On the Robustness of Generative Retrieval Models: An Out-of-Distribution Perspective

Recently, we have witnessed generative retrieval increasingly gaining attention in the information retrieval (IR) field, which retrieves documents by directly generating their identifiers. So far, much effort has been devoted to developing effective generative retrieval models. There has been less attention paid to the robustness perspective. When a new retrieval paradigm enters into the real-world application, it is also critical to measure the out-of-distribution (OOD) generalization, i.e., how would generative retrieval models generalize to new distributions. To answer this question, firstly, we define OOD robustness from three perspectives in retrieval problems: 1) The query variations; 2) The unforeseen query types; and 3) The unforeseen tasks. Based on this taxonomy, we conduct empirical studies to analyze the OOD robustness of several representative generative retrieval models against dense retrieval models. The empirical results indicate that the OOD robustness of generative retrieval models requires enhancement. We hope studying the OOD robustness of generative retrieval models would be advantageous to the IR community.Comment: 4 pages, submit to GenIR2

Exploring the Cosmic Reionization Epoch in Frequency Space: An Improved Approach to Remove the Foreground in 21 cm Tomography

Aiming to correctly restore the redshifted 21 cm signals emitted by the neutral hydrogen during the cosmic reionization processes, we re-examine the separation approaches based on the quadratic polynomial fitting technique in frequency space to investigate whether they works satisfactorily with complex foreground, by quantitatively evaluate the quality of restored 21 cm signals in terms of sample statistics. We construct the foreground model to characterize both spatial and spectral substructures of the real sky, and use it to simulate the observed radio spectra. By comparing between different separation approaches through statistical analysis of restored 21 cm spectra and corresponding power spectra, as well as their constraints on the mean halo bias $b$ and average ionization fraction $x_e$ of the reionization processes, at $z=8$ and the noise level of 60 mK we find that, although the complex foreground can be well approximated with quadratic polynomial expansion, a significant part of Mpc-scale components of the 21 cm signals (75% for $\gtrsim 6h^{-1}$ Mpc scales and 34% for $\gtrsim 1h^{-1}$ Mpc scales) is lost because it tends to be mis-identified as part of the foreground when single-narrow-segment separation approach is applied. The best restoration of the 21 cm signals and the tightest determination of $b$ and $x_e$ can be obtained with the three-narrow-segment fitting technique as proposed in this paper. Similar results can be obtained at other redshifts.Comment: 33 pages, 14 figures. Accepted for publication in Ap

Governance Policy Evaluation in the United States during the Pandemic: Nonpharmaceutical Interventions or Else?

Scientific evidence suggests that nonpharmaceutical interventions (NPIs) effectively curb the spread of COVID-19 before a pharmaceutical solution. Implementing these interventions also significantly affects regular socioeconomic activities and practices of social, racial, and political justice. Local governments often face conflicting goals during policymaking. Striking a balance among competing goals during a global pandemic is a fine science of governance. How well state governments consume the scientific evidence and maintain such a balance remains less understood. This study employs a set of Bayesian hierarchical models to evaluate how state governments in the United States use scientific evidence to balance the fighting against the spread of COVID-19 disease and socioeconomic, racial, social justice, and other demands. We modeled the relationships between five NPI strategies and COVID-19 caseload information and used the modeled result to perform a balanced governance evaluation. The results suggest that governmental attitude and guidance effectively guide the public to fight back against a global pandemic. The more detailed spatiotemporally varying coefficient process model produces 612,000 spatiotemporally varying coefficients, suggesting all measures sometimes work somewhere. Summarized results indicate that states emphasizing NPIs fared well in curbing the spread of COVID-19. With over 1 million deaths due to COVID-19 in the United States, we feel the balance scale likely needs to tip toward preserving human lives. Our evaluation of governance policies is hence based on such an argument. This study aims to provide decision support for policymaking during a national emergency

(E)-3-Allyl­sulfanyl-N-(4-methoxy­benzyl­idene)-5-(3,4,5-trimethoxy­phen­yl)-4H-1,2,4-triazol-4-amine

The title compound, C22H24N4O4S, adopts a trans configuration with respect to the C=N double bond. A weak intra­molecular C—H⋯N hydrogen bond is observed between the N atom of the C=N double bond and its neighboring phenyl H atom. The crystal structure is stabilized by inter­molecular C—H⋯N hydrogen bonds and C—H⋯π inter­actions