Understanding Differential Search Index for Text Retrieval

The Differentiable Search Index (DSI) is a novel information retrieval (IR) framework that utilizes a differentiable function to generate a sorted list of document identifiers in response to a given query. However, due to the black-box nature of the end-to-end neural architecture, it remains to be understood to what extent DSI possesses the basic indexing and retrieval abilities. To mitigate this gap, in this study, we define and examine three important abilities that a functioning IR framework should possess, namely, exclusivity, completeness, and relevance ordering. Our analytical experimentation shows that while DSI demonstrates proficiency in memorizing the unidirectional mapping from pseudo queries to document identifiers, it falls short in distinguishing relevant documents from random ones, thereby negatively impacting its retrieval effectiveness. To address this issue, we propose a multi-task distillation approach to enhance the retrieval quality without altering the structure of the model and successfully endow it with improved indexing abilities. Through experiments conducted on various datasets, we demonstrate that our proposed method outperforms previous DSI baselines.Comment: Accepted to Findings of ACL 202

Offline Pseudo Relevance Feedback for Efficient and Effective Single-pass Dense Retrieval

Dense retrieval has made significant advancements in information retrieval (IR) by achieving high levels of effectiveness while maintaining online efficiency during a single-pass retrieval process. However, the application of pseudo relevance feedback (PRF) to further enhance retrieval effectiveness results in a doubling of online latency. To address this challenge, this paper presents a single-pass dense retrieval framework that shifts the PRF process offline through the utilization of pre-generated pseudo-queries. As a result, online retrieval is reduced to a single matching with the pseudo-queries, hence providing faster online retrieval. The effectiveness of the proposed approach is evaluated on the standard TREC DL and HARD datasets, and the results demonstrate its promise. Our code is openly available at https://github.com/Rosenberg37/OPRF.Comment: Accepted at SIGIR202

Comparison between transgenic maize with exotic betaine aldehyde dehydrogenase (BADH) gene and its untransformed counterpart

We investigated the performance of a transgenic maize (Zea mays L) line with an exotic betaine aldehyde dehydrogenase (BADH) gene and its untransformed counterpart under drought and normal water conditions. Membrane permeability, osmoprotectant contents, and antioxidant enzyme activities of the maize lines as well as plant height and biomass were compared. The results showed that, under drought stress, compared with the untransgenic line, the contents of glycine betaine (GB), soluble sugars, soluble proteins and proline of the trans- genic line were significantly higher, so was the peroxidase (POD) activity; the contents of superoxide anion free radical, malondialdehyde (MDA) and the electrical conductivity of the transgenic line were lower; plant height and the biomass of the transgenic line were significantly higher. Under normal water conditions, the contents of soluble protein and MDA content of the transgenic line were significantly lower; but it was not the case for the content of superoxide anion free radical, electrical conductivity and superoxide dismutase (SOD) activity. No significant difference was observed in GB content and, the plant height and the biomass between the 2 lines. We conclude that the transgenic maize with exotic BADH gene was superior over its untransformed counterpart under drought stress and they performed similarly under normal water conditions

Features Extraction and Reconstruction of Country Risk based on Empirical EMD

AbstractIn the application of the Empirical Mode Decomposition (EMD), reconstruction to the intrinsic mode functions (IMFs) which are obtained by EMD is necessary in order to simplify analysis and make reconstruction results of more economic explanatory power. At present, there are two main reconstruction methods; one is based on the changing of data construction, represented by the fine- to-coarse method, the other one takes the correlation of the IMFs into consideration, for example, calculating the correlation between the marginal spectrums of different IMFs. In order to study the internal unity and differences between the two methods, country risk data of the BRICS countries are selected to make the empirical analysis. The results are as follows. Firstly, it is not reasonable that the residue obtained by the EMD is directly regarded as the trend of the original data. Secondly, by fine-to-coarse, all the IMFs can be reconstructed to three time scales, which are denoted as high-frequency mode, low-frequency mode and trend respectively, but explanation of these scales for the real situation is not satisfactory. At last, trend which is extracted based on the correlation of the IMF marginal spectrums can describe the basic behavior of the original data. Contrasted to fine-to-coarse, the results obtained by the second method are more reasonable