Feels like the more interesting trend is that Git itself is becoming an implementation detail.
There are already several openreview comments alleging academic misconduct around TurboQuant: https://openreview.net/forum?id=tO3ASKZlok Some write-ups argue that this was deliberate rather than a good-faith mistake:…
The public comments on Openreview now include explicit allegations that the TurboQuant paper knowingly misrepresented RaBitQ and understated RaBitQ’s results. The RaBitQ authors also report in a technical note that…
went through ICLR review: scores 4 4 6 10, serious? open-source implementations: where is the official code? CUDA kernels: where?
seems to be a scam "The TurboQuant paper (ICLR 2026) contains serious issues in how it describes RaBitQ, including incorrect technical claims and misleading theory/experiment comparisons. We flagged these issues to the…
This is not an LLM inference result. Table 2 is the part I find most questionable. Claiming orders-of-magnitude improvements in vector search over standard methods is an extraordinary claim. If it actually held up in…
They confirmed on the accuracy on NIAH but didn't reproduce the claimed 8x efficiency.
Pied Piper vibes. As far as I can tell, this algorithm is hardly compatible with modern GPU architectures. My guess is that’s why the paper reports accuracy-vs-space, but conveniently avoids reporting inference…
true
Feels like the more interesting trend is that Git itself is becoming an implementation detail.
There are already several openreview comments alleging academic misconduct around TurboQuant: https://openreview.net/forum?id=tO3ASKZlok Some write-ups argue that this was deliberate rather than a good-faith mistake:…
The public comments on Openreview now include explicit allegations that the TurboQuant paper knowingly misrepresented RaBitQ and understated RaBitQ’s results. The RaBitQ authors also report in a technical note that…
went through ICLR review: scores 4 4 6 10, serious? open-source implementations: where is the official code? CUDA kernels: where?
seems to be a scam "The TurboQuant paper (ICLR 2026) contains serious issues in how it describes RaBitQ, including incorrect technical claims and misleading theory/experiment comparisons. We flagged these issues to the…
This is not an LLM inference result. Table 2 is the part I find most questionable. Claiming orders-of-magnitude improvements in vector search over standard methods is an extraordinary claim. If it actually held up in…
They confirmed on the accuracy on NIAH but didn't reproduce the claimed 8x efficiency.
Pied Piper vibes. As far as I can tell, this algorithm is hardly compatible with modern GPU architectures. My guess is that’s why the paper reports accuracy-vs-space, but conveniently avoids reporting inference…
true