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SRCH:7CDDAEDD

What is the robustness of quantized SLMs (1B-10B parameters) across SLM-Bench domains when evaluated under fed

Submitted: 10 June 2026
Review score: 3.33/10
Verification: L1, Literature synthesis
Gate status: Unverified
Quality tier: Quarantine candidate

Abstract

Abstract: Small Language Models (SLMs) offer computational efficiency and accessibility, yet a systematic evaluation of their performance and environmental impact remains lacking. We introduce SLM-Bench, the first benchmark specifically designed to assess SLMs across multiple dimensions, including accuracy, computational efficiency, and sustainability metrics. SLM-Bench evaluates 15 SLMs on 9 NLP tasks using 23 datasets spanning 14 domains. The evaluation is conducted on 4 hardware configurations, providing a rigorous comparison of their effectiveness. Unlike prior benchmarks, SLM-Bench quantifies 11 me

Research Question

What is the robustness of quantized SLMs (1B-10B parameters) across SLM-Bench domains when evaluated under federated learning setups with edge Kubernetes distributions?

Verification Level

Paper levelL1, Literature synthesis
Source-grounded claims0
Claim record sourcenot publicly specified

Descriptive public verification status only; aggregate claim counts are public, but individual claim records are not exposed here.

Truth-Engine Gate Verdict

StatusUnverified
GateGate 2 — Verification (formal proof or sandbox reproduction)
ReasonPublished before the Gate 2 verification pipeline was activated (2026-06-10). No formal proof or sandbox reproduction has been attempted for this record.
Evaluated2026-06-10T06:30:49+00:00

This record has not completed Gate 2 of the verification pipeline (a type-checked Lean4 proof for mathematical claims, or a sealed-sandbox reproduction for empirical claims). It is a literature synthesis only. VERIFIED requires an attached reproducible artifact (Lean4 proof source, or repro script and results) before this status can be set; it is not derived from review score or claim count.

Quality Tier

TierQuarantine candidate
BasisReview score is below 5.0; source-level inspection is required before relying on the synthesis.

Descriptive public triage only; this tier does not alter current publication or DOI behavior.

Quality Dimensions

Evidence strength LOW
Uncertainty disclosure MEDIUM
Reproducibility status MEDIUM

Automated triage signals derived from public fields; not human peer review or independent validation.

Correction Record

StatusCURRENT
Correction count0
Manifest contractpaper-manifest-v1.1
Correction contractcorrection-record-v1

Public corrections are additive records. Current status does not claim the synthesis is error-free.

Provenance

PublisherAssignee Research
Public provenanceL2, Public artifact record
Report artifactAvailable
External recordNot registered
Claim lineage0 aggregate source-grounded claims
Review methodAutomated multi-reviewer assessment
Quality guideHow to read scores, claims, manifests, and evidence links
Provenance contractsource-provenance-v1
NoteMachine-generated synthesis of existing literature. Not primary research.