An Accuracy-Oriented Divide-and-Conquer Strategy for Recognizing Textual Entailment.
Bibliographic record
Abstract
The Two-Way Task: Run1: TAC-M, TS-M, and Tri-BM Run2: TAC-M, TS-M, and BoW-BM Run3: TAC-M, TS-M, NE-M, & Tri-BM, BoW-BM The Three-Way Task: Run1: TAC-M, TS-M, and Tri-BM, BoWBM Run2: TAC-M, TS-M, NE-M (partial), and Tri-BM, BoW-BM Run3: TAC-M, TS-M, NE-M, and Tri-BM, BoW-BM From Two-Way to Three-Way: If BoW-BM=YES & Tri-BM=NO then CONTRADICTION If BoW-BM=YES & Tri-BM=YES then ENTAILMENT Others UNKNOWN Tasks TAC-M TS-M NE-M BoW-BM Tri-BM Run1 Run2 Run3 IR(300) 75.0%/4 76.5%/85 61.0%/164 63.3% 54.3% 66.0% 72.3% 71.7% QA(200) 90.0%/10 73.2%/82 54.8%/93 49.0% 53.5% 73.0% 72.0% 74.0% SUM(200) 83.3%/6 74.5%/51 55.2%/67 63.5% 54.0% 64.0% 69.5% 71.5%
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.017 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.024 | 0.012 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".