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1. Long Document Re-ranking with Modular Re-ranker

   https://doi.org/10.1145/3477495.3531860  

   Gao, Luyu; Callan, Jamie (July 2022, ACM)

   Long document re-ranking has been a challenging problem for neural re-rankers based on deep language models like BERT. Early work breaks the documents into short passage-like chunks. These chunks are independently mapped to scalar scores or latent vectors, which are then pooled into a final relevance score. These encode-and-pool methods however inevitably introduce an information bottleneck: the low dimension representations. In this paper, we propose instead to model full query-to-document interaction, leveraging the attention operation and modular Transformer re-ranker framework. First, document chunks are encoded independently with an encoder module. An interaction module then encodes the query and performs joint attention from the query to all document chunk representations. We demonstrate that the model can use this new degree of freedom to aggregate important information from the entire document. Our experiments show that this design produces effective re-ranking on two classical IR collections Robust04 and ClueWeb09, and a large-scale supervised collection MS-MARCO document ranking. CCS CONCEPTS • Information systems 

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2. Proxy Re-Encryption and Re-Signatures from Lattices

   https://doi.org/https://doi.org/10.1007/978-3-030-21568-2_18  

   Fan, Xiong; Liu, Feng-Hao (May 2019, International Conference on Applied Cryptography and Network Security)
3. Synthesis and Reactivity of Re(III) and Re(V) Fischer Carbenes

   https://doi.org/10.1021/acs.organomet.9b00600  

   Brown, Caleb A.; Lilly, Cassandra P.; Lambic, Nikola S.; Sommer, Roger D.; Ison, Elon A. (February 2020, Organometallics)

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4. Re-ranking via Metric Fusion for Object Retrieval and Person Re-identification.

   Bai, Song; Tang, Peng; Torr, Philip; Latecki, Longin Jan (June 2019, IEEE Conference on Computer Vision and Pattern Recognition)

   This work studies the unsupervised re-ranking procedure for object retrieval and person re-identification with a specific concentration on an ensemble of multiple metrics (or similarities). While the re-ranking step is involved by running a diffusion process on the underlying data manifolds, thefusionstepcanleveragethecomplementarityofmultiple metrics. We give a comprehensive summary of existing fusion with diffusion strategies, and systematically analyze their pros and cons. Based on the analysis, we propose a unified yet robust algorithm which inherits their advantages and discards their disadvantages. Hence, we call it Unified Ensemble Diffusion (UED). More interestingly, we derive that the inherited properties indeed stem from a theoretical framework, where the relevant works can be elegantly summarized as special cases of UED by imposing additional constraints on the objective function and varying the solver of similarity propagation. Extensive experiments with 3D shape retrieval, image retrieval and person re-identification demonstrate that the proposed framework outperforms the state of the arts, and at the same time suggest that re-ranking via metric fusion is a promising tool to further improve the retrieval performance of existing algorithms. 

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5. Diffusive shock re-acceleration

   https://doi.org/10.1017/S0022377818000478  

   Caprioli, Damiano; Zhang, Horace; Spitkovsky, Anatoly (June 2018, Journal of Plasma Physics)

   We have performed two-dimensional hybrid simulations of non-relativistic collisionless shocks in the presence of pre-existing energetic particles (‘seeds’); such a study applies, for instance, to the re-acceleration of galactic cosmic rays (CRs) in supernova remnant (SNR) shocks and solar wind energetic particles in heliospheric shocks. Energetic particles can be effectively reflected and accelerated regardless of shock inclination via a process that we call diffusive shock re-acceleration. We find that re-accelerated seeds can drive the streaming instability in the shock upstream and produce effective magnetic field amplification. This can eventually trigger the injection of thermal protons even at oblique shocks that ordinarily cannot inject thermal particles. We characterize the current in reflected seeds, finding that it tends to a universal value $$J\simeq en_{\text{CR}}v_{\text{sh}}$$ , where $$en_{\text{CR}}$$ is the seed charge density and $$v_{\text{sh}}$$ is the shock velocity. When applying our results to SNRs, we find that the re-acceleration of galactic CRs can excite the Bell instability to nonlinear levels in less than $${\sim}10~\text{yr}$$ , thereby providing a minimum level of magnetic field amplification for any SNR shock. Finally, we discuss the relevance of diffusive shock re-acceleration also for other environments, such as heliospheric shocks, galactic superbubbles and clusters of galaxies. 

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