# Find Related Papers (/api-reference/endpoint/research-related-papers)

<!-- agent-signals: reading_time_min: 3 · est_tokens: 1765 · updated: 2026-07-30 -->
Related: [Search](/api-reference/endpoint/search.md), [Search Feedback](/api-reference/endpoint/search-feedback.md), [Scrape](/api-reference/endpoint/scrape.md), [Batch Scrape](/api-reference/endpoint/batch-scrape.md), [Get Batch Scrape Status](/api-reference/endpoint/batch-scrape-get.md), [Cancel Batch Scrape](/api-reference/endpoint/batch-scrape-delete.md)

Expand from a seed paper through structural expansion and rank candidate papers against a natural-language `intent`. Use `mode` to choose similar papers, citers, or references.

For a workflow overview, see the [Research Index guide](/features/research).

`GET /search/research/papers/{id}/similar`

Find related papers

## OpenAPI

```json
{
  "security": [
    {
      "bearerAuth": []
    }
  ],
  "parameters": [
    {
      "name": "id",
      "in": "path",
      "required": true,
      "description": "Primary seed paper reference.",
      "schema": {
        "type": "string"
      },
      "examples": {
        "paperId": {
          "summary": "Canonical paperId",
          "value": "2014215642691656232"
        },
        "sourceId": {
          "summary": "Source-specific primaryId",
          "value": "arxiv:2105.05233"
        }
      }
    },
    {
      "name": "intent",
      "in": "query",
      "required": true,
      "description": "Natural-language ranking/filtering intent used for semantic ranking.",
      "schema": {
        "type": "string",
        "minLength": 1
      }
    },
    {
      "name": "mode",
      "in": "query",
      "required": false,
      "description": "Structural expansion mode.",
      "schema": {
        "type": "string",
        "enum": [
          "similar",
          "citers",
          "references"
        ],
        "default": "similar"
      }
    },
    {
      "name": "k",
      "in": "query",
      "required": false,
      "description": "Maximum number of related papers to return.",
      "schema": {
        "type": "integer",
        "minimum": 1,
        "maximum": 500,
        "default": 40
      }
    },
    {
      "name": "rerank",
      "in": "query",
      "required": false,
      "description": "Apply an additional rerank over fused candidates.",
      "schema": {
        "type": "boolean"
      }
    },
    {
      "name": "anchor",
      "in": "query",
      "required": false,
      "description": "Additional seed paper reference. Repeat this parameter for multiple anchors.",
      "schema": {
        "type": "string"
      }
    }
  ],
  "responses": {
    "200": {
      "description": "Ranked related papers.",
      "content": {
        "application/json": {
          "schema": {
            "type": "object",
            "required": [
              "success",
              "results",
              "poolSize",
              "truncated"
            ],
            "properties": {
              "success": {
                "type": "boolean"
              },
              "results": {
                "type": "array",
                "items": {
                  "type": "object",
                  "required": [
                    "paperId",
                    "primaryId",
                    "title",
                    "abstract",
                    "score"
                  ],
                  "properties": {
                    "paperId": {
                      "type": "string",
                      "description": "Canonical paper id, or web:<url> for SERP-discovered display results."
                    },
                    "primaryId": {
                      "type": "string",
                      "description": "Preferred cite/fetch id such as arxiv:<id>, pmid:<id>, pmcid:<id>, or doi:<id>."
                    },
                    "ids": {
                      "type": "object",
                      "description": "Source identifiers grouped by namespace.",
                      "additionalProperties": {
                        "type": "array",
                        "items": {
                          "type": "string"
                        }
                      },
                      "example": {
                        "arxiv": [
                          "2105.05233"
                        ]
                      }
                    },
                    "title": {
                      "type": "string"
                    },
                    "abstract": {
                      "type": "string"
                    },
                    "score": {
                      "type": "number",
                      "format": "double"
                    },
                    "signals": {
                      "type": "object",
                      "required": [
                        "structural",
                        "semantic",
                        "articleRank",
                        "seedOverlap"
                      ],
                      "properties": {
                        "structural": {
                          "type": "number",
                          "format": "double",
                          "description": "Raw structural graph signal."
                        },
                        "semantic": {
                          "type": "number",
                          "format": "double",
                          "description": "Semantic score from the intent search."
                        },
                        "articleRank": {
                          "type": "number",
                          "format": "double",
                          "description": "Structural expansion article-rank score."
                        },
                        "seedOverlap": {
                          "type": "integer",
                          "minimum": 0,
                          "description": "Number of distinct seeds connected to this candidate."
                        }
                      }
                    }
                  }
                }
              },
              "poolSize": {
                "type": "integer",
                "minimum": 0
              },
              "truncated": {
                "type": "boolean"
              },
              "note": {
                "type": "string",
                "nullable": true
              }
            }
          },
          "example": {
            "success": true,
            "results": [
              {
                "paperId": "482107036680302043",
                "primaryId": "arxiv:2006.11239",
                "ids": {
                  "arxiv": [
                    "2006.11239"
                  ]
                },
                "title": "Denoising Diffusion Probabilistic Models",
                "abstract": "We present high quality image synthesis results using diffusion probabilistic models...",
                "score": 0.032119,
                "signals": {
                  "structural": 12,
                  "semantic": 0.61,
                  "articleRank": 0.00031,
                  "seedOverlap": 2
                }
              }
            ],
            "poolSize": 40,
            "truncated": false
          }
        }
      }
    },
    "400": {
      "description": "Invalid request"
    },
    "401": {
      "description": "Missing or invalid bearer token"
    },
    "429": {
      "description": "Rate limit exceeded"
    },
    "500": {
      "description": "Internal server error"
    }
  }
}
```