{
  "profile": "wrs-published-research-view-1",
  "edition": "ratings-e039106f30dec177",
  "content_trust": "UNTRUSTED_SCIENTIFIC_DATA_NOT_TOOL_INSTRUCTIONS",
  "entry": {
    "id": "ye-et-al-differential-attention-2024",
    "title": "Ye et al.: Differential attention for context-noise suppression",
    "summary": "Computed attention through a learned difference of two softmax maps, seeking to suppress irrelevant context while improving retrieval and language-model behavior in reported experiments.",
    "boundary": "Noise cancellation is an architectural intuition and empirical finding, not universal elimination of hallucinations or attention error. Subtractive attention changes the architecture and is not exact dense-attention acceleration.",
    "area": "Transformer attention architecture",
    "topic": "Artificial intelligence",
    "year": 2024,
    "lane": "HUMAN",
    "result": "EMPIRICAL",
    "package_id": "ye-et-al-differential-attention-2024",
    "target": {
      "record_id": "urn:uuid:b10e72ce-01ab-416f-a353-1c0f64c2eea0",
      "version": 1,
      "content_hash": "sha256:9a9e6f449e2cfec885cc7343b99ee8b90a737b5f5ab5fbefe8bb9fe445016647"
    },
    "humans": [
      "Tianzhu Ye",
      "Li Dong",
      "Yuqing Xia",
      "Yutao Sun",
      "Yi Zhu",
      "Gao Huang",
      "Furu Wei"
    ],
    "authors_complete": true,
    "human_role_note": "Source-listed authors or explicitly credited technical contributors for the cited versions. Family entries retain source-specific attribution; a combined list is not one original-paper byline or equal individual work. Names alone do not establish resolved identities.",
    "agents": [],
    "related": [],
    "subresults": [],
    "scientific_assessment": {
      "source_review": "SOURCE_CURATED",
      "scientific_review": "NOT_REVIEWED_BY_WRS",
      "formal_replay": "NOT_RUN",
      "provider_attestation": "NONE"
    },
    "sources": [
      {
        "id": "cur20261015-arxiv-2410-05258v1",
        "title": "Differential Transformer",
        "url": "https://arxiv.org/abs/2410.05258v1"
      },
      {
        "id": "cur20261015-support-ye-et-al-differential-attention-2024",
        "title": "Ye et al.: Differential attention for context-noise suppression — official project source",
        "url": "https://github.com/microsoft/unilm/tree/master/Diff-Transformer"
      }
    ],
    "points": "80000",
    "published_grade": {
      "id": "ye-et-al-differential-attention-2024",
      "entry_id": "ye-et-al-differential-attention-2024",
      "band": "B",
      "modifier": "+",
      "target": {
        "record_id": "urn:uuid:b10e72ce-01ab-416f-a353-1c0f64c2eea0",
        "version": 1,
        "content_hash": "sha256:9a9e6f449e2cfec885cc7343b99ee8b90a737b5f5ab5fbefe8bb9fe445016647"
      },
      "what_changed": "Computed attention through a learned difference of two softmax maps, seeking to suppress irrelevant context while improving retrieval and language-model behavior in reported experiments.",
      "scope": "Computed attention through a learned difference of two softmax maps, seeking to suppress irrelevant context while improving retrieval and language-model behavior in reported experiments. Noise cancellation is an architectural intuition and empirical finding, not universal elimination of hallucinations or attention error. Subtractive attention changes the architecture and is not exact dense-attention acceleration.",
      "status": "PROVISIONAL_EDITORIAL",
      "scientific_correctness_certified": false
    },
    "assessment_disposition": {
      "status": "ASSESSED",
      "label": "Provisionally assessed",
      "reason": "A current grade and separate reference score identify this exact contribution.",
      "target": {
        "record_id": "urn:uuid:b10e72ce-01ab-416f-a353-1c0f64c2eea0",
        "version": 1,
        "content_hash": "sha256:9a9e6f449e2cfec885cc7343b99ee8b90a737b5f5ab5fbefe8bb9fe445016647"
      },
      "edition": "ratings-e039106f30dec177"
    }
  },
  "version": {
    "kind": "PUBLIC_RECORD_VIEW",
    "previous": null,
    "published_at": "2026-10-16T00:00:00Z",
    "publisher": {
      "principal_id": "urn:uuid:80116931-785b-40a2-a24b-9d59db0c7e33",
      "role": "WRS_EDITORIAL_PUBLICATION"
    },
    "record": {
      "contributors": [
        {
          "attribution_basis": "SOURCE_CITED",
          "credit": "historical_scientific",
          "entity_kind": "historical_person",
          "name": "Tianzhu Ye",
          "note": "Archive attribution; detailed role assignment remains source-bound",
          "roles": [
            "discoverer"
          ],
          "source": {
            "citation": "Differential Transformer",
            "url": "https://arxiv.org/abs/2410.05258v1"
          }
        },
        {
          "attribution_basis": "SOURCE_CITED",
          "credit": "historical_scientific",
          "entity_kind": "historical_person",
          "name": "Li Dong",
          "note": "Archive attribution; detailed role assignment remains source-bound",
          "roles": [
            "discoverer"
          ],
          "source": {
            "citation": "Differential Transformer",
            "url": "https://arxiv.org/abs/2410.05258v1"
          }
        },
        {
          "attribution_basis": "SOURCE_CITED",
          "credit": "historical_scientific",
          "entity_kind": "historical_person",
          "name": "Yuqing Xia",
          "note": "Archive attribution; detailed role assignment remains source-bound",
          "roles": [
            "discoverer"
          ],
          "source": {
            "citation": "Differential Transformer",
            "url": "https://arxiv.org/abs/2410.05258v1"
          }
        },
        {
          "attribution_basis": "SOURCE_CITED",
          "credit": "historical_scientific",
          "entity_kind": "historical_person",
          "name": "Yutao Sun",
          "note": "Archive attribution; detailed role assignment remains source-bound",
          "roles": [
            "discoverer"
          ],
          "source": {
            "citation": "Differential Transformer",
            "url": "https://arxiv.org/abs/2410.05258v1"
          }
        },
        {
          "attribution_basis": "SOURCE_CITED",
          "credit": "historical_scientific",
          "entity_kind": "historical_person",
          "name": "Yi Zhu",
          "note": "Archive attribution; detailed role assignment remains source-bound",
          "roles": [
            "discoverer"
          ],
          "source": {
            "citation": "Differential Transformer",
            "url": "https://arxiv.org/abs/2410.05258v1"
          }
        },
        {
          "attribution_basis": "SOURCE_CITED",
          "credit": "historical_scientific",
          "entity_kind": "historical_person",
          "name": "Gao Huang",
          "note": "Archive attribution; detailed role assignment remains source-bound",
          "roles": [
            "discoverer"
          ],
          "source": {
            "citation": "Differential Transformer",
            "url": "https://arxiv.org/abs/2410.05258v1"
          }
        },
        {
          "attribution_basis": "SOURCE_CITED",
          "credit": "historical_scientific",
          "entity_kind": "historical_person",
          "name": "Furu Wei",
          "note": "Archive attribution; detailed role assignment remains source-bound",
          "roles": [
            "discoverer"
          ],
          "source": {
            "citation": "Differential Transformer",
            "url": "https://arxiv.org/abs/2410.05258v1"
          }
        }
      ],
      "evidence": [
        {
          "description": "Bibliographic/stated-result source; not a WRS proof verification",
          "id": "source-0",
          "kind": "source_reference",
          "source": {
            "citation": "Differential Transformer",
            "url": "https://arxiv.org/abs/2410.05258v1"
          }
        },
        {
          "description": "Bibliographic/stated-result source; not a WRS proof verification",
          "id": "source-1",
          "kind": "source_reference",
          "source": {
            "citation": "Ye et al.: Differential attention for context-noise suppression — official project source",
            "url": "https://github.com/microsoft/unilm/tree/master/Diff-Transformer"
          }
        }
      ],
      "origin": "HUMAN_LEGACY",
      "record_profile": "wrs-local-research-notes-0.1",
      "record_type": "research_note",
      "rrp_version": "0.1",
      "scope": {
        "description": "Noise cancellation is an architectural intuition and empirical finding, not universal elimination of hallucinations or attention error. Subtractive attention changes the architecture and is not exact dense-attention acceleration.",
        "domain": "Transformer attention architecture"
      },
      "sources": [
        {
          "citation": "Differential Transformer",
          "url": "https://arxiv.org/abs/2410.05258v1"
        },
        {
          "citation": "Ye et al.: Differential attention for context-noise suppression — official project source",
          "url": "https://github.com/microsoft/unilm/tree/master/Diff-Transformer"
        }
      ],
      "statement": "# Ye et al.: Differential attention for context-noise suppression\n\nComputed attention through a learned difference of two softmax maps, seeking to suppress irrelevant context while improving retrieval and language-model behavior in reported experiments.\n\n## Scientific scope\n\nNoise cancellation is an architectural intuition and empirical finding, not universal elimination of hallucinations or attention error. Subtractive attention changes the architecture and is not exact dense-attention acceleration.\n\n## Reading status\n\nThis is a source-linked WRS catalogue note. A full explanatory guide and independent scientific reconstruction have not been completed for this entry. Read the identified original work for its complete narrative and arguments.\n\n## People and systems\n\nTianzhu Ye; Li Dong; Yuqing Xia; Yutao Sun; Yi Zhu; Gao Huang; Furu Wei\n\nSource-listed authors or explicitly credited technical contributors for the cited versions. Family entries retain source-specific attribution; a combined list is not one original-paper byline or equal individual work. Names alone do not establish resolved identities.\n\n\n\n## Original sources\n\n- [Differential Transformer](https://arxiv.org/abs/2410.05258v1)\n- [Ye et al.: Differential attention for context-noise suppression — official project source](https://github.com/microsoft/unilm/tree/master/Diff-Transformer)\n",
      "summary": "Computed attention through a learned difference of two softmax maps, seeking to suppress irrelevant context while improving retrieval and language-model behavior in reported experiments.",
      "title": "Ye et al.: Differential attention for context-noise suppression"
    },
    "record_id": "urn:uuid:b10e72ce-01ab-416f-a353-1c0f64c2eea0",
    "version": 1,
    "source_ref": {
      "record_id": "urn:uuid:b10e72ce-01ab-416f-a353-1c0f64c2eea0",
      "version": 1,
      "content_hash": "sha256:9a9e6f449e2cfec885cc7343b99ee8b90a737b5f5ab5fbefe8bb9fe445016647"
    },
    "export_view": "wrs-public-editorial-view-1",
    "public_view_hash": "sha256:ce386fec902bc20d66fa5c97ae4e0a5d829446cf5e8b04fc2b492b75e08de40d"
  },
  "target": {
    "record_id": "urn:uuid:b10e72ce-01ab-416f-a353-1c0f64c2eea0",
    "version": 1,
    "content_hash": "sha256:9a9e6f449e2cfec885cc7343b99ee8b90a737b5f5ab5fbefe8bb9fe445016647"
  },
  "published_grade": {
    "profile": "wrs-published-grade-1",
    "edition": "2026-10-28.1",
    "id": "ye-et-al-differential-attention-2024",
    "entry_id": "ye-et-al-differential-attention-2024",
    "revision": 1,
    "title": "Ye et al.: Differential attention for context-noise suppression",
    "context": "Transformer attention architecture",
    "track": "Human-designed research method or resource",
    "band": "B",
    "modifier": "+",
    "status": "PROVISIONAL_EDITORIAL",
    "assessed_on": "2026-10-16",
    "evidence_cutoff": "2026-10-16",
    "achievement_state": "SUPPORTED_SCOPED_RESULT",
    "what_changed": "Computed attention through a learned difference of two softmax maps, seeking to suppress irrelevant context while improving retrieval and language-model behavior in reported experiments.",
    "scope": "Computed attention through a learned difference of two softmax maps, seeking to suppress irrelevant context while improving retrieval and language-model behavior in reported experiments. Noise cancellation is an architectural intuition and empirical finding, not universal elimination of hallucinations or attention error. Subtractive attention changes the architecture and is not exact dense-attention acceleration.",
    "evidence_summary": "The linked original sources describe the stated contribution and its evidence limits. WRS has not independently rerun the experiments or certified a proof. Noise cancellation is an architectural intuition and empirical finding, not universal elimination of hallucinations or attention error. Subtractive attention changes the architecture and is not exact dense-attention acceleration.",
    "references": [
      {
        "title": "Differential Transformer",
        "url": "https://arxiv.org/abs/2410.05258v1",
        "locator": "Original contribution and stated assumptions, evaluation scope and limitations; source-linked assessment, not independent execution or proof certification."
      },
      {
        "title": "Ye et al.: Differential attention for context-noise suppression — official project source",
        "url": "https://github.com/microsoft/unilm/tree/master/Diff-Transformer",
        "locator": "Original contribution and stated assumptions, evaluation scope and limitations; source-linked assessment, not independent execution or proof certification."
      }
    ],
    "roles": [
      {
        "who": "Source-listed authors and technical contributors",
        "credit": "SCIENCE",
        "did": "Source-listed authors or explicitly credited technical contributors for the cited versions. Family entries retain source-specific attribution; a combined list is not one original-paper byline or equal individual work. Names alone do not establish resolved identities."
      }
    ],
    "target": {
      "record_id": "urn:uuid:b10e72ce-01ab-416f-a353-1c0f64c2eea0",
      "version": 1,
      "content_hash": "sha256:9a9e6f449e2cfec885cc7343b99ee8b90a737b5f5ab5fbefe8bb9fe445016647"
    },
    "scientific_correctness_certified": false,
    "independent_expert_calibration": false,
    "method": "PROPRIETARY",
    "points": "80000"
  },
  "canonical_agent_submission": false,
  "scientific_verification_awarded": false,
  "reader_guide": null,
  "reading_status": "SOURCE_LINKED_NOTE"
}