Abstract: Example solutions for using natural language (NL) for complex optimization problems in operations research (OR) include: receiving a user input for an OR problem; generating an NL prompt based on at least the user input, the NL prompt comprising an objective, a variable, input data, and a constraint; using a large language model (LLM), generating a domain-specific language (DSL) passage based on at least the NL prompt, the DSL passage representing the OR problem; transpiling the DSL passage into a programming language passage; solving the OR problem, wherein solving the OR problem comprises executing the programming language passage to generate a problem solution; and generating a report of the problem solution.

Abstract: Methods, systems, and storage media for modeling subjects in a virtual environment are disclosed. Exemplary implementations may: receiving, from a client device, image data including at least one subject; extracting, from the image data, a face of the at least one subject and an object interacting with the face, wherein the object may be glasses worn by the subject; generating a set of face primitives based on the face, the set of face primitives comprising geometry and appearance information; generating a set of object primitives based on a set of latent codes for the object; generating an appearance model of photometric interactions between the face and the object; and rendering an avatar in the virtual environment based on the appearance model, the set of face primitives, and the set of object primitives.

Abstract: A system is described herein for managing digital transactions over a network with incomplete information. The system includes a data collection component and a transaction control component that may employ a prospective control model that is trained with fully matured data as well as partially matured data regarding past digital transactions. The transaction control component is configured to estimate an inauthentic rate of inauthentic digital transactions being wrongly approved for a current time period. A set of future reference values may be determined based on the estimated inauthentic rate. The set of future reference values relate to a predicted future decision made for the digital transaction. A set of current values may be determined based on the set of future reference values. Based on the set of current values, the transaction control component may determine whether the digital transaction should be rejected as inauthentic or approved as authentic.