On 6000 Qwen3-8B AIME traces, late-clustered moderate-to-severe backtracks are more common in incorrect outputs, enabling prefix-causal burst-aware filtering that outperforms fixed-length cutoffs at shallow and intermediate depths.
URL http://ieeexplore.ieee.org/document/ 7900006/
2 Pith papers cite this work, alongside 1,193 external citations. Polarity classification is still indexing.
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Looped-MoE models scale better than dense looped or standard transformers because routing changes across loops, and they enable stronger compute-quality trade-offs via early exits at loop boundaries.
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The Shape of Overthinking: Backtracking Bursts in Long Reasoning Traces
On 6000 Qwen3-8B AIME traces, late-clustered moderate-to-severe backtracks are more common in incorrect outputs, enabling prefix-causal burst-aware filtering that outperforms fixed-length cutoffs at shallow and intermediate depths.
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Sparse Layers are Critical to Scaling Looped Language Models
Looped-MoE models scale better than dense looped or standard transformers because routing changes across loops, and they enable stronger compute-quality trade-offs via early exits at loop boundaries.