Beyond Rational Illusion: Behaviorally Realistic Strategic Classification
The paper titled 'Beyond Rational Illusion: Behaviorally Realistic Strategic Classification' introduces a new framework for strategic classification that accounts for cognitive biases in decision-making. The authors propose the Prospect-Guided Strategic Framework (Pro-SF) to model agents' strategic manipulations that deviate from strict rationality. This approach aims to bridge the gap between machine learning and behavioral economics for more reliable applications in real-world scenarios.
- ▪The research identifies a limitation in existing strategic classification frameworks that assume agents are strictly rational.
- ▪The proposed Pro-SF framework incorporates mechanisms inspired by prospect theory to capture behaviorally realistic strategic responses.
- ▪Experiments demonstrate that Pro-SF effectively addresses the behaviorally realistic strategic classification problem.
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Record
| Original publisher | arXiv cs.AI |
| Canonical URL | https://arxiv.org/abs/2605.19674 |
| Publication time | Wed, 20 May 2026 00:00:00 -0400 |
| Retrieval time | 2026-05-20T04:04:59.484Z |
| Last seen | 2026-05-20T04:04:59.484Z |
| Headline source | Publisher (no WeSearch rewrite) |
| Excerpt source | publisher body |
| Excerpt method | First ~120 words (~800 chars) of extracted publisher body, fair-use limited. |
| 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 | xyJ5UDGmS3X0 |
| 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:2605.19674 (cs) [Submitted on 19 May 2026] Title:Beyond Rational Illusion: Behaviorally Realistic Strategic Classification Authors:Xinpeng Lv, Yunxin Mao, Renzhe Xu, Chunyuan Zheng, Yikai Chen, Haoxuan Li, Yang Shi, Jinxuan Yang, Zhouchen Lin, Yuanlong Chen, Yuanxing Zhang, Shaowu Yang, Wenjing Yang, Haotian Wang View a PDF of the paper titled Beyond Rational Illusion: Behaviorally Realistic Strategic Classification, by Xinpeng Lv and 13 other authors View PDF HTML (experimental) Abstract:Strategic classification(SC) studies the interaction between decision models and agents who strategically manipulate their features for favorable outcomes. Existing SC frameworks typically rely on the idealized assumption that agents are strictly rational.
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