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Atula Tejaswi Neerkaje

4 accepted papers

2024

RISE: Robust Early-exiting Internal Classifiers for Suicide Risk Evaluation

COLING 2024main

Suicide is a serious public health issue, but it is preventable with timely intervention. Emerging studies have suggested there is a noticeable increase in the number of individuals sharing suicidal thoughts online. As a result, utilising advance Natural Language Processing techniques to build autom…

Cited by 1SourcePDFScholar
2024

SVFT: Parameter-Efficient Fine-Tuning with Singular Vectors

NeurIPS 2024poster

Popular parameter-efficient fine-tuning (PEFT) methods, such as LoRA and its variants, freeze pre-trained model weights $\(\mathbf{W}\)$ and inject learnable matrices $\(\mathbf{\Delta W}\)$. These $\(\mathbf{\Delta W}\)$ matrices are structured for efficient parameterization, often using techniques…

2024

Saliency-Aware Interpolative Augmentation for Multimodal Financial Prediction

COLING 2024main

Predicting price variations of financial instruments for risk modeling and stock trading is challenging due to the stochastic nature of the stock market. While recent advancements in the Financial AI realm have expanded the scope of data and methods they use, such as textual and audio cues from fina…

2022

Intermix: An Interference-Based Data Augmentation and Regularization Technique for Automatic Deep Sound Classification

ICASSP 2022accepted

In this paper, we present InterMix, an interference-based regularization and data augmentation strategy for automatic sound classification. InterMix creates virtual training examples by creating an interference-based mixed representation for a sampled phase difference and mixup ratio. InterMix can b…

Cited by 0SourceScholar