Abstract: The present disclosure relates to systems and methods for providing personalized retrievals of items. The systems and methods create a user-specific morph operator for a user that captures learned user preferences for the user. The systems and methods use the user-specific morph operator to transform a generic embedding for a query into a personalized embedding for the query. The systems and method use the personalized embedding to retrieve items based on the user preferences to present in response to the query.

Abstract: Methods, apparatus and systems for wireless communication nodes to discover each other are disclosed. In one embodiment, a method performed by a first wireless communication node is disclosed. The method comprises: transmitting, to each of a plurality of second wireless communication nodes, respective configuration information that is utilized by the second wireless communication node to transmit a discovery signal in order to be discovered by at least one other second wireless communication node. At least two of the plurality of second wireless communication nodes transmit their discovery signals at different time domain positions based on their respective configuration information.

Abstract: A technique is described herein for processing a given query item in a latency-efficient and resource-efficient manner. The technique uses a first transformer-based encoder to transform the given query item into an encoded query item. In one case, the given query item is an expression that includes one or more query-expression linguistic tokens. The technique includes a second transformer-based encoder for transforming a given target item into an encoded target item. The given target item may likewise correspond to an expression that includes one or more target-expression linguistic tokens. A similarity-assessing mechanism then assesses the semantic similarity between the given query item and the given target item based on the encoded query item and the encoded target item. Each transformer-based encoder uses one or more self-attention mechanisms. The second transformer-based encoder can optionally perform its work in an offline manner, prior to receipt of the given query item.

Abstract: The present disclosure relates to methods and systems for managing and controlling resources. A system for managing and controlling resources may comprise a storage device configured to store a set of instructions, one or more processors configured to communicate with the storage device. When executing the set of instructions, the one or more processors may be configured to cause the system to collect resource usage data through one or more meters, process the resource usage data based on a preset algorithm to determine resource usage state, and control at least the one or more meters and/or one or more smart devices to perform specified operations based on the resource usage state. The present disclosure provides methods and systems for managing and controlling resources based on meters or smart devices controlled by the network.

Abstract: A technique is described herein for processing a given query item in a latency-efficient and resource-efficient manner. The technique uses a first transformer-based encoder to transform the given query item into an encoded query item. In one case, the given query item is an expression that includes one or more query-expression linguistic tokens. The technique includes a second transformer-based encoder for transforming a given target item into an encoded target item. The given target item may likewise correspond to an expression that includes one or more target-expression linguistic tokens. A similarity-assessing mechanism then assesses the semantic similarity between the given query item and the given target item based on the encoded query item and the encoded target item. Each transformer-based encoder uses one or more self-attention mechanisms. The second transformer-based encoder can optionally perform its work in an offline manner, prior to receipt of the given query item.