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End of preview. Expand in Data Studio
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Check out the documentation for more information.
laion/qasper-v2
LLM-judge-verified version of mlfoundations-dev/qasper-sandboxes.
Each task follows the nemotron_gym LLM-judge verifier contract:
instruction.md— the original task instruction, with submission guidance appended directing the agent to write its answer to/app/response.txt.tests/test_state.py— a pytest-runnable LLM judge that reads/app/response.txt(legacy/app/answer.txtfallback), readstests/verifier_data.jsonfor the instruction + rubric, callslitellm.completion(defaultopenai/gpt-4o-mini, temperature=0) with the rubric, parses\boxed{<score>}, and writes the float score to/logs/verifier/reward.txt.tests/test.sh— defaults reward to 0, then runspython3 -m pytest /tests/test_state.py.tests/verifier_data.json— the task instruction + a per-dataset rubric.environment/Dockerfile—ubuntu:24.04+ python3 + pip + openai + pytest- litellm.
task.toml—LLM_JUDGE_TASK_TOML, soOPENAI_API_KEY/JUDGE_MODELpropagate into the verifier container via[verifier].env(OPENAI_API_KEYis required at trial time).
QASPER paper-QA tasks. Each task names a paper and asks a question (the paper text is sometimes included). Graded by an LLM judge on correctness / completeness / groundedness in the paper.
Rubric: correctness / completeness / groundedness
10000 tasks.
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