mlsanityData to 7 Oct 2026

ProCQA: A Large-scale Community-based Programming Question Answering Dataset for Code Search

arXiv 2403.16702 ↗First posted 25 Mar 2024cs.CL cs.IR cs.SEcited by 12

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Abstract (arXiv)

Retrieval-based code question answering seeks to match user queries in natural language to relevant code snippets. Previous approaches typically rely on pretraining models using crafted bi-modal and uni-modal datasets to align text and code representations. In this paper, we introduce ProCQA, a large-scale programming question answering dataset extracted from the StackOverflow community, offering naturally structured mixed-modal QA pairs. To validate its effectiveness, we propose a modality-agnostic contrastive pre-training approach to improve the alignment of text and code representations of current code language models. Compared to previous models that primarily employ bimodal and unimodal pairs extracted from CodeSearchNet for pre-training, our model exhibits significant performance improvements across a wide range of code retrieval benchmarks.

Key facts. Cited by 12 papers in the map (data through 7 Oct 2026). Builds on 26 of its 34 references that are in the map. First posted on arXiv 25 Mar 2024.

Builds on

26 of 34 references.

References · 26

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14 more
  1. 2021CodeNet: A Large-Scale AI for Code Dataset for Learning a Diversity of Coding Taskscited by 199
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  3. 2020Contrastive Code Representation Learningcited by 76
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  14. 2022Cross-Domain Deep Code Search with Meta Learningcited by 6

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 2; 2025: 4; 2026: 6.

12 papers.

  1. 2025SWE-QA: Can Language Models Answer Repository-level Code Questions?cited by 37
  2. 2024Beyond Functional Correctness: Investigating Coding Style Inconsistencies in Large Language Modelscited by 15
  3. 2024CoSQA+: Pioneering the Multi-Choice Code Search Benchmark with Test-Driven Agentscited by 11
  4. 2026F2LLM-v2: Inclusive, Performant, and Efficient Embeddings for a Multilingual Worldcited by 10
  5. 2025ComRAG: Retrieval-Augmented Generation with Dynamic Vector Stores for Real-time Community Question Answering in Industrycited by 3
  6. 2026ShortCoder: Knowledge-Augmented Syntax Optimization for Token-Efficient Code Generationcited by 3
  7. 2025MASTER: Enhancing Large Language Model via Multi-Agent Simulated Teachingcited by 2
  8. 2025Empowering RepoQA-Agent based on Reinforcement Learning Driven by Monte-carlo Tree Searchcited by 1
  9. 2026Neurosymbolic Repo-level Code Localizationcited by 1
  10. 2026Beyond Retrieval: A Multitask Benchmark and Model for Code Searchcited by 1
  11. 2026SWE-Spot: Building Small Repo-Experts with Repository-Centric Learningcited by 0
  12. 2026DeepRepoQA: Code Repository Question Answering with Deep Agent Explorationcited by 0