mlsanityData to 14 Oct 2026

ClimRetrieve: A Benchmarking Dataset for Information Retrieval from Corporate Climate Disclosures

arXiv 2406.09818 ↗First posted 14 Jun 2024cs.IRcited by 12

On the map: Retrieval-augmented generation → Agentic RAG, agents and memory

Abstract (arXiv)

To handle the vast amounts of qualitative data produced in corporate climate communication, stakeholders increasingly rely on Retrieval Augmented Generation (RAG) systems. However, a significant gap remains in evaluating domain-specific information retrieval - the basis for answer generation. To address this challenge, this work simulates the typical tasks of a sustainability analyst by examining 30 sustainability reports with 16 detailed climate-related questions. As a result, we obtain a dataset with over 8.5K unique question-source-answer pairs labeled by different levels of relevance. Furthermore, we develop a use case with the dataset to investigate the integration of expert knowledge into information retrieval with embeddings. Although we show that incorporating expert knowledge works, we also outline the critical limitations of embeddings in knowledge-intensive downstream domains like climate change communication.

Key facts. Cited by 12 papers in the map (data through 14 Oct 2026). Placed in Agentic RAG, agents and memory, one of 15 directions in Retrieval-augmented generation. Builds on 12 of its 57 references that are in the map. First posted on arXiv 14 Jun 2024.

Builds on

12 of 57 references.

References · 12

  1. 2020Retrieval-Augmented Generation for Knowledge-Intensive NLP Taskscited by 9,297
  2. 2023Self-RAG: Learning to Retrieve, Generate, and Critique through Self-Reflectioncited by 1,839
  3. 2021BEIR: A Heterogenous Benchmark for Zero-shot Evaluation of Information Retrieval Modelscited by 1,252
  4. 2023RAGTruth: A Hallucination Corpus for Developing Trustworthy Retrieval-Augmented Language Modelscited by 283
  5. 2024The Power of Noise: Redefining Retrieval for RAG Systemscited by 281
  6. 2023ARES: An Automated Evaluation Framework for Retrieval-Augmented Generation Systemscited by 265
  7. 2024RAFT: Adapting Language Model to Domain Specific RAGcited by 262
  8. 2020CLIMATE-FEVER: A Dataset for Verification of Real-World Climate Claimscited by 196
  9. 2023CHATREPORT: Democratizing Sustainability Disclosure Analysis through LLM-based Toolscited by 29
  10. 2023Assessing Large Language Models on Climate Informationcited by 23
  11. 2020ClimaText: A Dataset for Climate Change Topic Detectioncited by 22
  12. 2023ClimateBERT-NetZero: Detecting and Assessing Net Zero and Reduction Targetscited by 17

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 5; 2026: 7.

12 papers.

  1. 2025Can LLMs Be Trusted for Evaluating RAG Systems? A Survey of Methods and Datasetscited by 7
  2. 2025SustainableQA: A Comprehensive Question Answering Dataset for Corporate Sustainability and EU Taxonomy Reportingcited by 5
  3. 2025ClimateBench-M: A Multi-Modal Climate Data Benchmark with a Simple Generative Methodcited by 4
  4. 2025Enhancing Retrieval for ESGLLM via ESG-CID -- A Disclosure Content Index Finetuning Dataset for Mapping GRI and ESRScited by 2
  5. 2026pdfQA: Diverse, Challenging, and Realistic Question Answering over PDFscited by 2
  6. 2026UsefulBench: Towards Decision-Useful Information as a Target for Information Retrievalcited by 1
  7. 2026DiagnosticIQ: A Benchmark for LLM-Based Industrial Maintenance Action Recommendation from Symbolic Rulescited by 1
  8. 2025Climate Finance Benchcited by 0
  9. 2026LLM Benchmark-User Need Misalignment for Climate Changecited by 0
  10. 2026RAG-DIVE: A Dynamic Approach for Multi-Turn Dialogue Evaluation in Retrieval-Augmented Generationcited by 0
  11. 2026Automating Multi-Hop RAG Evaluation via TRIAD: From Context Extraction to Validated Dataset Generationcited by 0
  12. 2026Climate-ModernBERT: Revisiting Corpus Composition for Domain-Adaptive Continued Pretrainingcited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2025Querying Climate Knowledge: Semantic Retrieval for Scientific Discovery
  2. 2024Responsible Retrieval Augmented Generation for Climate Decision Making from Documents
  3. 2025CF-RAG: A Dataset and Method for Carbon Footprint QA Using Retrieval-Augmented Generation
  4. 2025Listen to the Context: Towards Faithful Large Language Models for Retrieval Augmented Generation on Climate Questions
  5. 2025ESGenius: Benchmarking LLMs on Environmental, Social, and Governance (ESG) and Sustainability Knowledge
  6. 2025CarbonChat: Large Language Model-Based Corporate Carbon Emission Analysis and Climate Knowledge Q&A System
  7. 2026Beyond Vector Search: Comparing Classical RAG with Hybrid GraphRAG for Climate Science Q&A
  8. 2025Emission-GPT: A domain-specific language model agent for knowledge retrieval, emission inventory and data analysis