REVIEW 17 cited by
Not yet reviewed by Pith; the record is open.
This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.
SPECIMEN: schema-true, not a live event
T0 review · schema-true
One-sentence machine reading of the paper's core claim.
pith:XXXXXXXX · record.json · timestamp
BM25S: Orders of magnitude faster lexical search via eager sparse scoring
read the original abstract
We introduce BM25S, an efficient Python-based implementation of BM25 that only depends on Numpy and Scipy. BM25S achieves up to a 500x speedup compared to the most popular Python-based framework by eagerly computing BM25 scores during indexing and storing them into sparse matrices. It also achieves considerable speedups compared to highly optimized Java-based implementations, which are used by popular commercial products. Finally, BM25S reproduces the exact implementation of five BM25 variants based on Kamphuis et al. (2020) by extending eager scoring to non-sparse variants using a novel score shifting method. The code can be found at https://github.com/xhluca/bm25s
Forward citations
Cited by 17 Pith papers
-
Towards Retrieving Interaction Spaces for Agentic Search
RISE uses BM25 to bound interaction spaces for agentic search and pre-processes documents for shell navigation, matching direct corpus interaction accuracy at roughly one-quarter the cost on BrowseComp-Plus.
-
What Do Biomedical NER and Entity Linking Benchmarks Measure? A Corpus-Centric Diagnostic Framework
A corpus-centric framework diagnoses scale, structure, overlap, metadata, and terminology properties across nine biomedical NER/EL corpora, showing substantial differences that common statistics fail to capture.
-
MEME: Multi-entity & Evolving Memory Evaluation
All tested LLM memory systems fail at dependency reasoning in multi-entity evolving scenarios, with only an expensive file-based setup showing partial recovery.
-
Overview of the MedHopQA track at BioCreative IX: track description, participation and evaluation of systems for multi-hop medical question answering
MedHopQA introduces a 1,000-question two-hop biomedical QA benchmark where retrieval-augmented systems reach 89% conceptual accuracy, outperforming zero-shot baselines by over 20 points.
-
CMDR: Contextual Multimodal Document Retrieval
A contextual multimodal document retrieval benchmark (CMDR-Bench) and embedding model (CMDR-Embed) that jointly encodes multiple document pages and splits them into page-level representations, trained with a context-a...
-
DRIFT: Refining Instruction Data via On-Policy Data Attribution
DRIFT applies on-policy influence functions with signed weighting and debiasing to attribute and refine SFT data, raising performance on 7B instruction and reasoning models over prior curation methods.
-
Improving BM25 Code Retrieval Under Fixed Generic Tokenization: Adaptive q-Log Odds as a Drop-In BM25 Fix
A q-log odds variant of BM25 raises NDCG@10 by 89% relative on CodeSearchNet Go under fixed generic tokenization while recovering standard BM25 at q=1.
-
From Articles to Premises: Building PrimeFacts, an Extraction Methodology and Resource for Fact-Checking Evidence
PrimeFacts extracts decontextualized premises from fact-check articles, raising evidence retrieval MRR by up to 30% and verdict prediction Macro-F1 by 10-20 points over baselines.
-
Verbal-R3: Verbal Reranker as the Missing Bridge between Retrieval and Reasoning
Verbal-R3 uses a verbal reranker to generate analytic narratives that guide retrieval and reasoning in LLMs, achieving SOTA results on complex QA benchmarks.
-
Question-Adaptive Graph Learning for Multi-hop Retrieval Augmented Generation
A Multi-L KG and Quest-GNN with question-adaptive intra/inter-level message passing and synthesized pre-training data improves multi-hop RAG performance up to 33.8% on high-hop questions.
-
Extraction and Search in Rocq: Theorems, Definitions and Their dependencies
TheoremExtr extracts 71,795 theorems with dependencies and 27,481 definitions from 32 Rocq projects and provides a cross-project similarity search website.
-
How Does Chunking Affect Retrieval-Augmented Code Completion? A Controlled Empirical Study
Function-based chunking underperforms other strategies in RAG code completion by 3.57-5.64 points, with context length as the dominant factor.
-
Hierarchical Abstract Tree for Cross-Document Retrieval-Augmented Generation
Ψ-RAG improves cross-document multi-hop QA performance using an adaptive hierarchical abstract tree and agent-powered hybrid retrieval, outperforming RAPTOR by 25.9% and HippoRAG 2 by 7.4% in average F1.
-
Understand and Accelerate Memory Processing Pipeline for Large Language Model Inference
Unifying LLM memory optimizations into a Prepare-Compute-Retrieve-Apply pipeline and accelerating it on GPU-FPGA hardware yields up to 2.2x faster inference and 4.7x less energy than GPU-only baselines.
-
Legal Retrieval for Public Defenders
NJ BriefBank is a domain-adapted legal retrieval tool for public defenders that improves on standard benchmarks by incorporating legal reasoning, domain data, and synthetic examples, with a new released taxonomy and a...
-
Caraman at SemEval-2026 Task 8: Three-Stage Multi-Turn Retrieval with Query Rewriting, Hybrid Search, and Cross-Encoder Reranking
A pipeline with LoRA-fine-tuned query rewriting, BM25+dense hybrid retrieval via RRF, and cross-encoder reranking reaches nDCG@5 of 0.531 on multi-turn retrieval across four domains.
-
MLLP-VRAIN UPV system for the IWSLT 2026 Simultaneous Speech Translation task
A cascaded SimulST system using Parakeet and Qwen 3.5 with adaptive black-box policies and RAG context achieves +5.82 XCOMET-XL improvement on En→De for IWSLT 2026.
discussion (0)
Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.