| ## 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"} | |