HyperThink: Hypernetwork writes per-question weight updates so LLMs skip long CoT
mengyer · x · 2026-10-06
HyperThink, a COLM 2026 paper co-led by @Jacklume and @kdgyun425, proposes letting a hypernetwork write a per-question weight update to an LLM, letting it skip the long thinking trace and move toward accurate System 1 reasoning — thinking in weights rather than tokens.
The work is being presented at COLM on Oct 6, 4:30–6:30 PM, board #97, Franciscan C. By shifting reasoning from token generation into the weight space, the approach hints at big inference-cost savings, though full results are in the original thread.
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