Tootfinder

This https://arxiv.org/abs/2308.13249 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csIR_…

Learning and Optimization of Implicit Negative Feedback for Industrial Short-video Recommender System
Short-video recommendation is one of the most important recommendation applications in today's industrial information systems. Compared with other recommendation tasks, the enormous amount of feedback is the most typical characteristic. Specifically, in short-video recommendation, the easiest-to-collect user feedback is the skipping behavior, which leads to two critical challenges for the recommendation model. First, the skipping behavior reflects implicit user preferences, and thus, it is chal…

Late night, when you're entering your computer #password many times and get a negative feedback, start to question your ability to remember one of your most important and frequently used passphrases until you realize that you enter the (correct) passphrase of a different machine. 🤦‍♂️

A Directional Diffusion Graph Transformer for Recommendation
Zixuan Yi, Xi Wang, Iadh Ounis
https://arxiv.org/abs/2404.03326 https://…

A Directional Diffusion Graph Transformer for Recommendation
In real-world recommender systems, implicitly collected user feedback, while abundant, often includes noisy false-positive and false-negative interactions. The possible misinterpretations of the user-item interactions pose a significant challenge for traditional graph neural recommenders. These approaches aggregate the users' or items' neighbours based on implicit user-item interactions in order to accurately capture the users' profiles. To account for and model possible noise in the users' int…

If you have ever been in a position where you have to give people in power negative feedback with unequivocal data supporting your position, whether manager, senior employee or any position involving infrastructure, databases or networking, then you know that many people cannot accept it is possible to have someone criticize you and not be your mortal enemy who must be destroyed

This https://arxiv.org/abs/2311.13295 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_ees…

Feedback control of plant-soil autotoxicity via pulse-width modulation
Plant-soil negative feedback (PSNF) is the rise in soil of negative conditions for plant performance induced by the plants themselves, limiting the full potential yield and thus representing a loss for the agricultural industry. It has been recently shown that detrimental effects the PSNF has on the growth of plant's biomass can be mitigated by periodically intervening on the plant/soil system, for example by washing the soil. The periodic control inputs were computed by using an average model …

This https://arxiv.org/abs/2404.08977 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCL_…

RoNID: New Intent Discovery with Generated-Reliable Labels and Cluster-friendly Representations
New Intent Discovery (NID) strives to identify known and reasonably deduce novel intent groups in the open-world scenario. But current methods face issues with inaccurate pseudo-labels and poor representation learning, creating a negative feedback loop that degrades overall model performance, including accuracy and the adjusted rand index. To address the aforementioned challenges, we propose a Robust New Intent Discovery (RoNID) framework optimized by an EM-style method, which focuses on constr…

User seeks feedback on negative experiences with cybersecurity products like web apps or mobile apps, asking about frustration sources. https://reddit.com/r/cybersecurity/comments/1c1nd3d/

SIGformer: Sign-aware Graph Transformer for Recommendation
Sirui Chen, Jiawei Chen, Sheng Zhou, Bohao Wang, Shen Han, Chanfei Su, Yuqing Yuan, Can Wang
https://arxiv.org/abs/2404.11982

SIGformer: Sign-aware Graph Transformer for Recommendation
In recommender systems, most graph-based methods focus on positive user feedback, while overlooking the valuable negative feedback. Integrating both positive and negative feedback to form a signed graph can lead to a more comprehensive understanding of user preferences. However, the existing efforts to incorporate both types of feedback are sparse and face two main limitations: 1) They process positive and negative feedback separately, which fails to holistically leverage the collaborative info…

A lack of LAEs within 5Mpc of a luminous quasar in an overdensity at z=6.9: potential evidence of quasar negative feedback at protocluster scales
Trystan S. Lambert, R. J. Assef, C. Mazzucchelli, E. Ba\~nados, M. Aravena, F. Barrientos, J. Gonz\'alez-L\'opez, W. Hu, L. Infante, S. Malhotra, C. Moya-Sierralta, J. Rhoads, F. Valdes, J. Wang, I. G. B. Wold, Z. Zheng

A lack of LAEs within 5Mpc of a luminous quasar in an overdensity at z=6.9: potential evidence of quasar negative feedback at protocluster scales
High-redshift quasars are thought to live in the densest regions of space which should be made evident by an overdensity of galaxies around them. However, campaigns to identify these overdensities through the search of Lyman Break Galaxies (LBGs) and Lyman $α$ emitters (LAEs) have had mixed results. These may be explained by either the small field of view of some of the experiments, the broad redshift ranges targeted by LBG searches, and by the inherent large uncertainty of quasar redshifts es…

NFARec: A Negative Feedback-Aware Recommender Model
Xinfeng Wang, Fumiyo Fukumoto, Jin Cui, Yoshimi Suzuki, Dongjin Yu
https://arxiv.org/abs/2404.06900 htt…

NFARec: A Negative Feedback-Aware Recommender Model
Graph neural network (GNN)-based models have been extensively studied for recommendations, as they can extract high-order collaborative signals accurately which is required for high-quality recommender systems. However, they neglect the valuable information gained through negative feedback in two aspects: (1) different users might hold opposite feedback on the same item, which hampers optimal information propagation in GNNs, and (2) even when an item vastly deviates from users' preferences, the…

NFARec: A Negative Feedback-Aware Recommender Model
Xinfeng Wang, Fumiyo Fukumoto, Jin Cui, Yoshimi Suzuki, Dongjin Yu
https://arxiv.org/abs/2404.06900 htt…

NFARec: A Negative Feedback-Aware Recommender Model
Graph neural network (GNN)-based models have been extensively studied for recommendations, as they can extract high-order collaborative signals accurately which is required for high-quality recommender systems. However, they neglect the valuable information gained through negative feedback in two aspects: (1) different users might hold opposite feedback on the same item, which hampers optimal information propagation in GNNs, and (2) even when an item vastly deviates from users' preferences, the…

Open Cluster Dynamics under the Influence of Outflow-Ambient Interactions
Muxin Liu, Lile Wang, Xiaoting Fu, Luis C. Ho
https://arxiv.org/abs/2404.13809 ht…

Open Cluster Dynamics under the Influence of Outflow-Ambient Interactions
Outflowing stars impinging upon ambient gas experience accelerations due to the gravitational feedback from the morphology of the interaction betweem the outflow and the ambient gas. Such "negative dynamical friction" (NDF), in contrast to the conventional "dynamical friction" (DF), is studied for its impact on the dynamics of open clusters immersed in a uniform ambient gas. We modify the $N$-body integration code REBOUND with both NDF and DF implemented according to the outflow conditions of e…

A Generalization for Ultradiscrete Limit Cycles in a Certain Type of Max-Plus Dynamical Systems
Shousuke Ohmori, Yoshihiro Yamazaki
https://arxiv.org/abs/2402.06230

A Generalization for Ultradiscrete Limit Cycles in a Certain Type of Max-Plus Dynamical Systems
Dynamical properties of a generalized max-plus model for ultradiscrete limit cycles are investigated.This model includes both the negative feedback model and the Sel'kov model. It exhibits the Neimark-Sacker bifurcation, and possesses stable and unstable ultradiscrete limit cycles. The number of discrete states in the limit cycles can be analytically determined and its approximate relation is proposed. Additionally, relationship between the max-plus model and the two-dimensional normal form of …

This https://arxiv.org/abs/2310.19863 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_…

Dense stellar clump formation driven by strong quasar winds in the FIRE cosmological hydrodynamic simulations
We investigate the formation of dense stellar clumps in a suite of high-resolution cosmological zoom-in simulations of a massive, star forming galaxy at $z \sim 2$ under the presence of strong quasar winds. Our simulations include multi-phase ISM physics from the Feedback In Realistic Environments (FIRE) project and a novel implementation of hyper-refined accretion disk winds. We show that powerful quasar winds can have a global negative impact on galaxy growth while in the strongest cases trig…