{
  "id": 4544341,
  "title": "Optimal Adversarial Testing: Extracting Honest Test Results from Dishonest Test Takers",
  "url": "https://urgent.news/2026/08/28/optimal-adversarial-testing-extracting-honest-test-results-from",
  "topic": "ai",
  "section": "AI",
  "published": "2026-08-28T14:13:40.000Z",
  "source": {
    "name": "arXiv cs.AI",
    "slug": "arxiv-cs-ai",
    "url": "https://arxiv.org/abs/2608.28362v1"
  },
  "original_language": "en",
  "account": null,
  "summary": "In applications, it is often required to test objects or people to determine their qualities in terms of certain metrics. However, besides being naturally noisy, the test results can be corrupted by adversarial behaviors of objects or people being tested (test takers). For example, dishonest test takers can cheat in the exams to distort the test results. With the development of AI technologies,…",
  "key_points": [],
  "editors_take": null,
  "illustration": null,
  "coverage": {
    "outlets": 1,
    "also_reported_by": []
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}