Abstract: One or more computer-implemented methods, computer systems and/or computer program products of use provided herein relate to employing a task attention mechanism for context window augmentation of a large language model (LLM). In various embodiments, a computer-implemented method comprises receiving, at a machine learning model, first text data. The computer-implemented method further comprises determining, via the machine learning model, a token length of the first text data.

Abstract: Mechanisms are provided for automatically predicting vehicle weight of a moving vehicle. Vehicle operation data is obtained from one or more on-board sensors/systems of the vehicle and features are extracted. The features are filtered based on a required working condition of the vehicle to identify intervals of features having valid feature data to thereby generate a filtered valid data. The filtered valid data is processed by a first artificial intelligence (AI) computer model based on time slices of the filtered valid data to generate a first prediction of vehicle weight, and by a second AI computer model based on buckets of key variables to generate a second prediction of vehicle weight. The first prediction is fused with the second prediction to generate a final prediction of vehicle weight which is output to downstream computing logic.

Abstract: Mechanisms are provided for automatically predicting vehicle weight of a moving vehicle. Vehicle operation data is obtained from one or more on-board sensors/systems of the vehicle and features are extracted. The features are filtered based on a required working condition of the vehicle to identify intervals of features having valid feature data to thereby generate a filtered valid data. The filtered valid data is processed by a first artificial intelligence (AI) computer model based on time slices of the filtered valid data to generate a first prediction of vehicle weight, and by a second AI computer model based on buckets of key variables to generate a second prediction of vehicle weight. The first prediction is fused with the second prediction to generate a final prediction of vehicle weight which is output to downstream computing logic.

Abstract: A method, computer program, and computer system are provided for performing multiple machine learning tasks through a shared framework. Data corresponding to a plurality of predetermined machine learning tasks is received. One or more steps of the machine learning tasks associated with the received data is performed on the received data by a shared backbone of a machine learning model. The predetermined plurality of machine learning tasks is completed on the received data by a plurality of sub-networks associated with each of the plurality of predetermined machine learning tasks.