SYSTEMS AND METHODS FOR TRAINING LANGUAGE MODEL PARAMETERS GENERATE NETWORK APPLICATION INTERFACES ACCORDING TO DISTRIBUTED DATA SOURCES

1 . A system, comprising:

one or more processors coupled to non-transitory memory, the one or more processors configured to:

maintain, in one or more data structures, data corresponding to a plurality of historical wager opportunities and a set of formatting instructions;

generate, using the one or more data structures, a training dataset comprising at least one first training example including:

(i) a respective input context comprising data of a first wager opportunity of the plurality of wager opportunities, and

(ii) a respective output message comprising display instructions for the first wager opportunity generated according to the set of formatting instructions; and

update a language model using the training dataset.

2 . The system of claim 1 , wherein the one or more data structures further comprise a plurality of deep links corresponding to a plurality of application interfaces of an application, and wherein the one or more processors are further configured to:

generate the training dataset to comprise a second training example including:

(i) a respective input context comprising data of a first deep link of the plurality of deep links, and

(ii) a respective output message comprising second display instructions for the first deep link generated according to a second set of formatting instructions.

3 . The system of claim 2 , wherein the second set of formatting instructions are different from the first set of formatting instructions.

4 . The system of claim 1 , wherein the one or more processors are further configured to:

maintain a plurality of sets of formatting instructions, each set of the plurality of sets of formatting instructions corresponding to a respective type of wager opportunity, the plurality of sets of formatting instructions including the set of formatting instructions; and

select the set of formatting instructions from the plurality of sets of formatting instructions for the at least one training example based on a type of the first wager opportunity.

5 . The system of claim 1 , wherein the one or more processors are further configured to:

generate the input context to include a prompt requesting a wager recommendation and data of the first wager opportunity selected based on the prompt.

6 . The system of claim 5 , wherein the data of the first wager opportunity corresponds to a first data structure format and the display instructions for the first wager opportunity correspond to a second data structure format.

7 . The system of claim 1 , wherein the first wager opportunity comprises a parlay wager opportunity comprising a plurality of legs, and wherein the display instructions are configured to cause presentation of a content item identifying the plurality of legs of the parlay wager opportunity.

8 . The system of claim 1 , wherein the display instructions are configured to present a content item comprising an interactive element that, when interacted with, causes transmission of a request to place a wager corresponding to the first wager opportunity.

9 . The system of claim 1 , wherein the display instructions comprise at least one identifier of a network location from which odds for the first wager opportunity are to be retrieved.

10 . The system of claim 1 , wherein the one or more processors are further configured to:

update the language model to generate at least one token identifying a start position of the display instructions in output generated by the language model.

11 . A method, comprising:

maintaining, by one or more processors coupled to non-transitory memory, in one or more data structures, data corresponding to a plurality of historical wager opportunities and a set of formatting instructions;

generating, by the one or more processors, using the one or more data structures, a training dataset comprising at least one first training example including:

(i) a respective input context comprising data of a first wager opportunity of the plurality of wager opportunities, and

(ii) a respective output message comprising display instructions for the first wager opportunity generated according to the set of formatting instructions; and

updating, by the one or more processors, a language model using the training dataset.

12 . The method of claim 11 , wherein the one or more data structures further comprise a plurality of deep links corresponding to a plurality of application interfaces of an application, and further comprising:

generating, by the one or more processors, the training dataset to comprise a second training example including:

(i) a respective input context comprising data of a first deep link of the plurality of deep links, and

(ii) a respective output message comprising second display instructions for the first deep link generated according to a second set of formatting instructions.

13 . The method of claim 12 , wherein the second set of formatting instructions are different from the first set of formatting instructions.

14 . The method of claim 11 , further comprising:

maintaining, by the one or more processors, a plurality of sets of formatting instructions, each set of the plurality of sets of formatting instructions corresponding to a respective type of wager opportunity, the plurality of sets of formatting instructions including the set of formatting instructions; and

selecting, by the one or more processors, the set of formatting instructions from the plurality of sets of formatting instructions for the at least one training example based on a type of the first wager opportunity.

15 . The method of claim 11 , further comprising generating, by the one or more processors, the input context to include a prompt requesting a wager recommendation and data of the first wager opportunity selected based on the prompt.

16 . The method of claim 15 , wherein the data of the first wager opportunity corresponds to a first data structure format and the display instructions for the first wager opportunity correspond to a second data structure format.

17 . The method of claim 11 , wherein the first wager opportunity comprises a parlay wager opportunity comprising a plurality of legs, and wherein the display instructions are configured to cause presentation of a content item identifying the plurality of legs of the parlay wager opportunity.

18 . The method of claim 11 , wherein the display instructions are configured to present a content item comprising an interactive element that, when interacted with, causes transmission of a request to place a wager corresponding to the first wager opportunity.

19 . The method of claim 11 , wherein the display instructions comprise at least one identifier of a network location from which odds for the first wager opportunity are to be retrieved.

20 . The method of claim 11 , further comprising updating, by the one or more processors, the language model to generate at least one token identifying a start position of the display instructions in output generated by the language model.