finding
active
finding:b8-final-accuracy-92-4-1-8B8 final accuracy 92.4 ± 1.8%
Accuracy at k=16 shots for B8.
Source paper
extracted_from(2025) · Edward Yi Chang · Kaya, Zeyneb N. · Ethan Chang
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Communities (3)
community
- CoT effects on generalization, multimodal QA accuracy, and AI safety alignment training.
- ScienceQA and related vision-language tasks evaluated via explicit reasoning steps, spanning 738M-parameter models with 89-95% accuracy ranges.
- Three benchmarks (B8, B9, B10) with mean accuracy and standard deviation metrics.
Questions (1)
question
- Second research question in E2
Related by similarity (8)
cosine ≥ 0.65 · no typed edgeEntities in the same semantic neighborhood but without a typed relation to this one — candidates for new edges or unrecognized duplicates.
- Accuracy at k=16 shots for B10.
- Accuracy at k=16 shots for B9.
- Binary detection adjusted accuracy reaches 97.3% at layer 0 with α=5 before baseline control is appliedfinding0.770The misleadingly high result that prior paradigm would report as evidence of introspection
- Baseline accuracy when reflection is suppressed.
- CalmeRys-78B Perspectives accuracy slightly reduced to 95.2% ± 2.21% after SOO fine-tuningfinding0.739SOO fine-tuning caused slight reduction in perspective-taking accuracy for the largest model
- Demonstrates that stronger models are largely insensitive to reflection manipulation
- Core negative result: the binary detection paradigm cannot distinguish genuine introspection from uniform output bias
- SOO fine-tuning did not collapse Gemma-2-27B self-other distinction needed for perspective-taking