Official code for ACL2025 "🔍 Retrieval Models Aren’t Tool-Savvy: Benchmarking Tool Retrieval for Large Language Models"
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Updated
Dec 22, 2025 - JavaScript
Official code for ACL2025 "🔍 Retrieval Models Aren’t Tool-Savvy: Benchmarking Tool Retrieval for Large Language Models"
smallevals — CPU-fast, GPU-blazing fast offline retrieval evaluation for RAG systems with tiny QA models.
Official codebase for the ACL 2025 Findings paper: Optimized Text Embedding Models and Benchmarks for Amharic Passage Retrieval.
Published PyPI package for ArXiv embedding benchmarks, retrieval evaluation, and scientific RAG experiments.
Deterministic RAG evaluation toolkit -- retrieval metrics (recall, precision, MRR), corpus overlap detection, and CI regression gating without model calls.
RAG retrieval benchmark runner with JSON reports, Pareto plots, and regression gates for retrieval quality changes.
Bilingual RAG evaluation benchmark for culturally grounded English/Uzbek retrieval
Open-source retrieval diagnostics toolkit for enterprise RAG pipelines
Local-first memory infrastructure for coding workflows: deterministic retrieval, explainable traces, MCP/REST/SDK interfaces, and standalone browser-first operation.
A systems-level analysis of static RAG pipelines, isolating ingestion, retrieval, and ranking boundaries to expose structural failure modes before generation.
RAG chatbot over the WHO/PPRI pharmaceutical glossary - Gemini/Ollama behind a factory, ChromaDB, Streamlit; evaluated with hit@k vs a BM25 baseline, RAGAS, and refusal checks
Research-grade neuro-symbolic RAG framework where retrieval is a policy, not a vector search, built for evaluation, ablation, and reliability analysis.
Active web-search RAG workbench with provider routing, source extraction, citation verification, and extractive fallback.
A controlled experiment evaluating whether hybrid (dense + sparse) retrieval surfaces evidence that dense-only RAG systems misrank—without changing generation behavior.
RAG evaluation framework: hit-rate, MRR, faithfulness scoring, and async batch evaluation with golden question datasets
QPP for Clarification Need Prediction in context-grounded multi-turn Conversation. Clean implementations of QPP baselines suitable for multi-turn conversational dataset with ranked documents (opt.). Designed to detect ambiguous search queries.
Benchmarking BM25, dense retrieval, hybrid search, and re-rankers with gold-label evaluation and query-level failure analysis.
Open multilingual RAG benchmark for retrieval-grounded educational question answering
Archived: merged into signal-rag/evals/retrieval/coreb.
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