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jadoont/README.md

Tayyaba Jadoon

professional skeptic of impressive-looking benchmark results


reward-hacking-gym — A Q-learning agent finds a reward exploit I didn't design: 27.5 mean reward, 0% true task success. A held-out audit independent of the training code catches it and gates CI. Repaired via potential-based shaping (Ng et al., 1999) — audit passes at 1.00.

sovereign-rag-ratchet — A self-improving RAG pipeline for air-gapped deployment whose optimizer never sees the evaluator. Caught a planted prompt-injection cheat (+0.33 visible accuracy, −0.33 held-out) and auto-reverted it.

cot-scratchpad-research — Direct vs. Chain-of-Thought vs. Scratchpad on a 0.79M-parameter transformer. The scratchpad model invented its own carry notation unprompted — then failed out of distribution exactly where the others did.

watt-bench — Discrete-event simulation benchmark treating rack-level power budgets as hard constraints and tokens-per-watt as a first-class metric. On real Azure traces: 1,000+ thermal throttle events for latency-greedy scheduling, zero for power-aware.


LinkedIn · X

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  1. watt-bench watt-bench Public

    Open benchmark for power-constrained LLM inference scheduling. Tokens per watt as a first-class metric.

    Python

  2. sovereign-rag-ratchet sovereign-rag-ratchet Public

    Safe self-improving RAG for sovereign deployments — an overnight ratchet loop with a guardrail that catches metric-gaming. Built on Cohere Embed + Rerank + Command R+.

    Python 1

  3. cot-scratchpad-research cot-scratchpad-research Public

    Direct vs CoT vs Scratchpad on a 0.79M-param transformer: emergent carry notation, identical out-of-distribution failure

    Python 1

  4. reward-hacking-gym reward-hacking-gym Public

    RL agent finds an undesigned reward exploit — 27.5 reward, 0% task success — caught by a held-out audit that gates CI

    Python 1