Detecting a Route Flip Is Easier Than Knowing Whether to Fix It: Causal Route-Mediated Damage in Quantized Mixture-of-Experts

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[Submitted on 14 Jul 2026]

Title:Detecting a Route Flip Is Easier Than Knowing Whether to Fix It: Causal Route-Mediated Damage in Quantized Mixture-of-Experts

View a PDF of the paper titled Detecting a Route Flip Is Easier Than Knowing Whether to Fix It: Causal Route-Mediated Damage in Quantized Mixture-of-Experts, by Parvel Gu

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Abstract:Top-k Mixture-of-Experts (MoE) routing is discontinuous, so a deployment-motivated numerical disturbance -- simulated 4-bit KV-cache quantization read by a protected BF16 gate -- pushes tokens across decision boundaries and flips which experts fire. This paper proposes no new mitigation; it supplies a causal apparatus, empirical findings, and a detection-limit result. A four-run apparatus prices the route-mediated fraction (RMF) of quantization damage, a token-level attribution decomposes it by mechanism, and pre-registered probes carry the findings across three architectures. On OLMoE-1B-7B at 4-bit KV (pilot), about a third of the damage is routing-mediated: RMF ~ 0.31 (discovery 0.31 [0.20, 0.41]; process-replicated mean 0.313 +/- 0.020; pre-registered re-execution 0.231). The deployable router margin detects that a flip occurred (AUC 0.772) but cannot tell a harmful flip from a helpful one (at chance): among the tested local, inference-observable router statistics we find no predictor of a flip's loss sign above chance -- an empirical benefit-detection barrier bounding selective repair restricted to this feature family. The signed-flip tax and sign-inseparability carry cross-model; the clean-reference remedy's payout is architecture-modulated; a controlled same-checkpoint flag-swap re-scopes the gate's normalization convention to a damage-magnitude moderator, not a route-recoverability mechanism. A real int4 KV kernel yields a fraction compatible with the fake-quant dose curve but underpowered (95% CI [-0.111, 0.394] includes zero) -- ruling out gross disagreement, not an independent replication. Hypotheses, thresholds, and evaluations were pre-registered before measurement, with misses reported; a pre-registered held-out read replicates the partition and the near-cancelling tax out of sample, while the strict impossibility exclusion narrowly misses.

Comments: 13 pages, 2 figures, 8 tables. Pre-registered pilot study

Subjects:

Artificial Intelligence (cs.AI); Computation and Language (cs.CL); Machine Learning (cs.LG)

MSC classes: 68T07

ACM classes: I.2.6; I.2.7

Cite as: arXiv:2608.11212 [cs.AI]

(or arXiv:2608.11212v1 [cs.AI] for this version)

https://doi.org/10.48550/arXiv.2608.11212

arXiv-issued DOI via DataCite

Submission history

From: Parvel Gu [view email] [v1] Tue, 14 Jul 2026 01:12:04 UTC (373 KB)

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HASH_MANIFEST.txt

PREREG_REGISTRY.md

VERIFICATION.md

prereg_keys/P1_jump_removable.txt

prereg_keys/P2_kl_alignment_wa_not_kv.txt

prereg_keys/P3_vanishing_boundary_rmf0.txt

prereg_keys/P4_twin_gate.txt

prereg_keys/P5_window_cusum_bound.txt

prereg_keys/P8_crossover_generality.txt

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