InternBootcamp/examples/pipelines/autogen_configs/korLogicPropositionalLogicConcepts_test.json
Yongkang Chen a8249acc18
update to tech report version (#10)
* feat(run_eval): add checkpoint resume functionality and update example documentation;
- update new bootcamp benchmark dataset

* refactor(data_pipeline): optimize data generation pipeline; add multiple preset configurations for data generation

* docs: update bootcamp list and add new scripts

- Update Fulllist_InternBootcamp.md with new bootcamps and categories
- Add new scripts to .gitignore:
  - examples/pipelines/filter_autogen_configs.py
  - examples/pipelines/quickgen_data_configs_from_eval_meta.py
- Update dependencies in setup.py:
  - Add scipy and scikit-learn

* refactor(internbootcamp): update bootcamp modules and improve error handling

- Update import statements in __init__.py files
- Add timestamp to target directory name in verl_data_preprocess.py
- Improve error handling and scoring logic in bootcamp_judger.py
- Remove unnecessary comments and update puzzle descriptions in multiple files
2025-08-28 12:39:47 +08:00

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[
{
"s_list": [
"metals",
"products",
"students",
"mammals",
"pencils",
"stars",
"individual businesses"
],
"p_list": [
"conductive",
"qualified",
"like mathematics",
"warm-blooded animals",
"pens",
"planets",
"paid taxes"
],
"problem_types": [
"components",
"proposition_type",
"relationship_exists",
"relationship_type",
"truth_value"
]
},
{
"s_list": [
"students",
"animals",
"fruits",
"countries",
"books",
"cities"
],
"p_list": [
"happy",
"furry",
"sweet",
"large",
"interesting",
"populated"
],
"problem_types": [
"components",
"proposition_type",
"relationship_exists",
"truth_value"
]
},
{
"s_list": [
"plants",
"rocks",
"mountains",
"oceans",
"stars"
],
"p_list": [
"green",
"hard",
"tall",
"deep",
"bright"
],
"problem_types": [
"proposition_type",
"relationship_exists",
"truth_value"
]
}
]