mlsanityData to 14 Oct 2026

LLMsAgainstHate @ NLU of Devanagari Script Languages 2025: Hate Speech Detection and Target Identification in Devanagari Languages via Parameter Efficient Fine-Tuning of LLMs

arXiv 2412.17131 ↗First posted 22 Dec 2024cs.CLcited by 2

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Abstract (arXiv)

The detection of hate speech has become increasingly important in combating online hostility and its real-world consequences. Despite recent advancements, there is limited research addressing hate speech detection in Devanagari-scripted languages, where resources and tools are scarce. While large language models (LLMs) have shown promise in language-related tasks, traditional fine-tuning approaches are often infeasible given the size of the models. In this paper, we propose a Parameter Efficient Fine tuning (PEFT) based solution for hate speech detection and target identification. We evaluate multiple LLMs on the Devanagari dataset provided by (Thapa et al., 2025), which contains annotated instances in 2 languages - Hindi and Nepali. The results demonstrate the efficacy of our approach in handling Devanagari-scripted content.

Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 19 of its 41 references that are in the map. First posted on arXiv 22 Dec 2024.

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19 of 41 references.

References · 19

  1. 2020Language Models are Few-Shot Learnerscited by 32,419
  2. 2024The Llama 3 Herd of Modelscited by 14,715
  3. 2021LoRA: Low-Rank Adaptation of Large Language Modelscited by 14,380
  4. 2022Large Language Models are Zero-Shot Reasonerscited by 4,374
  5. 2021Prefix-Tuning: Optimizing Continuous Prompts for Generationcited by 3,915
  6. 2021The Power of Scale for Parameter-Efficient Prompt Tuningcited by 3,795
  7. 2024Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phonecited by 1,917
  8. 2022Few-Shot Parameter-Efficient Fine-Tuning is Better and Cheaper than In-Context Learningcited by 896
  9. 2017Automated Hate Speech Detection and the Problem of Offensive Languagecited by 736
  10. 2023Knowledge Transfer from High-Resource to Low-Resource Programming Languages for Code LLMscited by 45
  11. 2022Hate Speech and Offensive Language Detection in Bengalicited by 19
  12. 2021Hate and Offensive Speech Detection in Hindi and Marathicited by 18
7 more
  1. 2024Shortcomings of LLMs for Low-Resource Translation: Retrieval and Understanding are Both the Problemcited by 17
  2. 2023Memotion 3: Dataset on Sentiment and Emotion Analysis of Codemixed Hindi-English Memescited by 12
  3. 2023Uncovering Political Hate Speech During Indian Election Campaign: A New Low-Resource Dataset and Baselinescited by 8
  4. 2021Hater-O-Genius Aggression Classification using Capsule Networkscited by 7
  5. 2021Offense Detection in Dravidian Languages using Code-Mixing Index based Focal Losscited by 6
  6. 2023NUAA-QMUL-AIIT at Memotion 3: Multi-modal Fusion with Squeeze-and-Excitation for Internet Meme Emotion Analysiscited by 2
  7. 2023Overview of Memotion 3: Sentiment and Emotion Analysis of Codemixed Hinglish Memescited by 2

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Cited by year

Citing papers per year: 2025: 2.

2 papers.

  1. 2025Beyond Monolingual Assumptions: A Survey of Code-Switched NLP in the Era of Large Language Models across Modalitiescited by 5
  2. 2025Parameter-Efficient Fine-Tuning for Low-Resource Languages: A Comparative Study of LLMs for Bengali Hate Speech Detectioncited by 3