Summary of On Importance Of Code-mixed Embeddings For Hate Speech Identification, by Shruti Jagdale et al.
On Importance of Code-Mixed Embeddings for Hate Speech Identificationby Shruti Jagdale, Omkar Khade, Gauri Takalikar,…
On Importance of Code-Mixed Embeddings for Hate Speech Identificationby Shruti Jagdale, Omkar Khade, Gauri Takalikar,…
Automated Literature Review Using NLP Techniques and LLM-Based Retrieval-Augmented Generationby Nurshat Fateh Ali, Md. Mahdi…
New Faithfulness-Centric Interpretability Paradigms for Natural Language Processingby Andreas MadsenFirst submitted to arxiv on: 27…
Non-Contextual BERT or FastText? A Comparative Analysisby Abhay Shanbhag, Suramya Jadhav, Amogh Thakurdesai, Ridhima Sinare,…
Towards Efficient Model-Heterogeneity Federated Learning for Large Modelsby Ruofan Jia, Weiying Xie, Jie Lei, Haonan…
Predicting Emergent Capabilities by Finetuningby Charlie Snell, Eric Wallace, Dan Klein, Sergey LevineFirst submitted to…
Development of Pre-Trained Transformer-based Models for the Nepali Languageby Prajwal Thapa, Jinu Nyachhyon, Mridul Sharma,…
Signformer is all you need: Towards Edge AI for Sign Languageby Eta YangFirst submitted to…
ULTra: Unveiling Latent Token Interpretability in Transformer Based Understandingby Hesam Hosseini, Ghazal Hosseini Mighan, Amirabbas…
Bias in Large Language Models: Origin, Evaluation, and Mitigationby Yufei Guo, Muzhe Guo, Juntao Su,…