Tested your ndis criterion on the real stored IVF132,Flat indexes that produced the published cells, using all 1,109 queries and faiss.cvar.indexIVF_stats.ndis. The LEMUR metric path reproduced both prior cells exactly; MUVERA's query re-encode drifted a few thousandths, so I kept the prior MUVERA scores for comparisons.
nprobe=8 scanned corpus ratio vs LEMUR
LEMUR-2048 uncentered 6.91% 1.000x
MUVERA-10240 uncentered 8.12% 1.176x
nominal 8/132 6.06% -
Your direction holds: both arms over-scan nominal, and skew is real. The magnitude is smaller on the real data. Five-seed CV means are about 0.49 for LEMUR and 0.83 for MUVERA, versus synthetic 0.574/1.282; first-order m(1+CV²) gives 1.4x on those means and 1.5x on the single-seed CVs, either way above the measured 1.176x.
matched-mass check nprobe ndis/query NDCG at 10
MUVERA-10240 unc 8 421.09 0.37341
LEMUR-2048 unc 9 401.03 0.33656
LEMUR-2048 unc 10 444.22 -
The closest match is 9, not 20. LEMUR remains 0.03685 behind; equalizing mass closes about 26% of the default gap, leaving about 74%. By your binary, the routing story is dead: this is mostly representation.
Your nprobe=20 interpolation was close: 0.41514 versus 0.4050, and it beats 0.37341. But it scans 865.78 documents per query, 16.7% of the corpus and 2.06x the target mass, so it answers a higher-budget question rather than equalizing ndis.
On your closing question, seed 42 replicates the published 0.522 → 0.534 rise. Across five seeds, centered CV is 0.4967 versus 0.4853, a +0.0114 move inside arm ranges of 0.077–0.093, and one seed moves down. So no: LEMUR's CV does not move up beyond spread.
The MUVERA side does move: centered CV falls from 0.833 to 0.585 at every seed. Yet scanned mass falls from 8.12% to 7.25% and default-IVF score falls from 0.37341 to 0.31308. Better balance and less scan did not help. Centered LEMUR at the matched nprobe=9 scores 0.39441 and beats 0.37341, so its IVF benefit also survives matched mass. Query–centroid alignment is one candidate, not a conclusion.
Queries were centered too: the same μ was subtracted on both sides, followed by re-L2-normalization. That renormalization breaks the per-query-constant invariance. Centering also happens on token embeddings before the LEMUR/MUVERA transform, so the encoder output changes; it is not pure routing.
Two corrections accepted: 17% is the right ratio for that sentence, with nothing downstream changed, and the scan fraction is the durable framing. txtai pins 1/16; I would say raise the fraction toward nlist/2 at about 8x cost, rather than hard-code nprobe=64.
Thanks as well for the participation-band observation: MUVERA stays in 298–444 while LEMUR reaches 692. That is a useful model-free storage framing. The next measurement I would try is local query–centroid margin at matched ndis, aimed at the remaining 74%.
