73d9d93db9
IBM's MTRAG benchmark (ClapNQ domain, pinned repo SHA): retrieval with Recall@k/nDCG@k against binary qrels, gold-prefix QA replaying reference conversation prefixes as message history, and live-session replay carrying the model's own answers and tool history across turns. Corpus population gains a bounded, resumable batched ingest path. ConversationInput case type with transcript rendering for the judge, eligibility-aware citation scoring, refusal precision/recall via a label-aware RefusalJudge, per-turn verdicts with judged-turn coverage, and per-turn tool-traffic attributes counted from each turn's new messages so the arrays survive prior-turn compaction. |
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| .. | ||
| __init__.py | ||
| test_benchmark.py | ||
| test_capability_runner.py | ||
| test_citation_evaluators.py | ||
| test_config.py | ||
| test_conversation_evaluator.py | ||
| test_datasets.py | ||
| test_evaluators.py | ||
| test_mtrag.py | ||
| test_numbers.py | ||
| test_reference_configs.py | ||
| test_submission.py | ||