Safety-Oriented Routing Analysis of Mixtral MoE Under Benign and Harmful Prompts
The paper analyzes the routing behavior of the Mixtral 8x7B-Instruct model under different prompt conditions. It finds that expert usage is broad and long-tailed, with some experts showing preference for benign or harmful prompts. The study highlights the subtle and distributed nature of safety-relevant routing in the model.
- ▪The study focuses on the routing behavior of sparse mixture-of-experts language models.
- ▪Activation-based expert usage is broad and long-tailed, while gradient-based importance is concentrated.
- ▪Most experts are shared across benign and harmful prompts, with some showing clear group preference.
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| Original publisher | arXiv cs.AI |
| Canonical URL | https://arxiv.org/abs/2605.24270 |
| Publication time | Tue, 26 May 2026 00:00:00 -0400 |
| Retrieval time | 2026-05-26T04:07:43.013Z |
| Last seen | 2026-05-26T04:07:43.013Z |
| Headline source | Publisher (no WeSearch rewrite) |
| Excerpt source | publisher body |
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| Summary | WeSearch · cerebras-chat (WeSearch summarizer) |
| Summary source text | contentText |
| Citation coverage | Summary is a WeSearch-generated derivative; primary citation is the original publisher URL. |
| Cluster | -cr3caSux88q |
| Cluster logic | Grouped by semantic title/content similarity across sources within a rolling window. Same-publisher template collisions are excluded from coverage comparison. |
| Ranking reason | Story pages are not engagement-ranked. Hub feeds use recency, with optional source-diversified chronological ordering (cap consecutive stories per source). No personalized ranking. |
| Publisher visit | Yes — open original |
| Substitutes article? | No — link-out required for full text |
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| Indexing | May the item be indexed (stored, ranked, made findable)? | Allowed |
| Snippet | May a short excerpt of the publisher's text be shown? | Allowed |
| AI summary | May WeSearch generate its own short summary of the article? | Limited |
| Retrieval / RAG | May the content be exposed for third-party retrieval-augmented generation? | Not asserted |
| Model training | May the content be used to train AI models? | Not asserted |
| Commercial reuse | May the content be reused commercially? | Not permitted |
Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.
Opening excerpt (first ~120 words) tap to expand
Computer Science > Artificial Intelligence arXiv:2605.24270 (cs) [Submitted on 22 May 2026] Title:Safety-Oriented Routing Analysis of Mixtral MoE Under Benign and Harmful Prompts Authors:Md Nurul Absar Siddiky View a PDF of the paper titled Safety-Oriented Routing Analysis of Mixtral MoE Under Benign and Harmful Prompts, by Md Nurul Absar Siddiky View PDF HTML (experimental) Abstract:Sparse mixture-of-experts (MoE) language models activate only a small subset of parameters for each token, making router behavior a central part of model computation.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at arXiv cs.AI.
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