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README.md

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 ---
-tags: ["benchmark", "beir", "cqadupstack_programmers", "retrieval"]
+language:
+  - en
+license: cc-by-sa-4.0
+tags:
+  - retrieval
+  - text-retrieval
+  - beir
+  - programming
+  - stack-exchange
+  - duplicate-question-detection
+  - community-question-answering
+  - benchmark
+pretty_name: BEIR CQADupStack — Programmers (retrieval)
+size_categories: 10K<n<100K
 task_categories:
-  - question-answering
   - text-retrieval
-size_categories:
-  - 1K<n<10K
 ---
 
-# beir_cqadupstack_programmers
+# CQADupStack / Programmers (BEIR) — programming Q&A retrieval
+
+## Dataset description
+
+**CQADupStack** is a benchmark for **community question answering (cQA)** built from Stack Exchange data. It was introduced by Hoogeveen, Verspoor, and Baldwin at **ADCS 2015** to support research on **duplicate questions**: finding earlier posts that match or subsume a newly asked question, so users can reuse existing answers instead of opening redundant threads.
+
+The full CQADupStack release aggregates **twelve** Stack Exchange subcommunities (subforums). Each subforum is distributed as its own slice with **pre-defined splits** and **duplicate annotations** (which posts are duplicates of which), enabling comparable retrieval and classification experiments. The **Programmers** slice corresponds to the historical **Programmers.StackExchange** community (software engineering and professional programming topics, distinct from “pure code” Q&A).
+
+**BEIR** (*Benchmarking IR*) repackaged CQADupStack — including the **Programmers** sub-benchmark — as part of a **heterogeneous zero-shot IR benchmark** spanning many tasks and domains. In BEIR’s retrieval setting, each slice is a standard **corpus + queries + qrels** collection: systems must rank corpus documents so that human-annotated duplicates appear at the top.
+
+This repository (`orgrctera/beir_cqadupstack_programmers`) exposes the **BEIR CQADupStack / Programmers** **test** split in **Parquet** form for retrieval evaluation pipelines. Each row is one **query** with **relevance judgments** (`qrels`) pointing at corpus document identifiers, aligned with the BEIR release.
+
+### Scale (BEIR / Programmers retrieval setting)
+
+For the **Programmers** task as used in embedding benchmarks (e.g. MTEB’s “CQADupstackProgrammersRetrieval”), the **test** split is on the order of:
+
+- **~32k** unique **documents** in the corpus (Stack Exchange question posts).
+- **876** **queries** in the official test set.
+- **~1.9** relevant documents per query on average (some queries have many duplicates annotated).
+
+Exact counts depend on the upstream BEIR snapshot; see [BEIR on GitHub](https://github.com/beir-cellar/beir) for version-precise figures.
+
+## Task: retrieval (CQADupStack Programmers)
+
+The task is **ad hoc passage (or document) retrieval** for **duplicate question finding**:
+
+1. **Input:** a natural-language **question** (the query) posted on the Programmers forum.
+2. **Output:** a ranked list of **document IDs** from the Programmers corpus (or scores over the full collection), such that **relevant** IDs — posts marked as duplicates of the query in the official qrels — receive high rank.
+
+Evaluation uses standard IR metrics (e.g. **nDCG@k**, **Recall@k**, **MRR**), as in BEIR’s evaluation utilities or frameworks such as Pyserini / MTEB.
+
+> **Note:** Full retrieval evaluation also requires the **corpus** (passage text keyed by ID). This dataset card describes the **query + qrels** side as prepared for CTERA-style evaluation rows; align corpus IDs with the same **BEIR CQADupStack / Programmers** corpus you use for indexing.
+
+## Data format (this repository)
+
+Each record includes:
+
+| Field | Description |
+|--------|-------------|
+| `id` | UUID for this example row. |
+| `input` | The **query text** (question). |
+| `expected_output` | JSON string: list of objects `{"id": "<corpus-doc-id>", "score": <relevance>}`. Scores follow the BEIR qrels convention (typically `1` for relevant in binary settings). |
+| `metadata.query_id` | Original BEIR / CQADupStack query identifier (string). |
+| `metadata.split` | Split name (here: `test`). |
 
-BEIR CQADupStack/programmers test split
+### Example 1 — single annotated duplicate
 
-| Field | Value |
-|-------|-------|
-| Benchmark | beir |
-| Sub-benchmark | cqadupstack_programmers |
-| Type | retrieval |
-| Total items | 876 |
-| Splits | 1 |
+```json
+{
+  "id": "4fc8cccf-f1d8-4685-adcc-6506b470d0c1",
+  "input": "How do I write a specification?",
+  "expected_output": "[{\"id\": \"34356\", \"score\": 1}]",
+  "metadata.query_id": "132074",
+  "metadata.split": "test"
+}
+```
 
-## Splits
+### Example 2 — multiple duplicate targets
 
-| Split | Items |
-|-------|-------|
-| test | 876 |
+```json
+{
+  "id": "0e2e4cb0-3d07-4208-94bb-bc20761f4bb6",
+  "input": "Is this a violation of the Liskov Substitution Principle?",
+  "expected_output": "[{\"id\": \"224350\", \"score\": 1}, {\"id\": \"254398\", \"score\": 1}, {\"id\": \"229549\", \"score\": 1}, {\"id\": \"189222\", \"score\": 1}, {\"id\": \"177831\", \"score\": 1}, {\"id\": \"145941\", \"score\": 1}, {\"id\": \"82682\", \"score\": 1}, {\"id\": \"237843\", \"score\": 1}, {\"id\": \"132612\", \"score\": 1}, {\"id\": \"107723\", \"score\": 1}, {\"id\": \"231300\", \"score\": 1}]",
+  "metadata.query_id": "170138",
+  "metadata.split": "test"
+}
+```
+
+## References
+
+### CQADupStack (original dataset)
+
+**Doris Hoogeveen, Karin M. Verspoor, Timothy Baldwin**  
+*CQADupStack: A Benchmark Data Set for Community Question-Answering Research*  
+Proceedings of the 20th Australasian Document Computing Symposium (ADCS 2015), pages 3:1–3:8.
+
+**Abstract (summary):** The paper presents CQADupStack, a resource derived from Stack Exchange with **duplicate question annotations** across multiple communities, together with standard splits and evaluation tooling for **retrieval** and **classification** experiments on duplicate detection in cQA.
+
+- Paper: [ACM DL 10.1145/2838931.2838934](https://doi.org/10.1145/2838931.2838934) — IR Anthology entry: [hoogeveen-2015-cqadupstack](https://ir.webis.de/anthology/2015.adcs_conference-2015.3/).
+- Original data landing page (University of Melbourne NLP): [CQADupStack resources](http://nlp.cis.unimelb.edu.au/resources/cqadupstack/).
+
+### BEIR benchmark (CQADupStack as a subset)
+
+**Nandan Thakur, Nils Reimers, Andreas Rücklé, Abhishek Srivastava, Iryna Gurevych**  
+*BEIR: A Heterogeneous Benchmark for Zero-shot Evaluation of Information Retrieval Models*  
+NeurIPS 2021 (Datasets and Benchmarks Track).
+
+**Abstract (from arXiv):** *“Existing neural information retrieval (IR) models have often been studied in homogeneous and narrow settings, which has considerably limited insights into their out-of-distribution (OOD) generalization capabilities. To address this, and to facilitate researchers to broadly evaluate the effectiveness of their models, we introduce Benchmarking-IR (BEIR), a robust and heterogeneous evaluation benchmark for information retrieval. We leverage a careful selection of 18 publicly available datasets from diverse text retrieval tasks and domains and evaluate 10 state-of-the-art retrieval systems including lexical, sparse, dense, late-interaction and re-ranking architectures on the BEIR benchmark. Our results show BM25 is a robust baseline and re-ranking and late-interaction-based models on average achieve the best zero-shot performances, however, at high computational costs. In contrast, dense and sparse-retrieval models are computationally more efficient but often underperform other approaches, highlighting the considerable room for improvement in their generalization capabilities.”*
+
+- Paper: [arXiv:2104.08663](https://arxiv.org/abs/2104.08663) — [OpenReview](https://openreview.net/forum?id=wCu6T5xFjeJ); code and data: [BEIR on GitHub](https://github.com/beir-cellar/beir).
+
+### Related resources
+
+- **MTEB** packages the same retrieval task as [`mteb/cqadupstack-programmers`](https://huggingface.co/datasets/mteb/cqadupstack-programmers) (corpus + queries + qrels) with descriptive statistics.
+- **BEIR-style mirrors** on Hugging Face for raw JSONL / TSV layouts (e.g. `BeIR/cqadupstack-*` datasets where applicable) — see the upstream BEIR project for the canonical file layout.
+
+## Citation
+
+If you use **CQADupStack**, cite the ADCS 2015 paper. If you use the **BEIR** benchmark packaging, cite the BEIR NeurIPS 2021 paper. BibTeX for CQADupStack is available from the [IR Anthology](https://ir.webis.de/anthology/2015.adcs_conference-2015.3/) (BibTeX download on that page).
+
+## License
+
+Stack Exchange content is typically shared under **Creative Commons** terms. This card marks **`cc-by-sa-4.0`** as a common license for Stack Exchange–derived text; verify against your corpus snapshot and upstream terms if compliance is strict.
+
+---
 
-Exported from Langfuse.
+*Dataset card maintained for the `orgrctera/beir_cqadupstack_programmers` Hub repository.*