Papers with Odia
Benchmark Creation for Aspect-Based Sentiment Analysis in Low-Resource Odia Language and Evaluation through Fine-Tuning of Multilingual Models (2025.coling-main)
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| Challenge: | Aspect-based sentiment analysis is underexplored in low-resource languages such as Odia . a dataset is annotated for two tasks: Aspect Term Extraction (ATE) and Aspect Polarity Classification (APC) |
| Approach: | They propose to use a dataset for aspect-based sentiment analysis in Odia . they use ensemble data augmentation and a fine-tuned paraphrase generation model . |
| Outcome: | The proposed dataset is annotated for two tasks: ATE and APC . the proposed dataset will spur more work for the ABSA task in Odia . |
Detecting Urgency Status of Crisis Tweets: A Transfer Learning Approach for Low Resource Languages (2020.coling-main)
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| Challenge: | We train monolingual and cross-lingual classifiers on the extracted features of tweets . we use a few state-of-the-art contextual embeddings to extract features of the tweets. |
| Approach: | They propose to use tweets to train a dataset of English and two low-resource languages to train zero-shot transfer models. |
| Outcome: | The proposed model performs well in English and in low-resource languages . the proposed model is based on state-of-the-art embeddings and semi-supervised methods . |
PARIKSHA: A Large-Scale Investigation of Human-LLM Evaluator Agreement on Multilingual and Multi-Cultural Data (2024.emnlp-main)
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| Challenge: | Evaluation of multilingual Large Language Models is challenging due to a variety of factors including the lack of benchmarks with sufficient linguistic diversity, contamination of popular benchmarks into LLM pre-training data and lack of local, cultural nuances in translated benchmarks. |
| Approach: | They evaluate 30 models across 10 Indic languages by conducting 90K human evaluations and 30K LLM-based evaluations. |
| Outcome: | The proposed models perform best in most Indic languages, while the agreement drops for direct assessment especially for Bengali and Odia. |