ModelInclusionAI (Ant Group)InclusionAI (Ant Group)published Sep 14, 2026seen Sep 15

inclusionAI/gemma-4-31B-it-singprobe

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published Sep 14, 2026seen Sep 15captured Sep 15http 200method plainlicense apache-2.0params 11Mdownloads 114likes 1

gemma-4-31B-it-singprobe

Model Description

SingProbe is an intrinsic streaming guardrail built on google/gemma-4-31B-it. Rather than running a separate safety model, this lightweight probe reuses the base model's hidden states during generation to score, at every token, query intent, response unsafety, and hallucination risk. It adds less than 0.5% decode-time overhead.

| Base model | Probe parameters | Tapped layers | Outputs | | --- | ---: | --- | --- | | inclusionAI/gemma-4-31B-it-singprobe | 10.59M | [18, 38, 58] | 8 intents + unsafe + hallucination |

See the technical report for methodology and complete results. Training codes are available at inclusionAI/SingProbe.

Evaluation

Higher is better for every metric. Results are averages over the benchmark suites specified below.

| Task | Metric | gemma-4-31B-it-singprobe | Reference baseline | | --- | --- | ---: | ---: | | Query intent classification (6 benchmarks) | F1 | 0.8700 | YuFeng-XGuard-Reason-8B: 0.8714 | | Response safety classification (8 benchmarks) | F1 | 0.8655 | Qwen3Guard-Gen-8B-strict: 0.8604 | | Streaming safety (3 benchmarks) | R-AUC / T-AUC | 0.9830 / 0.9184 | Qwen3Guard-Stream-8B-strict: 0.9640 / 0.8893 | | Hallucination detection (6 benchmarks) | AUC | 0.8054 | DRIFT: 0.8000 |

| Deployment characteristic | Result | | --- | --- | | Benign-response false-positive rate | 0.03% average across 5 datasets | | Decode overhead | < 0.5% |

Quick Start

SingProbe is supported through the SGLang integration branch or vLLM integration branch. Load the probe by its Hugging Face ID at server launch:

python -m sglang.launch_server \
--model-path google/gemma-4-31B-it \
--probe-ckpt inclusionAI/gemma-4-31B-it-singprobe \
--port 30000

The integrations return one score dictionary per generated token (label_0–label_9). Use the exact base-model/probe pair: google/gemma-4-31B-it with this checkpoint.

Citation

@article{singteam2026singprobe,
title = {SingProbe Technical Report},
author = {Sing Team},
journal = {arXiv preprint arXiv:2608.30703},
year = {2026},
}

Notability

notability 5.0/10

Custom Gemma fine-tune, limited traction