RaBitQ First Author Publicly Challenges Google's TurboQuant Paper — Academic Credit Controversy Erupts

r/LocalLLaMA / r/MachineLearning·medium signal

Jianyang Gao, first author of the RaBitQ papers, posted directly to r/LocalLLaMA to address TurboQuant discussions in the local inference community. He documented three issues with Google's ICLR 2026 TurboQuant paper: it describes RaBitQ as having 'suboptimal guarantees' due to 'loose analysis' while omitting that both methods share the same core random rotation mechanism. The controversy spilled to r/MachineLearning (116↑, 18 comments) where the OpenReview comment chain was flagged. This matters for builders because TurboQuant's 6x KV cache compression is entering llama.cpp discussions. Reddit: r/LocalLLaMA (222↑, 41 comments).