Negative / Null Result ReportOpen accessMathematics
Martina Zizza · 2024 · arXiv
In this paper we examine the discrete Shnirelman's inequality [Shnirelman A., 1985], which relates the $L^2$-distance of two discrete configurations of a fluid to the $L^1_tL^2_x$-norm of the vector field connecting them. Our proof is inspired by [Shnirelman A., 1985], where it was obtained $α=\frac{1}{64}$ in dimension $ν=2$, while here we get $α\geq\frac{2}{7}$. Moreover we prove that $α\geq\frac{1}{ν+1}$ for any dimension $ν\geq 3$. We point out that, even if this does not improve the bound in the continuous version, where it was proved that $α\geq\frac{2}{4+ν}$, with $ν\geq 3$, our bound i
Negative / Null Result ReportOpen accessComputer Science
Felix Krejca, Tobias Kietreiber, Alexander Buchelt et al. · 2025 · arXiv
The increasing volume of online discussions requires advanced automatic content moderation to maintain responsible discourse. While hate speech detection on social media is well-studied, research on German-language newspaper forums remains limited. Existing studies often neglect platform-specific context, such as user history and article themes. This paper addresses this gap by developing and evaluating binary classification models for automatic content moderation in German newspaper forums, incorporating contextual information. Using LSTM, CNN, and ChatGPT-3.5 Turbo, and leveraging the One Mi
Negative / Null Result ReportOpen accessComputer Science
Syed Assad, Mark Bradshaw, Ping Koy Lam · 2016 · arXiv
Amplification of quantum states is inevitably accompanied with the introduction of noise at the output. For protocols that are probabilistic with heralded success, noiseless linear amplification in theory may still possible. When the protocol is successful, it can lead to an output that is a noiselessly amplified copy of the input. When the protocol is unsuccessful, the output state is degraded and is usually discarded. Probabilistic protocols may improve the performance of some quantum information protocols, but not for metrology if the whole statistics is taken into consideration. We calcula
Negative / Null Result ReportOpen accessMathematics
Aihua Xia, Fuxi Zhang · 2011 · arXiv
Random events in space and time often exhibit a locally dependent structure. When the events are very rare and dependent structure is not too complicated, various studies in the literature have shown that Poisson and compound Poisson processes can provide adequate approximations. However, the accuracy of approximations does not improve or may even deteriorate when the mean number of events increases. In this paper, we investigate an alternative family of approximating point processes and establish Stein's method for their approximations. We prove two theorems to accommodate respectively the po
Negative / Null Result ReportOpen accessComputer Science
Peratham Wiriyathammabhum · 2023 · arXiv
In this report, we describe our Transformers for euphemism detection baseline (TEDB) submissions to a shared task on euphemism detection 2022. We cast the task of predicting euphemism as text classification. We considered Transformer-based models which are the current state-of-the-art methods for text classification. We explored different training schemes, pretrained models, and model architectures. Our best result of 0.816 F1-score (0.818 precision and 0.814 recall) consists of a euphemism-detection-finetuned TweetEval/TimeLMs-pretrained RoBERTa model as a feature extractor frontend with a Ki
Negative / Null Result ReportOpen accessEngineering
Jingqi Li, Anand Siththaranjan, Somayeh Sojoudi et al. · 2024 · arXiv
Autonomous agents should coordinate effectively without prior knowledge of others' intents. While prior work has focused on intent inference, we address the inverse problem: how agents can strategically demonstrate their intents within general-sum dynamic games. We model this problem and propose an algorithm that balances intent demonstration with task performance. To handle nonlinear dynamic games with continuous state-action spaces, our method leverages iterative linear-quadratic game approximations and provides efficient intent-teaching guarantees: the uncertain agent's belief can be driven
Negative / Null Result ReportOpen accessEngineering
Karl Strecker, Sabit Ekin, John OHara · 2021 · arXiv
A theoretical framework and numerical simulations quantifying the impact of atmospheric group velocity dispersion on wireless terahertz communication link error rate were developed based upon experimental work. We present, for the first time, predictions of symbol error rate as a function of link distance, signal bandwidth, signal-to-noise ratio, and atmospheric conditions, revealing that long-distance, broadband terahertz communication systems may be limited by inter-symbol interference stemming from group velocity dispersion, rather than attenuation. In such dispersion limited links, increas
Negative / Null Result ReportOpen accessComputer Science
Dawar Jyoti Deka, Amit Sethi, Syed Mohammad Ali · 2026 · arXiv
Vision-language models enable open-vocabulary object grounding through natural language queries, under the implicit assumption that semantically equivalent descriptions yield consistent outputs. We examine this assumption using a controlled pipeline combining DETR for object proposals with CLIP for language-conditioned selection on 263 COCO val2017 images. We find that overlapping prompts such as "a person," "a human," and "a pedestrian" frequently select different instances, with mean instability of 2.11 distinct selections across six prompts. PCA analysis shows this variability is structured
Negative / Null Result ReportOpen accessComputer Science
Andrea Gallo Rosso, Francesco Vissani, Maria Cristina Volpe · 2017 · arXiv
We investigate the precision with which a neutron star gravitational binding energy can be measured through the supernova neutrino signal, without assuming any prior such as the energy equipartition hypothesis, mean energies hierarchy or constraints on the pinching parameters that characterize the neutrino spectra. We consider water Cherenkov detectors and prove that combining inverse beta decay with elastic scattering on electrons is sufficient to reach $11\%$ precision on the neutron star gravitational binding energy already with Super-Kamiokande. The inclusion of neutral current events on o
Negative / Null Result ReportOpen accessComputer Science
Matthew Aldridge · 2012 · arXiv
Group testing is the combinatorial problem of identifying the defective items in a population by grouping items into test pools. Recently, nonadaptive group testing - where all the test pools must be decided on at the start - has been studied from an information theory point of view. Using techniques from channel coding, upper and lower bounds have been given on the number of tests required to accurately recover the defective set, even when the test outcomes can be noisy. In this paper, we give the first information theoretic result on adaptive group testing - where the outcome of previous tes
Negative / Null Result ReportOpen accessComputer Science
Yunah Jang, Megha Sundriyal, Kyomin Jung et al. · 2026 · arXiv
Adaptive Retrieval-Augmented Generation (RAG) promises accuracy and efficiency by dynamically triggering retrieval only when needed and is widely used in practice. However, real-world queries vary in surface form even with the same intent, and their impact on Adaptive RAG remains under-explored. We introduce the first large-scale benchmark of diverse yet semantically identical query variations, combining human-written and model-generated rewrites. Our benchmark facilitates a systematic evaluation of Adaptive RAG robustness by examining its key components across three dimensions: answer quality
Negative / Null Result ReportOpen accessComputer Science
Seungwon Baek · 2006 · arXiv
We perform a combined analysis of $B \to ππ$ and $B \to πK$ decays with the current experimental data. Assuming SU(3) flavor symmetry and no new physics contributions to the topological amplitudes, we demonstrate that the conventional parametrization in the Standard Model (SM) does not describe the data very well, in contrast with a similar analysis based on the earlier data. It is also shown that the introduction of smaller amplitudes and reasonable SU(3) breaking parameters does not improve the fits much. Interpreting these puzzling behaviors in the SM as a new physics (NP) signal, we study
Negative / Null Result ReportOpen accessComputer Science
Yuto Nishida, Makoto Morishita, Hiroyuki Deguchi et al. · 2025 · arXiv
The $k$-nearest-neighbor language model ($k$NN-LM), one of the retrieval-augmented language models, improves the perplexity for given text by directly accessing a large datastore built from any text data during inference. A widely held hypothesis for the success of $k$NN-LM is that its explicit memory, i.e., the datastore, enhances predictions for long-tail phenomena. However, prior works have primarily shown its ability to retrieve long-tail contexts, leaving the model's performance remain underexplored in estimating the probabilities of long-tail target tokens during inference. In this paper
Negative / Null Result ReportOpen accessComputer Science
Hassan Bassereh, Vahid Salari, Farhad Shahbazi et al. · 2015 · arXiv
We consider quantum excitation energy transport (EET) in a network of two-state nodes in the Markovian approximation by employing the Lindblad formulation. We find that EET from an initial site, where the excitation is inserted to the sink, is generally inefficient due to the inhibition of transport by localization of the excitation wave packet in a symmetric, fully-connected network. We demonstrate that the EET efficiency can be significantly increased up to %100 by perturbing hopping transport between the initial node and the one connected directly to the sink, while the rate of energy trans
Negative / Null Result ReportOpen accessComputer Science
Hugo Meric, Jose Miguel Piquer · 2013 · arXiv
We study the design of a DVB-S2 system in order to maximise spectrum efficiency. This task is usually challenging due to channel variability. Modern satellite communications systems such as DVB-SH and DVB-S2 rely mainly on a time sharing strategy to optimise the spectrum efficiency. Recently, we showed that combining time sharing with hierarchical modulation can provide significant gains (in terms of spectrum efficiency) compared to the best time sharing strategy. However, our previous design does not improve the DVB-S2 performance when all the receivers experience low or large signal-to-noise
Negative / Null Result ReportOpen accessComputer Science
Samuel F. Dodge, Lina J. Karam · 2013 · arXiv
The human visual system employs a selective attention mechanism to understand the visual world in an eficient manner. In this paper, we show how computational models of this mechanism can be exploited for the computer vision application of scene recognition. First, we consider saliency weighting and saliency pruning, and provide a comparison of the performance of different attention models in these approaches in terms of classification accuracy. Pruning can achieve a high degree of computational savings without significantly sacrificing classification accuracy. In saliency weighting, however,
Negative / Null Result ReportOpen accessComputer Science
Taisuke Kobayashi · 2020 · arXiv
This paper proposes a new optimizer for deep learning, named d-AmsGrad. In the real-world data, noise and outliers cannot be excluded from dataset to be used for learning robot skills. This problem is especially striking for robots that learn by collecting data in real time, which cannot be sorted manually. Several noise-robust optimizers have therefore been developed to resolve this problem, and one of them, named AmsGrad, which is a variant of Adam optimizer, has a proof of its convergence. However, in practice, it does not improve learning performance in robotics scenarios. This reason is h
Negative / Null Result ReportOpen accessComputer Science
Domenic Rosati · 2023 · arXiv
Communication of scientific findings to the public is important for keeping non-experts informed of developments such as life-saving medical treatments. However, generating readable lay summaries from scientific documents is challenging, and currently, these summaries suffer from critical factual errors. One popular intervention for improving factuality is using additional external knowledge to provide factual grounding. However, it is unclear how these grounding sources should be retrieved, selected, or integrated, and how supplementary grounding documents might affect the readability or rele
Negative / Null Result ReportOpen accessComputer Science
Ushak Rahaman, Soebur Razzaque · 2021 · arXiv
The $ν_μ\to ν_e$ oscillation probability over short baseline ($\lesssim 1$~km) would be negligible in case the mixing matrix for three active neutrinos is unitary. However, in case of non-unitary mixing of three neutrinos, this probability would be non-negligible due to the so-called "zero distance" effect. Hence, the near detector of the accelerator experiments such as NO$ν$A can provide strong constraints on the parameters of the non-unitary mixing with very large statistics. By analyzing the NO$ν$A near detector data we find that the non-unitary mixing does not improve fits to the $ν_e$ or
Negative / Null Result ReportOpen accessComputer Science
Ewout van den Berg, Michael P. Friedlander · 2009 · arXiv
The joint-sparse recovery problem aims to recover, from sets of compressed measurements, unknown sparse matrices with nonzero entries restricted to a subset of rows. This is an extension of the single-measurement-vector (SMV) problem widely studied in compressed sensing. We analyze the recovery properties for two types of recovery algorithms. First, we show that recovery using sum-of-norm minimization cannot exceed the uniform recovery rate of sequential SMV using $\ell_1$ minimization, and that there are problems that can be solved with one approach but not with the other. Second, we analyze
Negative / Null Result ReportMedicine
Orhan B, Nauta M · 2026 · Death studies
Meaning Management Theory suggests that engaging with meaning-related resources helps individuals constructively regulate consciously experienced death anxiety. Consistent with that theory, we tested whether a single-session, online…
View details →DOI: 10.1080/07481187.2026.2659888 Negative / Null Result ReportOpen accessAgricultural and Biological Sciences
Louis Jalouzot, Alexis Thual, Yair Lakretz et al. · 2025 · arXiv
We investigate optimal strategies for decoding perceived natural speech from fMRI data acquired from a limited number of participants. Leveraging Lebel et al. (2023)'s dataset of 8 participants, we first demonstrate the effectiveness of training deep neural networks to predict LLM-derived text representations from fMRI activity. Then, in this data regime, we observe that multi-subject training does not improve decoding accuracy compared to single-subject approach. Furthermore, training on similar or different stimuli across subjects has a negligible effect on decoding accuracy. Finally, we fin
Negative / Null Result ReportOpen accessComputer Science
Yulin Chen, He He, Chen Zhao · 2026 · arXiv
Reinforcement Learning with Verifiable Reward (RLVR) has proven effective in improving Large Language Model's (LLM) reasoning ability. However, the learning dynamics of RLVR remain underexplored. In this paper, we reveal a counterintuitive phenomenon: among hard examples that the model initially struggles with, a substantial subset remains unlearnable even when correct rollouts are present. To understand the phenomenon, we first demonstrate that existing optimization and sampling techniques fail to resolve unlearnability. With cross-example gradient analysis, we show that unlearnable examples
Negative / Null Result ReportOpen accessComputer Science
Hyeong Kyu Choi, Xiaojin Zhu, Sharon Li · 2025 · arXiv
Multi-Agent Debate~(MAD) has emerged as a promising paradigm for improving the performance of large language models through collaborative reasoning. Despite recent advances, the key factors driving MAD's effectiveness remain unclear. In this work, we disentangle MAD into two key components--Majority Voting and inter-agent Debate--and assess their respective contributions. Through extensive experiments across seven NLP benchmarks, we find that Majority Voting alone accounts for most of the performance gains typically attributed to MAD. To explain this, we propose a theoretical framework that mo
Negative / Null Result ReportOpen accessComputer Science
Mitchell A. Gordon, Kevin Duh, Nicholas Andrews · 2020 · arXiv
Pre-trained universal feature extractors, such as BERT for natural language processing and VGG for computer vision, have become effective methods for improving deep learning models without requiring more labeled data. While effective, feature extractors like BERT may be prohibitively large for some deployment scenarios. We explore weight pruning for BERT and ask: how does compression during pre-training affect transfer learning? We find that pruning affects transfer learning in three broad regimes. Low levels of pruning (30-40%) do not affect pre-training loss or transfer to downstream tasks a
Negative / Null Result ReportOpen accessComputer Science
Tovly Deutsch, Masoud Jasbi, Stuart Shieber · 2020 · arXiv
Readability assessment aims to automatically classify text by the level appropriate for learning readers. Traditional approaches to this task utilize a variety of linguistically motivated features paired with simple machine learning models. More recent methods have improved performance by discarding these features and utilizing deep learning models. However, it is unknown whether augmenting deep learning models with linguistically motivated features would improve performance further. This paper combines these two approaches with the goal of improving overall model performance and addressing th
Negative / Null Result ReportOpen accessComputer Science
C. Fernandez-Ramirez, A. M. Bernstein · 2012 · arXiv
With the availability of the new neutral pion photoproduction from the proton data from the A2 and CB-TAPS Collaborations at Mainz it is mandatory to revisit Heavy Baryon Chiral Perturbation Theory (HBChPT) and address the extraction of the partial waves as well as other issues such as the value of the low-energy constants, the energy range where the calculation provides a good agreement with the data and the impact of unitarity. We find that, within the current experimental status, HBChPT with the fitted LECs gives a good agreement with the existing neutral pion photoproduction data up to $\s
Negative / Null Result ReportOpen accessComputer Science
Osvaldo Simeone, Haim H. Permuter · 2011 · arXiv
For memoryless sources, delayed side information at the decoder does not improve the rate-distortion function. However, this is not the case for more general sources with memory, as demonstrated by a number of works focusing on the special case of (delayed) feedforward. In this paper, a setting is studied in which the encoder is potentially uncertain about the delay with which measurements of the side information are acquired at the decoder. Assuming a hidden Markov model for the sources, at first, a single-letter characterization is given for the set-up where the side information delay is arb
Negative / Null Result Report
Bernard B. Dzoma, Nigel Wilhelm, Matthew Denton et al. · 2026 · Plant and Soil
Abstract Background and aims Residual imidazolinone herbicides are widely recognised for constraining the growth of rotational legume crops; however, little is known about how individual active ingredients including imazapyr and imazamox…
View details →DOI: 10.1007/s11104-026-08682-6 Negative / Null Result Report
Peace N Eneh, Jennifer Bath · 2011 · The FASEB Journal
Soil transmitted helminths have attracted interest in clinical research due their ability to parasitize human hosts. These parasitic species such as H. polygyrus infest host cell and suppress the immune system by secreting a fatty acid and…
View details →DOI: 10.1096/fasebj.25.1_supplement.918.1 