Papers by Pruthwik Mishra
Fine-tuning Pre-trained Named Entity Recognition Models For Indian Languages (2024.naacl-srw)
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| Challenge: | Named Entity Recognition (NER) is a useful component in NLP applications. |
| Approach: | They propose to use annotated named entity corpora to classify a given entity into a category within a textual document. |
| Outcome: | The proposed model achieves an F1 score of 0.80 on an unseen dataset for Indian languages. |
Controllable Text Summarization: Unraveling Challenges, Approaches, and Prospects - A Survey (2024.findings-acl)
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| Challenge: | scholarly attention has turned to the development of text summarization methods that are more closely tailored and controlled to align with specific objectives and user needs. |
| Approach: | They formalize a controllable text summarization task and categorize controllability attributes according to their shared characteristics and objectives. |
| Outcome: | The proposed method is tailored to meet the specific intent and needs of users. |
Linguistically Informed Hindi-English Neural Machine Translation (2020.lrec-1)
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| Challenge: | Neural Machine Translation (NMT) is a promising approach to machine translation . lack of parallel training data for Hindi-English is limiting . |
| Approach: | They propose to incorporate linguistic knowledge encoded by Hindi phenomena into a Transformer model to improve the translation performance. |
| Outcome: | The proposed model incorporates linguistic features to improve the translation performance. |
AGIC: Attention-Guided Image Captioning to Improve Caption Relevance (2026.findings-eacl)
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| Challenge: | Existing methods for image captioning generate generic captions that are limited in capturing nuanced visual details. |
| Approach: | They propose attention-guided image captioning which amplifies visual regions directly in the feature space to guide caption generation. |
| Outcome: | The proposed approach matches or surpasses state-of-the-art models while achieving faster inference. |
HAWP: a Dataset for Hindi Arithmetic Word Problem Solving (2022.lrec-1)
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| Challenge: | Word problem solving is a challenging and interesting task in NLP. |
| Approach: | They propose to use equations to solve Hindi arithmetic word problems . they propose to also use equation equivalence to evaluate word problem solvers . |
| Outcome: | The proposed dataset is based on 2336 arithmetic word problems in Hindi . it also includes baseline systems and evaluation techniques . |
Annotated Corpus for Sentiment Analysis in Odia Language (2020.lrec-1)
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| Challenge: | Existing sentiment analysis models are not available for Odia 1 as it is a resource-poor language. |
| Approach: | They create an annotated Odia corpus and test its usability by training and testing on the corpus using various classifiers. |
| Outcome: | The created corpus contains 2045 Odia sentences from news domain annotated with sentiment labels using a well-defined annotation scheme. |