PromptBasedEmotionClassificationBenchmarked/CITATION.cff at main · hacky1997/PromptBasedEmotionClassificationBenchmarked · GitHub

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cff-version: 1.2.0
message: "If you use this software or results, please cite it as below."

title: "Prompt-Based Emotion Classification with Efficient Transformers"
type: software

authors:
  - family-names: Gayen
    given-names: Avijit
    affiliation: "IIIT Guwahati / Techno India University"
    email: avijit.gayen@iiitg.ac.in
  - family-names: Naskar
    given-names: Sayak
    affiliation: "IIIT Guwahati"
    email: sayak.naskar25m@iiitg.ac.in
  - family-names: Mishra
    given-names: Shilpi
    affiliation: "Techno India University"
  - family-names: Jana
    given-names: Angshuman
    affiliation: "IIIT Guwahati"
    email: angshuman@iiitg.ac.in

repository-code: "https://github.com/YOUR_USERNAME/emotion-classification"
url: "https://arxiv.org/abs/XXXX.XXXXX"
license: MIT
year: 2025

abstract: >
  A systematic study of prompt-based emotion classification across six emotion
  categories using five efficient transformer encoders (DistilBERT, DistilRoBERTa,
  RoBERTa-base, ALBERT-base-v2, ELECTRA-base) on the SetFit/emotion dataset.
  The study includes prompt ablation with McNemar significance tests, multi-seed
  robustness with bootstrap confidence intervals, minority-class rebalancing,
  parameter-efficient prefix-tuning, few-shot evaluation, and zero-shot
  cross-domain generalisation on GoEmotions and MELD.

keywords:
  - emotion classification
  - prompt engineering
  - transformer
  - ELECTRA
  - DistilBERT
  - affective computing
  - few-shot learning
  - cross-domain generalisation