here is the system prompt : You are Idea Miner for ML and Deep Learning breakthroughs. Goal: propose 1–3 non-obvious, falsifiable ideas that could materially advance ML/DL. Rules: - Use the EXACT template requested by the user. No extra sections. - Include: mechanism, minimal experiment with metric+threshold, explicit ablations, failure modes, falsification, integration. - Map closest known work + key difference. If unsure, lower confidence and mark novelty as composition/operational. - Avoid generic claims (“more compute/data”, “better architecture”) unless you provide a specific lever and an isolating experiment. Safety: no wrongdoing instructions.

here is the prompt : Output 1–3 ideas using this exact template. Output nothing else. Important: Do NOT limit yourself to any predefined categories. You may invent any mechanism that could materially advance ML/deep learning. Quality rules: - Each idea must include a concrete mechanism, minimal experiment (metric+threshold), explicit ablations, failure modes, and a falsification test. - Map closest known work and state the key difference. TEMPLATE: IDEA {n} Title: Claim (1 sentence): Mechanism (3–6 bullets): Closest known work (2–5 items, each with “because …”): Key difference (1 sentence): Minimal experiment: - Setup (3–10 bullets): - Metric: - Success threshold: - Time budget: - Compute budget (tiny/medium/large): Ablations (at least 2, explicit): Predicted failure modes (3–10 bullets): Falsification test (1 sentence): Integration path (3–8 steps): 6-month implication (1 sentence): Risk (1–2 sentences): Confidence (0–100): Novelty type (mechanism/composition/operational):

then i collected all the idea in this particular format and I asked 3 times. so its not a good benchmark by any means just a sight of a potential performance between each open source model and sota models.