Abstract: Methods and systems for training and deploying a neural network mode include training a modular encoder model using training data collected from heterogeneous system types. The modular encoder model includes layers of neural network blocks and a selectively enabled connections between neural network blocks of adjacent layers. Each neural network block includes neural network layers. The modular encoder model is deployed to a system corresponding to one of the heterogeneous system types.

Abstract: Provided is a bispecific chimeric antigen receptor targeting CD19 and CD22, which comprises extracellular antigen binding domains of heavy-chain variable regions and light-chain variable regions of anti-CD19 and anti-CD22 antibodies. Further provided is a bispecific CAR-T cell targeting CD19 and CD22.

Abstract: A polymer liquid crystal dimming box, a manufacturing method thereof, and a display module are provided. The polymer liquid crystal dimming box includes a first substrate, a second substrate, a polymer liquid crystal layer, a frame adhesive layer and a light-shielding structure. The light-shielding structure is disposed between the frame adhesive layer and the polymer liquid crystal layer and surrounds the polymer liquid crystal layer. The light-shielding structure is used to absorb ultraviolet light obliquely incident during the curing process of the frame adhesive layer. In this way, the problem that the polymer liquid crystal layer is cured in advance due to ultraviolet light irradiation can be avoided, the edge failure of the polymer liquid crystal dimming box can be improved, which is conducive to mass production.

Abstract: The present disclosure provides a semiconductor epitaxial structure, including a substrate, a first-type semiconductor layer, an active region comprising multiple quantum layers stacked in sequence along a first direction, and a stress release layer between two adjacent quantum layers, wherein the first direction is perpendicular to the substrate and is directed from the substrate to the first-type semiconductor layer, and a second-type semiconductor layer sequentially stacked on a surface of the substrate; wherein the quantum layers each comprises barrier layers and potential well layers, and the barrier layers are alternately stacked with the potential well layers, and wherein at least one of the quantum layers further comprises a growth temperature transition layer between a barrier layer and a potential well layer, or an electron confinement layer between a barrier layer and a potential well layer.

Abstract: Systems and methods for detecting artificial intelligence (AI) generated computer code. Lines of code can be masked from a candidate code to obtain perturbed codes. Missing code can be generated from the perturbed codes by employing an AI code generator model to obtain machine-filled codes. Probabilities of the candidate code probability and the machine-filled codes as AI-generated can be predicted by employing a surrogate model. The candidate code can be distinguished as AI-generated by comparing the probabilities against a detection threshold to obtain detection results.

Abstract: Methods and systems include embedding an input query, including contextual information. Performance and cost of executing the input query are predicted on each of a set of language models. The prediction is performed using a multi-armed bandit approach with each of the language models being represented by a respective arm. The input query is executed on a selected model that has a best balance of performance and cost.

Abstract: The present application discloses a method for analyzing a layout pattern density, comprising: step 1, providing layouts of a chip, and merging the layouts to form a wafer level layout, wherein the wafer level layout presents a first circle in a top view, and the layout comprises a plurality of mask layers; step 2, segmenting the first circle to form a plurality of check windows; step 3, searching for the mask layer containing the patterns having a height morphology, and combining the found mask layers into a pattern layer combination; step 4, sequentially calculating a pattern density of the pattern layer combination in each check window; and step 5, recording the pattern density in each check window on a third circle to form a wafer level pattern density distribution diagram. The present application can predict a height morphology of a top surface of a wafer related to a layout.

Abstract: Systems and methods for detecting artificial intelligence (AI) generated text. A candidate text can be truncated to obtain a prefix text and a remainder text by employing a truncation module. Regenerated model texts can be regenerated by utilizing the prefix text by employing an AI text generation model. Detection results can be predicted by comparing n-gram similarities of the regenerated model texts and the remainder text. The candidate text can be distinguished as AI generated text by providing explanation texts based on the detection results.

Abstract: Systems and methods for detecting artificial intelligence (AI) generated computer code. Lines of code can be masked from a candidate code to obtain perturbed codes. Missing code can be generated from the perturbed codes by employing an AI code generator model to obtain machine-filled codes. Probabilities of the candidate code probability and the machine-filled codes as AI-generated can be predicted by employing a surrogate model. The candidate code can be distinguished as AI-generated by comparing the probabilities against a detection threshold to obtain detection results.

Abstract: Systems and methods for detecting artificial intelligence (AI) generated computer code. Lines of code can be masked from a candidate code to obtain perturbed codes. Missing code can be generated from the perturbed codes by employing an AI code generator model to obtain machine-filled codes. Probabilities of the candidate code probability and the machine-filled codes as AI-generated can be predicted by employing a surrogate model. The candidate code can be distinguished as AI-generated by comparing the probabilities against a detection threshold to obtain detection results.

Abstract: Provided are a light-emitting master plate, a light-emitting panel, and a cutting method for a light-emitting master plate, and the present disclosure relates to the field of display technology. A light-emitting master plate includes at least one display area and multiple light-emitting areas arranged in an array in the display area. The light-emitting area includes a light-emitting element and a driver circuit. At least part of the light-emitting areas are provided with a cutting mark.

Abstract: Methods and systems include fine-tuning a classifier while masking part of a training dataset to cause a distribution of the classifier to match a distribution of an explainer model. A performance of the explainer model is determined using the fine-tuned classifier to ensure that the explainer has an above-threshold fidelity. A downstream task is performed using the classifier and the explainer model.

Abstract: Methods and systems for code generation include generating code for tree root nodes responsive to a query that specifies a task. The tree root nodes are expanded into trees based on foresting tree search using scattering to select varied directional prompts and sharing direction information between the trees. Generated code is output corresponding to a node from the trees that satisfies a test case.

Abstract: Methods and systems include fine-tuning a small language model (SLM) to determine a first probability distribution. Text is generated with a large language model (LLM), including modifying a second probability distribution of the LLM using the first probability distribution so that the text is human-like. A detector is trained, using the text, to determine whether input text is generated by a human or by a language model.

Abstract: A CD70 antibody and a chimeric antigen receptor (CAR) that can specifically bind to a CD70 protein. The CAR comprises a CD70 binding domain, a transmembrane domain, a costimulatory domain, and an intracellular signaling domain. Further disclosed is an application of the antibody and the CAR for treating diseases or conditions related to CD70 expression.

Abstract: A method of forming a semiconductor memory structure is disclosed. A substrate having thereon a device cell region and a contact forming region in proximity to the device cell region is provided. A memory cell transistor is formed on the substrate within the device cell region. The memory cell transistor includes a gate and a charge storage structure between the gate and the substrate. The gate comprises an extended portion within the contact forming region. A first spacer is formed on a sidewall of the gate within the device cell region. The first spacer has a first spacer height. A second spacer is formed on a sidewall of the extended portion of the gate within the contact forming region. The second spacer has a second spacer height that is greater than the first spacer height.

Abstract: A method for executing a multi-task deep learning model for learning trends in multivariate time series is presented. The method includes collecting multi-variate time series data from a plurality of sensors, jointly learning both local and global contextual features for predicting a trend of the multivariate time series by employing a tensorized long short-term memory (LSTM) with adaptive shared memory (TLASM) to learn historical dependency of historical trends, and employing a multi-task one-dimensional convolutional neural network (1dCNN) to extract salient features from local raw time series data to model a short-term dependency between local time series data and subsequent trends.

Abstract: Methods and systems include estimating situational weights for an agent based on a distance measure for steps taken by the agent. The situational weights are combined with uncertainties from the agent for the steps to determine a total uncertainty for an action indicated by the agent. The action indicated by the agent is performed responsive to the total uncertainty.

Abstract: Methods and systems for image analysis include initializing a set of initial regions that segment an input image. The initial regions are split into split regions. The split regions are merged into combined regions. Image analysis is performed on the combined regions using a visual language model, responsive to a query. An action is performed responsive to the image analysis in a downstream task.

Abstract: Methods and systems include fine-tuning a surrogate model, using example images generated by a target model, to match a distribution of the target model. A new image is masked to generate a masked image. A recovered image is generated that fills in a masked region of the masked image using the surrogate model. The recovered image is compared to the new image to determine that the new image was generated by the target model. An action is performed responsive to the determination that the new image was generated by the target model.