase the risk of transmission of human immunodeficiency virus and increase National Health Service costs. Objectives The overall aim was to improve antiretroviral therapy uptake and adherence by addressing perc
View details →DOI: 10.3310/kppw8401 Negative / Null Result ReportOpen accessMathematics
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 accessComputer Science
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
