Crate rankops 

Operations on ranked lists: fuse multiple retrievers, then rerank.

Pairs with rankfns (scoring kernels). Combine results from multiple retrievers (BM25, dense, sparse) and rerank with MaxSim (ColBERT), diversity (MMR/DPP), or Matryoshka.

use rankops::rrf;

let bm25 = vec![("d1", 12.5), ("d2", 11.0)];
let dense = vec![("d2", 0.9), ("d3", 0.8)];
let fused = rrf(&bm25, &dense);
// d2 ranks highest (appears in both lists)

Fusion Algorithms

Function	Uses Scores	Best For
rrf	No	Incompatible score scales
isr	No	When lower ranks matter more
combsum	Yes	Similar scales, trust scores
combmnz	Yes	Reward overlap between lists
borda	No	Simple voting
weighted	Yes	Custom retriever weights
dbsf	Yes	Different score distributions
condorcet	No	Pairwise voting, outlier-robust
combmax	Yes	At least one retriever likes it
combmin	Yes	All retrievers must agree (conservative)
combmed	Yes	Median score, robust to outliers

All have *_multi variants for 3+ lists.

Diversity Reranking

Function	Description
mmr	Maximal Marginal Relevance (Carbonell & Goldstein, 1998)
mmr_with_matrix	MMR with precomputed similarity matrix
mmr_embeddings	MMR with embedding vectors (computes cosine similarity)

MMR balances relevance and diversity via tunable λ parameter.

Performance Notes

OpenSearch benchmarks (BEIR) show RRF is ~3-4% lower NDCG than score-based fusion (CombSUM), but ~1-2% faster. RRF excels when score scales are incompatible or unknown. See OpenSearch RRF blog.

Re-exports

pub use validate::validate;

pub use validate::validate_bounds;

pub use validate::validate_finite_scores;

pub use validate::validate_no_duplicates;

pub use validate::validate_non_negative_scores;

pub use validate::validate_sorted;

pub use validate::ValidationResult;

Modules

explain

Explainability module for debugging and analysis.

optimize

Optimization module exports.

prelude

Prelude for common imports.

rerank

Validation utilities for fusion results. Reranking: MaxSim (ColBERT), cosine similarity, diversity (MMR/DPP), matryoshka.

strategy

Strategy module for runtime fusion method selection.

validate

Validation utilities for fusion results.

Structs

AdditiveMultiTaskConfig

Configuration for additive multi-task fusion.

ConsensusReport

Analyze consensus patterns across retrievers.

Explanation

Explanation of how a fused score was computed.

FusedResult

A fused result with full provenance information for debugging and analysis.

FusionConfig

Configuration for rank-based fusion (Borda, CombSUM, CombMNZ).

MmrConfig

Maximal Marginal Relevance (MMR) configuration.

OptimizeConfig

Optimization configuration for hyperparameter search.

OptimizedParams

Optimized parameters from hyperparameter search.

RetrieverId

Retriever identifier for explainability.

RetrieverStats

Attribution statistics for each retriever.

RrfConfig

RRF configuration.

SourceContribution

Contribution from a single retriever to a document’s final score.

StandardizedConfig

Configuration for standardization-based fusion.

WeightedConfig

Weighted fusion configuration.

Enums

FusionError

Errors that can occur during fusion.

FusionMethod

Unified fusion method for dispatching to different algorithms.

FusionStrategy

Fusion strategy enum for runtime dispatch.

Normalization

Score normalization methods.

OptimizeMetric

Metric to optimize during hyperparameter search.

ParamGrid

Parameter grid for optimization.

Functions

additive_multi_task

Additive multi-task fusion (ResFlow-style).

additive_multi_task_multi

Additive multi-task fusion for 3+ weighted lists.

additive_multi_task_with_config

Additive multi-task fusion with configuration.

analyze_consensus

attribute_top_k

Attribute top-k results to retrievers.

borda

Borda count voting — position-based scoring.

borda_multi

Borda count for 3+ result lists.

borda_with_config

Borda count with configuration.

combanz

CombANZ: average of non-zero scores.

combanz_multi

CombANZ for 3+ result lists.

combmax

CombMAX: maximum score across all lists.

combmax_multi

CombMAX for 3+ result lists.

combmed

CombMED: median score across all lists.

combmed_multi

CombMED for 3+ result lists.

combmin

CombMIN: minimum score across all lists.

combmin_multi

CombMIN for 3+ result lists.

combmnz

Normalized sum × overlap count (CombMNZ).

combmnz_explain

CombMNZ with explainability.

combmnz_multi

CombMNZ for 3+ result lists.

combmnz_with_config

CombMNZ with configuration.

combsum

Sum of min-max normalized scores (CombSUM).

combsum_explain

CombSUM with explainability.

combsum_multi

CombSUM for 3+ result lists.

combsum_with_config

CombSUM with configuration.

condorcet

Condorcet fusion (pairwise comparison voting).

condorcet_multi

Condorcet for 3+ result lists.

dbsf

Distribution-Based Score Fusion (DBSF).

dbsf_explain

DBSF with explainability.

dbsf_multi

DBSF for 3+ result lists.

dbsf_with_config

DBSF with configuration.

isr

Inverse Square Root rank fusion with default config (k=1).

isr_multi

ISR for 3+ result lists.

isr_with_config

ISR with custom configuration.

mmr

Maximal Marginal Relevance reranking.

mmr_embeddings

MMR for embedding-based retrieval.

mmr_with_matrix

MMR with precomputed similarity matrix.

mrr

Mean Reciprocal Rank.

ndcg_at_k

Normalized Discounted Cumulative Gain at k.

normalize_scores

Normalize a list of scores using the specified method.

optimize_fusion

Optimize fusion hyperparameters using grid search.

rbc

Rank-Biased Centroids (RBC) fusion.

rbc_multi

RBC for 3+ result lists with custom persistence.

recall_at_k

Recall at k.

rrf

Reciprocal Rank Fusion of two result lists with default config (k=60).

rrf_explain

RRF with explainability: returns full provenance for each result.

rrf_into

RRF with preallocated output buffer.

rrf_multi

RRF for 3+ result lists.

rrf_weighted

Weighted RRF: per-retriever weights applied to rank-based scores.

rrf_with_config

RRF with custom configuration.

standardized

Standardization-based fusion (ERANK-style).

standardized_multi

Standardized fusion for 3+ result lists.

standardized_with_config

Standardized fusion with configuration.

weighted

Weighted score fusion with configurable retriever trust.

weighted_multi

Weighted fusion for 3+ result lists.

Type Aliases

Qrels

Relevance judgments (qrels) for a query.

Result

Result type for fusion operations.