| #!/bin/bash |
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| DATASET="musique" |
| N=100 |
| BASE="python src/passage_entity/benchmark_runner.py --task multihop --dataset $DATASET --num_queries $N --embedding_model openai-small --skip_qa" |
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| echo "======================================================================" |
| echo " QAFD-RAG Query-Awareness Ablation (${DATASET}, ${N} queries)" |
| echo "======================================================================" |
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| echo "" |
| echo "[1/7] Baseline (original, all QA flags = 0)" |
| $BASE --save_dir outputs_ablation/baseline 2>&1 | grep -E "Recall@|QAFD completed|Retrieval done" |
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| echo "" |
| echo "[2/7] Phase 1: qa_sink_gamma=0.5" |
| $BASE --qa_sink_gamma 0.5 --save_dir outputs_ablation/sink_05 2>&1 | grep -E "Recall@|QAFD completed|Retrieval done" |
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| echo "" |
| echo "[3/7] Phase 1: qa_sink_gamma=1.0" |
| $BASE --qa_sink_gamma 1.0 --save_dir outputs_ablation/sink_10 2>&1 | grep -E "Recall@|QAFD completed|Retrieval done" |
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| echo "" |
| echo "[4/7] Phase 2: qa_warm_delta=0.5" |
| $BASE --qa_warm_delta 0.5 --save_dir outputs_ablation/warm_05 2>&1 | grep -E "Recall@|QAFD completed|Retrieval done" |
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| echo "" |
| echo "[5/7] Phase 3: qa_post_lambda=0.5" |
| $BASE --qa_post_lambda 0.5 --save_dir outputs_ablation/post_05 2>&1 | grep -E "Recall@|QAFD completed|Retrieval done" |
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| echo "" |
| echo "[6/7] Phase 3: qa_post_lambda=1.0" |
| $BASE --qa_post_lambda 1.0 --save_dir outputs_ablation/post_10 2>&1 | grep -E "Recall@|QAFD completed|Retrieval done" |
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| echo "" |
| echo "[7/7] Combined: sink=0.5 + warm=0.5 + post=0.5" |
| $BASE --qa_sink_gamma 0.5 --qa_warm_delta 0.5 --qa_post_lambda 0.5 --save_dir outputs_ablation/combined 2>&1 | grep -E "Recall@|QAFD completed|Retrieval done" |
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| echo "" |
| echo "======================================================================" |
| echo " ALL EXPERIMENTS COMPLETE" |
| echo "======================================================================" |
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