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 "name": "Large language models",
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  "name": "Wulf A. Kaal",
  "identifier": "https://orcid.org/0000-0003-0757-275X"
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   "@id": "https://wulfkaal.github.io/claims/5541658-032",
   "identifier": "kaal:claim:5541658-032",
   "text": "Benchmark results for legal LLMs may overstate capability because of data contamination: if a model saw a benchmark's ground truth answers during training, its measured performance reflects memorization rather than genuine generalization.",
   "abstract": "If a model has already seen a benchmark's ground-truth answers during training, its performance may reflect memorization rather than genuine generalization, making it hard to assess its ability on truly unseen tasks.",
   "citation": "Wulf A. Kaal, Morgan A. Gray, The Evolving Role of Artificial Intelligence in Law (2025). SSRN: https://ssrn.com/abstract=5541658",
   "datePublished": "2025",
   "claim_type": "failure",
   "confidence": "evidenced",
   "is_failure_mode": true,
   "scope_conditions": [
    "closed source LLMs evaluated on public benchmarks"
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   "status": "current"
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   "@type": "Claim",
   "@id": "https://wulfkaal.github.io/claims/5541658-034",
   "identifier": "kaal:claim:5541658-034",
   "text": "Even as LLMs for judicial reasoning become more sophisticated, their inability to replicate empathy and social responsiveness will confine them to supportive rather than decisional functions.",
   "abstract": "However, AI's inability to replicate empathy and social responsiveness will limit its role to supportive functions.",
   "citation": "Wulf A. Kaal, Morgan A. Gray, The Evolving Role of Artificial Intelligence in Law (2025). SSRN: https://ssrn.com/abstract=5541658",
   "datePublished": "2025",
   "claim_type": "predictive",
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