mskkm

7 ms·

1.
by mskkm 29d ago
Feels like the more interesting trend is that Git itself is becoming an implementation detail.
2.
by mskkm 29d ago
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: https
3.
by mskkm 5mo ago
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 several of TurboQuant’s r
4.
by mskkm 5mo ago
went through ICLR review: scores 4 4 6 10, serious? open-source implementations: where is the official code? CUDA kernels: where?
5.
by mskkm 6mo ago
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 authors bef
6.
by mskkm 6mo ago
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 practice, I would have
7.
by mskkm 6mo ago
They confirmed on the accuracy on NIAH but didn't reproduce the claimed 8x efficiency.
8.
by mskkm 6mo ago
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 wall-clock time. The baseline
9.
by mskkm 1y ago
true