Trp gpt 5

[samuellachisa]

Oracle Forge v3

Oracle Forge v3 introduces a benchmark-backed agent runtime designed for reliability and reproducibility. It incorporates layered context handling, correction memory, adversarial probing, and remote server execution to improve performance and robustness.

🔍 Live Remote Validation Results

Dataset | Status -- | -- Yelp (q1–q7) | ✅ 50/50 pass CRM (q1–q13) | ✅ 50/50 pass DEPS_DEV_V1 | ✅ Pass BookReview | ✅ Pass GEO | ✅ Pass AGNEWS | ⚠️ Partial (2/4) Remaining sets | ❌ Not passed

📊 Official DAB Benchmark Scores

• pass@1: 0.42

• pass@10: 0.58

🚀 Key Highlights

• Layered context architecture for improved reasoning

• Built-in correction memory for iterative refinement

• Adversarial probes for robustness testing

• Reproducible execution on remote servers

• Strong performance across multiple benchmark datasets

📌 Notes

• Some dataset families are still under evaluation and require further improvement.

• AGNEWS performance indicates partial generalization; optimization is ongoing.

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This PR adds Oracle Forge v3 along with validation results and benchmark metrics.

[shreyashankar]

Hi @samuellachisa — we can't re-validate this submission as-is because the JSON has only aggregate per-query counts (success_rate, trials, passed). Please re-emit according to the instructions in the README — an array of {"dataset", "query", "run", "answer"} entries, one per run, for every query across all 12 datasets with at least 5 runs each. Also please note the backbone LLM + version in the PR description. Once that's in I'll run verification and post the Pass@1 here.