mlsanityData to 7 Oct 2026

Bryndza at ClimateActivism 2024: Stance, Target and Hate Event Detection via Retrieval-Augmented GPT-4 and LLaMA

arXiv 2402.06549 ↗First posted 9 Feb 2024cs.CL cs.AIcited by 1

On the map: Retrieval-augmented generation → Privacy and security of RAG

Abstract (arXiv)

This study details our approach for the CASE 2024 Shared Task on Climate Activism Stance and Hate Event Detection, focusing on Hate Speech Detection, Hate Speech Target Identification, and Stance Detection as classification challenges. We explored the capability of Large Language Models (LLMs), particularly GPT-4, in zero- or few-shot settings enhanced by retrieval augmentation and re-ranking for Tweet classification. Our goal was to determine if LLMs could match or surpass traditional methods in this context. We conducted an ablation study with LLaMA for comparison, and our results indicate that our models significantly outperformed the baselines, securing second place in the Target Detection task. The code for our submission is available at https://github.com/NaiveNeuron/bryndza-case-2024

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Placed in Privacy and security of RAG, one of 15 directions in Retrieval-augmented generation. Builds on 8 of its 16 references that are in the map. First posted on arXiv 9 Feb 2024.

Builds on

8 of 16 references.

References · 8

  1. 2023GPT-4 Technical Reportcited by 18,132
  2. 2023Llama 2: Open Foundation and Fine-Tuned Chat Modelscited by 12,865
  3. 2020Retrieval-Augmented Generation for Knowledge-Intensive NLP Taskscited by 9,160
  4. 2022RankT5: Fine-Tuning T5 for Text Ranking with Ranking Lossescited by 114
  5. 2021ClimateBert: A Pretrained Language Model for Climate-Related Textcited by 89
  6. 2017Detecting Hate Speech in Social Mediacited by 42
  7. 2021DeepHate: Hate Speech Detection via Multi-Faceted Text Representationscited by 29
  8. 2023Prompting and Fine-Tuning Open-Sourced Large Language Models for Stance Classificationcited by 16

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2026: 1.

1 paper.

  1. 2026Retrieval-Augmented Generation Must Move Beyond Factual Grounding to Represent Diverse Opinionscited by 1

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  1. 2025Rethinking Hate Speech Detection on Social Media: Can LLMs Replace Traditional Models?
  2. 2025Collaborative Stance Detection via Small-Large Language Model Consistency Verification
  3. 2025Evaluating Large Language Models for Detecting Antisemitism
  4. 2023HateRephrase: Zero- and Few-Shot Reduction of Hate Intensity in Online Posts using Large Language Models
  5. 2023Revisiting Hate Speech Benchmarks: From Data Curation to System Deployment
  6. 2024The Power of LLM-Generated Synthetic Data for Stance Detection in Online Political Discussions
  7. 2025HateBench: Benchmarking Hate Speech Detectors on LLM-Generated Content and Hate Campaigns
  8. 2024SQBC: Active Learning using LLM-Generated Synthetic Data for Stance Detection in Online Political Discussions