mlsanityData to 14 Oct 2026

Zero-Shot Multi-Label Classification of Bangla Documents: Large Decoders Vs. Classic Encoders

arXiv 2503.02993 ↗First posted 4 Mar 2025cs.CL cs.IRcited by 2

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Abstract (arXiv)

Bangla, a language spoken by over 300 million native speakers and ranked as the sixth most spoken language worldwide, presents unique challenges in natural language processing (NLP) due to its complex morphological characteristics and limited resources. While recent Large Decoder Based models (LLMs), such as GPT, LLaMA, and DeepSeek, have demonstrated excellent performance across many NLP tasks, their effectiveness in Bangla remains largely unexplored. In this paper, we establish the first benchmark comparing decoder-based LLMs with classic encoder-based models for Zero-Shot Multi-Label Classification (Zero-Shot-MLC) task in Bangla. Our evaluation of 32 state-of-the-art models reveals that, existing so-called powerful encoders and decoders still struggle to achieve high accuracy on the Bangla Zero-Shot-MLC task, suggesting a need for more research and resources for Bangla NLP.

Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 25 of its 63 references that are in the map. First posted on arXiv 4 Mar 2025.

Builds on

25 of 63 references.

References · 25

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
  2. 2020Language Models are Few-Shot Learnerscited by 32,419
  3. 2023LLaMA: Open and Efficient Foundation Language Modelscited by 14,132
  4. 2019Sentence-BERT: Sentence Embeddings using Siamese BERT-Networkscited by 9,170
  5. 2021Finetuned Language Models Are Zero-Shot Learnerscited by 3,780
  6. 2024Gemini 1.5: Unlocking multimodal understanding across millions of tokens of contextcited by 3,224
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  12. 2018Massively Multilingual Sentence Embeddings for Zero-Shot Cross-Lingual Transfer and Beyondcited by 434
13 more
  1. 2019Benchmarking Zero-shot Text Classification: Datasets, Evaluation and Entailment Approachcited by 308
  2. 2023SOLAR 10.7B: Scaling Large Language Models with Simple yet Effective Depth Up-Scalingcited by 172
  3. 2025Qwen2.5-1M Technical Reportcited by 164
  4. 2021BanglaBERT: Language Model Pretraining and Benchmarks for Low-Resource Language Understanding Evaluation in Banglacited by 125
  5. 2022BanglaNLG and BanglaT5: Benchmarks and Resources for Evaluating Low-Resource Natural Language Generation in Banglacited by 42
  6. 2020BanFakeNews: A Dataset for Detecting Fake News in Banglacited by 40
  7. 2019Integrating Semantic Knowledge to Tackle Zero-shot Text Classificationcited by 28
  8. 2020Zero-Shot Audio Classification via Semantic Embeddingscited by 21
  9. 2017Multi-label Dataless Text Classification with Topic Modelingcited by 14
  10. 2020Detection of Bangla Fake News using MNB and SVM Classifiercited by 10
  11. 2020Bangla Text Classification using Transformerscited by 10
  12. 2023Zero-Shot Multi-Label Topic Inference with Sentence Encoderscited by 6
  13. 2021Bangla Image Caption Generation through CNN-Transformer based Encoder-Decoder Networkcited by 2

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 1; 2026: 1.

2 papers.

  1. 2025DL3M: A Vision-to-Language Framework for Expert-Level Medical Reasoning through Deep Learning and Large Language Modelscited by 0
  2. 2026Are LLMs Ready to Replace Bangla Annotators?cited by 0