# SuperThoughts: Reasoning Tokens in Superposition

Page: https://stenobird.com/podcast/best-ai-papers-explained-7258006/superthoughts-reasoning-tokens-in-superposition
Text version: https://stenobird.com/podcast/best-ai-papers-explained-7258006/superthoughts-reasoning-tokens-in-superposition.md
Podcast: [Best AI papers explained](https://stenobird.com/podcast/best-ai-papers-explained-7258006)
Published: 2026-06-26T19:42:52+00:00
Episode link: https://podcasters.spotify.com/pod/show/ehwkang/episodes/SuperThoughts-Reasoning-Tokens-in-Superposition-e3lasbo
Audio file: https://anchor.fm/s/1026675f8/podcast/play/122040120/https%3A%2F%2Fd3ctxlq1ktw2nl.cloudfront.net%2Fstaging%2F2026-5-26%2F72729b04-9150-caaf-b360-bafdfba429f7.m4a
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JSON: https://stenobird.com/v1/public/podcasts/best-ai-papers-explained-7258006/episodes/superthoughts-reasoning-tokens-in-superposition
Duration seconds: 1140

## Resource

SuperThoughts is a novel framework designed to accelerate the Chain-of-Thought (CoT) reasoning process in large language models by processing tokens in superposition. Unlike traditional models that generate tokens sequentially, this method uses a compressor to fuse pairs of consecutive tokens into single latent representations, effectively halving the number of required forward passes. To ensure accuracy is not sacrificed for speed, the system employs a Multi-Token Prediction (MTP) module and a confidence-based adaptive mechanism that reverts to standard decoding when the model is uncertain. Experimental results on complex mathematical and scientific benchmarks show that SuperThoughts reduces reasoning length by 20–35% while maintaining performance within a few percentage points of the original baseline. The research highlights that larger models are particularly adept at handling this compression, achieving significant wall-clock time reductions during inference. Ultimately, this approach offers a more efficient way to utilize test-time compute without losing the dense supervision provided by discrete token training.

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## Transcript

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