Abstract: A first set of features associated with a neural network are parameterized. A decision tree is generated from the first set of features. One or more adjustments for the neural network are received at the decision tree. A second set of features associated with the adjustments at the decision tree are parameterized. The parameterized first and second set of features are combined into a plurality of parameters. From the plurality, an adjusted neural network is generated.

Abstract: One or more systems, devices, computer program products and/or computer-implemented methods of use provided herein relate to a process to facilitate abnormal document self-discovery. A system can comprise a memory that stores computer executable components, and a processor that executes the computer executable components stored in the memory, wherein the computer executable components can comprise an object detection component that can generate a knowledge graph with vectors corresponding with nodes representative of a page layout of a document. Additionally, the computer executable components can comprise an evaluation component that can compare the vectors to identify whether an edge is present between corresponding vectors of the knowledge graph; an encoder component that can re-code the knowledge graph; and a comparison component that can compare a structure of the knowledge graph with one or more other knowledge graphs corresponding to one or more other documents to determine if the document is abnormal.

Abstract: A system and method for table conversion including converting a table containing text in tabular form to an image, labeling each text area of the image with a bounding box, determining for each bounding box, a position information, a semantic information, and an image information, reconstructing the image into a graph form having a plurality of nodes, wherein each node represents the bounding box of the text areas of the image, inputting at least two nodes into a trained neural network to determine a relative relationship between the at least two nodes, building a knowledge graph using the relative relationship of the at least two nodes, and translating the knowledge graph into machine readable natural language.

Abstract: A method, computer program product, and computer system for generating and using a basic state layer. N task models are provided (N?2). Each task model was trained on a same pre-trained backbone model. Each task model includes M feature layers and a task layer (M?1). Each feature layer of each task model includes a parameter matrix that is different for the different models. An encoder-decoder model is trained. The encoder-decoder model includes sequentially: an input layer, an encoder, M hidden layers, a decoder, and an output layer. The encoder is a neural network that maps and compresses the parameter matrices in the input layer into the M hidden layers, which generates a basic state model. The decoder is a neural network that receives the basic state model as input and generates the output layer to be identical to the input layer.

Abstract: Methods for manufacturing a display device are provided. The methods include providing a plurality of light-emitting units and a substrate. The methods also include transferring the light-emitting units to a transfer head. The methods further include attaching at least one of the plurality of light-emitting units on the transfer head to the substrate by a bonding process, wherein the transfer head and the substrate satisfy the following equation during the bonding process: 0 ? ? ? T ? ? 1 T ? ? 2 ? A ? ( T ) ? dT - ? T ? ? 1 T ? ? 3 ? E ? ( T ) ? dT ? ? < 0.01 wherein A(T) is the coefficient of thermal expansion of the transfer head, E(T) is the coefficient of thermal expansion of the substrate, T1 is room temperature, T2 is the temperature of the transfer head, and T3 is the temperature of the substrate.

Abstract: An example operation may include one or more of generating a three-dimensional (3D) model of an object via execution of a machine learning model on one or more images of the object, capturing a plurality of snapshots of the 3D model of the object at different angles to generate a plurality of snapshot images of the object, fusing a feature into each of the plurality of snapshots to generate a plurality of fused snapshots of the 3D model of the object, and storing the plurality of fused snapshots of the 3D model of the object in memory.

Abstract: Certain aspects of the present disclosure provide techniques for interference avoidance in full duplex communications. A method that may be performed by a user equipment (UE) includes transmitting, to a network entity, a request to provide a configuration for interference avoidance between a first signal and a second signal, wherein the first signal is scheduled in a same transmission occasion as the second signal is scheduled for reception. The method further includes receiving, from the network entity, the configuration and configuring resources for at least one of transmission of the first signal or reception of the second signal in response to receiving the configuration. The method also includes transmitting the first signal via the configured resources and receiving the second signal in the transmission occasion.

Abstract: A method of this disclosure may include performing a named entity recognition on text information related to requirements for a wireframe by a first artificial intelligence (AI) model, so as to extract entities and relations of the entities from the text information. The method may further comprise inputting the extracted entities and relations to a second AI model to generate the wireframe, wherein the second AI model is trained so that a difference between resultant relations of the entities of the generated wireframe and the extracted relations of the entities from the first AI model is decreased.

Abstract: Using labelled training content, a content classification model is trained. Using the trained content classification model, a label describing a first content is determined. The first content is classified into a category in a set of categories using the label. Responsive to the first content being classified into a category of inappropriate content, the first content is removed from a storage location.

Abstract: Techniques for using implicit pathloss reference signal (RS) in a transmission configuration indication (TCI) may be performed. In an example, a method of wireless communication by a user equipment (UE), may include receiving, from a base station, a TCI state configuration. The method may also include determining a PLRS is not explicitly indicated by the TCI state configuration. The method may also include obtaining a default PLRS in response to the PLRS not being explicitly indicated by the TCI state configuration. The method may also include transmitting, to the base station, uplink (UL) power control information based on the default PLRS in a UL transmission.

Abstract: Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a user equipment (UE) may start, from a last transmission of a reference signal resource, a known transmission control indicator (TCI) duration during which a TCI state switch command is to be received. The known TCI duration may end after a maximum time duration and may exclude an invalid period. The UE may receive the TCI state switch command during the known TCI duration. Numerous other aspects are described.

Abstract: A light-emitting element includes a pair of electrodes, a first light-emitting unit, a second light-emitting unit, and a charge generation layer. The first light-emitting unit, between the pair of electrodes, and the first light-emitting unit, includes a first light-emitting layer. The second light-emitting unit, between the pair of electrodes, includes a second light-emitting layer. A first luminescent layer includes a first main body material, a second main body material, a first guest material, and a first auxiliary material, and the first main body material forms a first excimer complex with the second main body material. A first excited triplet state energy level of the first auxiliary material is lower than a first excited triplet state energy level of the first excimer complex, and the first excited triplet state energy level of the first auxiliary material is higher than that of the first guest material.

Abstract: Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a user equipment (UE) may obtain an indication of at least one rate matching configuration. The UE may communicate in a full duplex communication mode, wherein communicating in the full duplex communication mode comprises rate matching based at least in part on the at least one rate matching configuration. Numerous other aspects are described.

Abstract: A method for contrastive learning by selecting dropout ratios and locations based on reinforcement learning includes receiving training data having a positive sample corresponding to a target and negative samples not corresponding to the target. A dropout policy for a neural network is produced based on the training data, where the dropout policy identifies at least one connection between neurons in the neural network to dropout. The training data is encoded, based on the dropout policy, to form embeddings, where the embeddings include multiple positive sample embeddings corresponding to the positive sample and multiple negative sample embedding corresponding to the negative samples.

Abstract: Methods, systems, and devices for wireless communications are described. In some examples, a first user equipment (UE) may receive an active communication configuration between the first UE and a base station. The first UE may receive a UE cooperation configuration between at least the first UE and a second UE. The UE cooperation configuration may include a configuration for communicating messages between the base station and a set of antenna panels corresponding to at least the first UE and the second UE as a single entity. The UE cooperation configuration may include parameters associated with the second UE. The first UE may identify, from the set of antenna panels, an antenna panel for reception of a downlink message based on the UE cooperation configuration. The first UE may transmit a message to the base station, the second UE, or both in response to the downlink message.

Abstract: An environment-transforming system transforms a user's environmental information in ways that allow the user to better perceive her environment. For example, the system transforms some aspects of a visual scene into a sound space for a visually impaired user. Once the user learns to interpret the sound space, she avoids walking into an object because a sound cue tells her that the object is in her near environment and roughly where it is. Various types of transformations are possible depending upon the user's needs and preferences. As all people are different, each user has a personalized profile that directs the transformation process. More generally, the environment to be transformed may include aspects of artificial or enhanced reality. The transformed environmental information can be presented to the user in a number of ways, such as in haptic feedback, as directional audio, through oral stimulation, or through modified visual display.

Abstract: Uplink control channel group and cross-carrier scheduling is disclosed for cooperative communications of a virtual UE. In an aspect, a UE reports a cooperative configuration with member UEs of a virtual UE and reports associations between a plurality of component carriers (CCs) allocated to a cell group and each member UE of the virtual UE. The UE may then receive an uplink control transmission configuration message dividing each member UE into an assigned uplink control transmission group and assign one or more component CCs into one or more CC sets, wherein each CC set is assigned to each uplink control transmission group. The UE may receive an uplink scheduling message from a serving base station, wherein the uplink scheduling message includes an uplink schedule for CCs within the CC set assigned to an uplink control transmission group associated with the UE. Other aspects and features are also claimed and described.

Abstract: Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a user equipment (UE) may transmit a beam applicability report that indicates beam applicability information corresponding to one or more physical channels for a UE cooperation operation. The UE may communicate with at least one wireless communication device in the UE cooperation operation based at least in part on the beam applicability information. Numerous other aspects are described.

Abstract: Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a user equipment (UE) may receive a control message, wherein the control message includes, for a multi-panel transmission, a first sounding reference signal (SRS) resource indicator (SRI) and a second SRI. The UE may determine power control information for the multi-panel transmission, wherein the power control information includes first power control information for a first transmission and second power control information for a second transmission. The UE may transmit the first transmission and the second transmission, in accordance with the first power control information and the second power control information, respectively, using a set of panels. Numerous other aspects are described.

Abstract: Embodiments of the present invention relate to a method, system and computer program product for application programming interface (API) management. According to the method, in response to a first response from an API provider indicating a failure of a first API request initiated by an API requestor, a second API request is generated at least based on the first API request. The second API request is transmitted to the API provider. A second response to the second API request is received from the API provider. A third response is provided to the API requestor based on the second response.