Abstract: Method, system, and computer-readable storage media for optimizing fine-tuning of a Large Language Model (LLM) are disclosed. An adapter recommendation is generated for fine-tuning of the LLM based on input data and a desired output criterion corresponding to each of output aspects. Based on the adapter recommendation, initial coefficient values for coefficients that correspond with the output aspects and an initial ranking value are assigned. Once the coefficients and ranking value are assigned, an adaptive multi-objective low rank adaptation and uncertainty estimation are iteratively performed for a predefined number of iterations or until the desired criterion corresponding to each of the output aspects is achieved. Upon reaching the predefined number of iterations or achieving the desired criterion corresponding to each of the output aspects, an output value for each of the output aspects is derived. The derived output value is used for fine-tuning of the LLM.

Abstract: A device receives, as part of a gesture translation service, data that depicts gestures, wherein the data is image data or multimedia data. The device converts a set of frames that include the data to another set of frames that include modified data identifying a grayscale or black and white depiction of the gestures and generates graphical representations of the gestures identified by the modified data. The device selects, using a matching technique, a graphical representation of corresponding gestures that matches or satisfies a threshold level of similarity with the graphical representations of the gestures identified by the modified data. The device identifies response data that is representative of the corresponding gestures based on the response data being stored in association with an identifier of the graphical representation that has been selected. The device provides the response data to be displayed, via an interface, as text data or audio data.

Abstract: A device receives, as part of a gesture translation service, data that depicts gestures, wherein the data is image data or multimedia data. The device converts a set of frames that include the data to another set of frames that include modified data identifying a grayscale or black and white depiction of the gestures and generates graphical representations of the gestures identified by the modified data. The device selects, using a matching technique, a graphical representation of corresponding gestures that matches or satisfies a threshold level of similarity with the graphical representations of the gestures identified by the modified data. The device identifies response data that is representative of the corresponding gestures based on the response data being stored in association with an identifier of the graphical representation that has been selected. The device provides the response data to be displayed, via an interface, as text data or audio data.

Abstract: According to an example of the present disclosure, a software testing system is operable to test functionalities of a web application across different platforms. The software testing system can interact with different platforms via different drivers to facilitate multiplatform testing of the functionalities. Also, multiplatform test result views may be generated.

Abstract: According to an example of the present disclosure, a software testing system is operable to test functionalities of a web application across different platforms. The software testing system can interact with different platforms via different drivers to facilitate multiplatform testing of the functionalities. Also, multiplatform test result views may be generated.