Revisiting B\to\pi K, \pi K^{\ast} and \rho K decays: CP violations and implication for New Physics

Combining the up-to-date experimental information on $B\to\pi K, \pi K^{\ast}$ and $\rho K$ decays, we revisit the decay rates and CP asymmetries of these decays within the framework of QCD factorization. Using an infrared finite gluon propagator of Cornwall prescription, we find that the time-like annihilation amplitude could contribute a large strong phase, while the space-like hard spectator scattering amplitude is real. Numerically, we find that all the branching ratios and most of the direct CP violations, except $A_{CP}(B^{\pm}\to K^{\pm}\pi^{0})$, agree with the current experimental data with an effective gluon mass $m_g\simeq0.5 {\rm GeV}$. Taking the unmatched difference in direct CP violations between $B\to\pi^{0} K^{\pm}$ and $\pi^{\mp}K^{\pm}$ decays as a hint of new physics, we perform a model-independent analysis of new physics contributions with a set of $\bar{s}(1+\gamma_{5})b\otimes\bar{q}(1+\gamma_{5})q$ (q=u,d) operators. Detail analyses of the relative impacts of the operators are presented in five cases. Fitting the twelve decay modes, parameter spaces are found generally with nontrivial weak phases. Our results may indicate that both strong phase from annihilation amplitude and new weak phase from new physics are needed to resolve the $\pi K$ puzzle. To further test the new physics hypothesis, the mixing-induced CP violations in $B\to\pi^{0}K_{S}$ and $\rho^{0}K_{S}$ are discussed and good agreements with the recent experimental data are found.Comment: Version published in JHE

Family Non-universal Z^\prime effects on \bar{B}_q-B_q$ mixing, B\to X_s \mu^+\mu^- and B_s\to \mu^+\mu^- Decays

Motivated by the large discrepancy of CP-violating phase in $\bar{B}_s-B_s$ mixing between the experimental data and the Standard Model prediction, we pursue possible solutions within a family non-universal $Z^{\prime}$ model. Within such a specific model, we find that both the $\bar{B}_s-B_s$ mixing anomaly and the well-known "$\pi K$ puzzle" could be moderated simultaneously with a nontrivial new weak phase, $\phi^L_s\sim-72^{\circ}$ (S1) or $-82^{\circ}$ (S2). With the stringently constrained $Z^{\prime}$ coupling $B_{sb}^{L}$, we then study the $Z^{\prime}$ effects on the rare $B\to X_s \mu^+\mu^-$ and $B_s\to \mu^+\mu^-$ decays, which are also induced by the same $b\to s$ transition. The observables of $B\to X_s \mu^+\mu^-$, at both high and low $q^2$ regions, are found to be able to put strong constraints on the $\mu-\mu-Z^{\prime}$ coupling, $B_{\mu\mu}^{L,R}\sim10^{-2}$. It is also shown that the combined constraints from $\bar{B}_s-B_s$ mixing, $B\to \pi K$ and $B\to X_s \mu^+\mu^-$ do not allow a large $Z^{\prime}$ contribution to the pure leptonic $B_s\to\mu^+\mu^-$ decay.Comment: 29 pages, 10 figs and 6 tables. References and discussions added. To appear in JHE

B→K∗l+l−B \to K^{\ast} l^+ l^-, Kl+l−K l^+ l^- decays in a family non-universal Z′Z^{\prime} model

Motivated by the observed forward-backward asymmetry in $B\to K^{\ast} l^+ l^-$ decay, we perform a detailed analysis of this decay mode within a family non-universal $Z^{\prime}$ model. With the related coupling $Z^{\prime}-\bar{s}b$ constrained by $\bar{B}_s-B_s$ mixing, $B\to \pi K$, and $B\to X_s \mu^{+}\mu^{-}$ decays, we look for further constraint on the couplings $Z^{\prime}-\mu^{+}\mu^{-}$ from $A_{FB}(B\to K^{\ast} \mu^{+}\mu^{-})_{0 {\rm GeV}^2\leqslant q^2\leqslant 2 {\rm GeV}^2}$ and get numerically $B_{\mu\mu}^{L,R}\sim{\cal O}(10^{-2})$. Moreover, we find that the relations, $B_{\mu\mu}^{L}<B_{\mu\mu}^{R}$ and $B_{\mu\mu}^{L}+B_{\mu\mu}^{R}<0$, with a small negative $\phi_{s}^{L}$, are crucial to moderate the discrepancy for $A_{FB}(B\to K^{\ast} \mu^{+}\mu^{-})$ between the SM prediction and the experimental data. Numerically, comparing with the SM prediction, we find that $A_{FB}(B\to K^{\ast} \mu^{+}\mu^{-})_{0 {\rm GeV}^2\leqslant q^2\leqslant 2 {\rm GeV}^2}$ could be enhanced about 80% and 50% by $Z^{\prime}$ contribution at most in scenarios S1 and S2, corresponding to the two fitted results of $\phi_{s}$ by UTfit collaboration, respectively. However, the results are still about $1.5\sigma$ lower than the experimental measurement.Comment: 20 pages, 3 figures. To appear in JHE

An Effective Deployment of Contrastive Learning in Multi-label Text Classification

The effectiveness of contrastive learning technology in natural language processing tasks is yet to be explored and analyzed. How to construct positive and negative samples correctly and reasonably is the core challenge of contrastive learning. It is even harder to discover contrastive objects in multi-label text classification tasks. There are very few contrastive losses proposed previously. In this paper, we investigate the problem from a different angle by proposing five novel contrastive losses for multi-label text classification tasks. These are Strict Contrastive Loss (SCL), Intra-label Contrastive Loss (ICL), Jaccard Similarity Contrastive Loss (JSCL), Jaccard Similarity Probability Contrastive Loss (JSPCL), and Stepwise Label Contrastive Loss (SLCL). We explore the effectiveness of contrastive learning for multi-label text classification tasks by the employment of these novel losses and provide a set of baseline models for deploying contrastive learning techniques on specific tasks. We further perform an interpretable analysis of our approach to show how different components of contrastive learning losses play their roles. The experimental results show that our proposed contrastive losses can bring improvement to multi-label text classification tasks. Our work also explores how contrastive learning should be adapted for multi-label text classification tasks.Comment: Accepted by ACL-Findings 2023, 13 page

Spam Review Detection with Graph Convolutional Networks

Customers make a lot of reviews on online shopping websites every day, e.g., Amazon and Taobao. Reviews affect the buying decisions of customers, meanwhile, attract lots of spammers aiming at misleading buyers. Xianyu, the largest second-hand goods app in China, suffering from spam reviews. The anti-spam system of Xianyu faces two major challenges: scalability of the data and adversarial actions taken by spammers. In this paper, we present our technical solutions to address these challenges. We propose a large-scale anti-spam method based on graph convolutional networks (GCN) for detecting spam advertisements at Xianyu, named GCN-based Anti-Spam (GAS) model. In this model, a heterogeneous graph and a homogeneous graph are integrated to capture the local context and global context of a comment. Offline experiments show that the proposed method is superior to our baseline model in which the information of reviews, features of users and items being reviewed are utilized. Furthermore, we deploy our system to process million-scale data daily at Xianyu. The online performance also demonstrates the effectiveness of the proposed method.Comment: Accepted at CIKM 201