{
  "schema_version": "1.0.0",
  "rubric_version": "1.0",
  "license": "CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/)",
  "record": {
    "id": "O-0122",
    "slug": "university-of-waterloo",
    "title": "University of Waterloo",
    "aliases": [],
    "status": "draft",
    "last_reviewed": "2026-09-23",
    "review_interval_days": 90,
    "steward": null,
    "provenance": {
      "drafted_by": "ai",
      "reviewed_by": []
    },
    "risk_flags": [],
    "flags": [],
    "kind": "academic-lab",
    "homepage": "https://uwaterloo.ca/",
    "one_liner": "A university in Waterloo, Ontario, Canada, whose researchers developed zkLLM, a zero-knowledge proof system for large language model inference.",
    "sources": [
      {
        "source": "S-0023",
        "supports": "zkLLM paper; all three authors at the University of Waterloo; view on proofs of training"
      },
      {
        "source": "S-1108",
        "supports": "zkLLM code and artifact"
      }
    ],
    "type": "organization",
    "url": "https://trustbutveri.fyi/organizations/university-of-waterloo/",
    "source_file": "content/organizations/university-of-waterloo.md",
    "flags_all": [
      "ai-drafted"
    ],
    "body_markdown": "The University of Waterloo is in Waterloo, Ontario, Canada; all three authors of zkLLM list it as their affiliation [[S-0023]]. Their work includes:\n\n- **zkLLM.** The CCS 2024 paper presents [[I-0003|zkLLM]], a zero-knowledge proof system for large language model inference [[S-0023]]; see [[M-0004]].\n- **Code.** The authors released the code as an artifact after the conference's artifact evaluation, archived on Zenodo [[S-1108]].\n- **Proofs of training.** The authors wrote that zero-knowledge proofs of LLM training \"may pose insurmountable challenges\" [[S-0023]]; see [[M-0005]].",
    "body_text": "The University of Waterloo is in Waterloo, Ontario, Canada; all three authors of zkLLM list it as their affiliation [S-0023]. Their work includes: - zkLLM. The CCS 2024 paper presents zkLLM, a zero-knowledge proof system for large language model inference [S-0023]; see Zero-knowledge proofs of inference. - Code. The authors released the code as an artifact after the conference's artifact evaluation, archived on Zenodo [S-1108]. - Proofs of training. The authors wrote that zero-knowledge proofs of LLM training \"may pose insurmountable challenges\" [S-0023]; see Zero-knowledge proofs of training constraints.",
    "referenced_by": [
      {
        "id": "M-0004",
        "title": "Zero-knowledge proofs of inference",
        "url": "https://trustbutveri.fyi/mechanisms/zk-proofs-of-inference/"
      },
      {
        "id": "I-0003",
        "title": "zkLLM",
        "url": "https://trustbutveri.fyi/implementations/zkllm/"
      },
      {
        "id": "S-1108",
        "title": "zkllm-ccs2024: code for zkLLM: Zero Knowledge Proofs for Large Language Models",
        "url": "https://trustbutveri.fyi/sources/sun-zkllm-code/"
      },
      {
        "id": "S-0023",
        "title": "zkLLM: Zero Knowledge Proofs for Large Language Models",
        "url": "https://trustbutveri.fyi/sources/sun-zkllm/"
      }
    ]
  }
}