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## Templatic Generation Tasks dataset (Jan-08-2025)

A synthetic dataset for containing examples of the Templatic Generation Task, as described
in our Oct 2024 Technical report: Mechanisms of Symbol Processing for In-context Learning in Transformer Networks.

Each example has 2-3 parts, separated by TAB character:
    x - the example input

    y - the example label

    info - OPTIONAL text identifying the type of example (for optional filtering during training)


# Currently available tasks:
    1_shot_rlw:          each example is 1 sample input/output pair + input cue; random two-letter words

    2_shot_rlw           each example is 2 sample input/output pairs + input cue; random two-letter words

    3_shot_rlw:          each example is 3 sample input/output pairs + input cue; random two-letter words

    5_shot_rlw:          each example is 5 sample input/output pairs + input cue; random two-letter words

    10_shot_rlw:         each example is 10 sample input/output pairs + input cue; random two-letter words


    1_shot_eng:          each example is 1 sample input/output pair + input cue; english words

    1_shot_rlw_10x:      same as 1_shot_rlw, but with 10x as many training examples


# Each task contains the following splits:
    train               contains 1, 2, or 4 constituents; each with 1, 2, or 4 parts

    dev                 contains 1, 2, or 4 constituents; each with 1, 2, or 4 parts

    test                contains 1, 2, or 4 constituents; each with 1, 2, or 4 parts

    ood_lexical         the constituent part vocab is held out from training (except for the echo examples)

    ood_cons_len_3      all templates have constituents have 3 parts

    ood_cons_len_5      all templates have constituents have 5 parts

    ood_cons_len_7      all templates have constituents have 7 parts

    ood_cons_len_10     all templates have constituents have 10 parts

    ood_cons_count_3    all templates have 3 constituents

    ood_cons_count_5    all templates have 5 constituents

    ood_cons_count_7    all templates have 7 constituents

    ood_cons_count_10   all templates have 10 constituents


Definitions:
    - echo examples: use to introduce out-of-distribution vocabulary symbols to the model (in the train split)
    - template - used to generate an example (input/output sample pairs, cue input, gold output)

Normal example:
    Q oy xf kq be ` ? jp A jp = . Q jf ty zu np ` ? cx A	cx = .	{"cons_count": "Q2A1", "cons_len": "Q41.Q41"}


    breakdown:

        1 sample input:     Q oy xf kq be ` ? jp A

        1 sample output:    jp = .

        cue input:          Q jf ty zu np ` ? cx A

        gold output:        cx = .

        example info:       {"cons_count": "Q2A1", "cons_len": "Q41.Q41"}


Echo example:
    Q ZW A ZW . Q VI A	VI .	{"type": "echo"}


    breakdown:

        1 sample input:     Q ZW A

        1 sample output:    ZW .

        cue input:          Q VI A

        gold output:        VI .

        example info:       {"type": "echo"}