Abstract: The present invention discloses IL-13 antibody, method of its preparation and use thereof. The IL-13 antibody comprises one or more of heavy chain CDR1, heavy chain CDR2 and heavy chain CDR3 of heavy chain variable region of the IL-13 antibody, and/or one or more of light chain CDR1, light chain CDR2, and light chain CDR3 of light chain variable region of the IL-13 antibody. The IL-13 antibody has a high affinity and can significantly inhibit the secretion of thymus activation-regulated chemokine and periostin as well as the expression of vascular cell adhesion molecule-1 induced by IL-13, it can significantly inhibit airway hyperresponsiveness in mice induced by IL-13, and therefore can be used in the preparation of drugs for preventing or treating IL-13 expression or dysfunction related diseases.

Abstract: The disclosed embodiments provide a system for processing scoring requests. During operation, the system matches an identifier for an entity in a scoring request to a cache entry in a score cache. Next, the system retrieves, from the cache entry, a previous value of a score generated by a machine learning model from previous values of features for the entity and a first encoded representation of the previous values of a subset of the features with greater than a threshold effect on the score. The system then compares the first encoded representation with a second encoded representation of the most recent values of the subset of the features for the entity. When the comparison indicates that the most recent values match the previous values, the system outputs the previous value of the score for the entity in a response to the scoring request.

Abstract: Technologies for determining performance gains for content item delivery based on modifications to content item selection parameters are provided. The disclosed techniques include implementing a multi-objective optimization model for content item selection using a value for a parameter. The model generates a first plurality of scores and a first ranking for content items. Subset of content items is selected for delivery based on the first ranking. New values for the parameter are identified and for each new value, the content item selection event is replayed. A second plurality of scores and a second ranking is generated for the content items, where the second ranking is different from the first ranking. A third plurality of scores and a third ranking is generated where the third ranking matches the second ranking. A set of gains is calculated for each new value, where each gain corresponds to a different objective of the model.

Abstract: Technologies for leveraging machine learning techniques to present content items to an entity based upon prior interaction history of the entity are provided. The disclosed techniques include identifying a first plurality of content items with which the entity has interacted during prior entity sessions. Interactions include selecting, viewing, or dismissing content items during prior entity sessions. For each content item in the first plurality, a learned embedding is identified, where each of the embeddings represent a vector of content item features mapped in a vector space. An aggregated embedding is generated based on the identified embeddings. A comparison is performed between the aggregated embedding and embeddings corresponding to a second plurality of content items. Based on the comparison, a subset of content items from the second plurality of content items is identified. The subset of content items is then presented on a computing device of the entity.

Abstract: Disclosed in the present invention are an antibody targeting LAG-3, a preparation method therefor and the use thereof. In particular, disclosed in the present invention is a novel monoclonal antibody targeting LAG-3. Also disclosed in the present invention is a method for the preparation of the monoclonal antibody. The monoclonal antibody of the present invention is capable of binding LAG-3 antigens with high specificity, and has very high affinity and significant activities such as anti-tumor activity.

Abstract: In an example the output of a machine learned model is a score is then compared to a threshold, and if the score transgresses the threshold, the corresponding item is available to be recommended to the user via the graphical user interface. In an example embodiment, rather than a fixed (static) threshold, a dynamic threshold is utilized. This dynamic threshold is based on a harmonic mean of probabilities utilized in the GLMix model. Specifically, the GLMix model may calculate and utilize the probability that a user will engage with a particular item via a graphical user interface, and also a probability that a user will dismiss a particular item via a graphical user interface.

Abstract: Techniques for user-defined quality control of resource usage are provided. In one technique, resource split data is received that indicates a split of a total resource amount that is associated with a content delivery campaign. In response, based on the split, a first resource amount and a second resource amount is determined, each a subset of the total resource amount. The first resource amount is associated with a first utilization strategy and a first mapping function and the second resource amount is associated with a second utilization strategy and a second mapping function. In response to receiving a request from a client device, an entity of the client device is determined and associated with the first mapping function. A quality score of the entity is determined and, based on the first mapping function and the quality score, an adjustment factor is determined. A content item selection event is conducted based on the adjustment factor.

Abstract: Anti-PD-1 antibodies and antigen-binding fragments thereof are described. Also described are nucleic acids encoding the antibodies, compositions comprising the antibodies, and methods of producing the antibodies and using the antibodies for treating or preventing diseases such as cancers and autoimmune diseases.

Abstract: The disclosed embodiments provide a system for predicting response rates. During operation, the system determines features representing historical applications to opportunities and historical responses to the historical applications by a poster of the opportunities, wherein the historical responses include interactions between the poster and candidates submitting the historical applications and notifications transmitted to the candidates of actions related to the historical applications by the poster. Next, the system applies one or more operations to the features to generate a predicted response rate of the poster to an application for an opportunity by a member of the online system. The system then compares the predicted response rate to a threshold to determine a recommendation related to the application by the member. Finally, the system outputs, to the member in a user interface of the online system, the recommendation in association with the opportunity.

Abstract: The disclosed embodiments provide a system for processing data. During operation, the system performs processing related to a first set of features for a first entity using a first series of embedding layers, wherein the processing includes applying each embedding layer in the first series of embedding layers to a concatenation of all outputs of one or more layers preceding the embedding layer. Next, the system obtains a first embedding as an output of a first final layer in the first series of embedding layers. The system then outputs the first embedding for use by a machine learning model.

Abstract: The present invention provides an anti-C5aR antibody and a preparation method and use thereof. The anti-C5aR antibody comprises one or more of the followings: a heavy chain CDR1, heavy chain CDR2 or heavy chain CDR3 of a heavy chain variable region of an anti-C5aR antibody, and one or more of the followings: a light chain CDR1, light chain CDR2 or light chain CDR3 of a light chain variable region of the anti-C5aR antibody. The anti-C5aR antibody has a high affinity to human C5aR protein and can block the binding of the C5aR protein to a C5a, thus downregulating or switching off a corresponding signaling pathway, stopping C5a directed migration of a neutrophil in vitro and inhibiting chemotaxis of the neutrophil.

Abstract: Provided herein are anti-PD-L1 antibodies and antigen-binding fragments thereof. Also provided are nucleic acids encoding the antibodies, compositions containing the antibodies, and methods of producing the antibodies and using the antibodies for treating or preventing diseases such as cancer, infectious diseases and autoimmune diseases.

Abstract: Instead of a fixed fee for a particular job application, discussed in some examples are methods, systems, and machine readable mediums which provide for a job posting service that utilizes a pay-per-click model. That is, job posters pay a fee for each time the member selects the job posting for further inquiry when that posting is shown to a member (called an impression). The fee that is paid is determined by the job poster. Selecting a job posting may comprise clicking on or otherwise entering an input signifying an intention to view the job.

Abstract: Techniques for generating cross features using a data driven approach are provided. Multiple possible splits of a numerical feature are identified. For each split, the numerical feature is transformed into a second feature based on the split, a cross feature is generated based on the second feature and a third (e.g., categorial) feature that is different than the first feature and the second feature, a predictive power of the cross feature is estimated, and the predictive power is added to a set of estimated predictive powers. After each split is considered, a cross feature that is associated with the highest estimated predictive power in the set of estimated predictive powers is selected. That first cross feature corresponds to a particular split from the multiple possible splits. The numerical feature is split based on the particular split to generate a bucketized version of the numerical feature.

Abstract: Technologies for determining performance gains for content item delivery based on modifications to content item selection parameters are provided. The disclosed techniques include implementing a multi-objective optimization model for content item selection using a value for a parameter. The model generates a first plurality of scores and a first ranking for content items. Subset of content items is selected for delivery based on the first ranking. New values for the parameter are identified and for each new value, the content item selection event is replayed. A second plurality of scores and a second ranking is generated for the content items, where the second ranking is different from the first ranking. A third plurality of scores and a third ranking is generated where the third ranking matches the second ranking. A set of gains is calculated for each new value, where each gain corresponds to a different objective of the model.

Abstract: Technologies for generating a graph containing clusters of feature attribute values for training a machine learning model for content item selection and delivery are provided. The disclosed techniques include, for each entity, of a plurality of entities, a system identifies transitions from one geographic location to another geographic location. A graph is generated based on the transitions associated with each entity. The graph comprises nodes representing geographic locations and edges connecting the nodes. Each of the edges connects two nodes, represents a transition from one geographic location to another geographic location, and each edge represents an edge weight value that is based on frequencies of transitions between geographic locations represented by the two connected nodes. The system generates a plurality of clusters from the nodes based upon the edge weight value of each edge. The system includes the plurality of clusters as features in a machine learning model.

Abstract: Provided in the present invention are a 4-1BB antibody and a preparation method and the use thereof. In particular, provided in the present invention are a 4-1BB antibody, which has high affinity to 4-1BB protein, can effectively activate the signal downstream of the 4-1BB and significantly increase expression quantities of IFN-? and IL-2 in human mixed lymphocytes or T lymphocytes, and can be used to treat cancers and autoimmune diseases.

Abstract: Methods, systems, and computer programs are presented for presenting return-on-investment (ROI) information, for budgeted services that resulted in a successful service delivery, on a user interface for setting the budget for a service request. One method includes an operation for identifying daily budgets for budgeted services that resulted in a successful service delivery (BSSSD). Each daily budget indicates an amount for spending in promotion of the BSSSD in an online service. The method further includes receiving a request, in a graphical user interface (GUI) of the online service, for posting a daily budget for a first budgeted service. Further, a performance value, associated with the daily budgets of the BSSSD that are similar to the first budgeted service, is selected. Further, the method includes causing presentation, by the one or more processors, of the performance value in the GUI.

Abstract: Methods, systems, and computer programs are presented for determining a recommended daily budget for a job post. One method includes operations for identifying an initial budget value for recommending a daily budget when a job poster is adding a job post, and for performing a test to determine responses of job posters when the recommended daily budget is presented as a function of a multiplier applied to the initial budget value. Further, the method includes operations for defining a model to determine committed bookings as a function of the multiplier, determining based on the model a value of the multiplier that maximizes the committed bookings, and setting a new initial budget value to the initial budget value times the value of the multiplier that maximizes the committed bookings. Additionally, the new initial budget value is presented in a user interface when job posters add new job posts.

Abstract: The present invention discloses IL-13 antibody, method of its preparation and use thereof. The IL-13 antibody comprises one or more of heavy chain CDR1, heavy chain CDR2 and heavy chain CDR3 of heavy chain variable region of the IL-13 antibody, and/or one or more of light chain CDR1, light chain CDR2, and light chain CDR3 of light chain variable region of the IL-13 antibody. The IL-13 antibody has a high affinity and can significantly inhibit the secretion of thymus activation-regulated chemokine and periostin as well as the expression of vascular cell adhesion molecule-1 induced by IL-13, it can significantly inhibit airway hyperresponsiveness in mice induced by IL-13, and therefore can be used in the preparation of drugs for preventing or treating IL-13 expression or dysfunction related diseases.