Papers by P. K. Srijith

2 papers
TL-CL: Task And Language Incremental Continual Learning (2024.emnlp-main)

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Challenge: a multilingual model is periodically updated to accommodate new tasks in previously learned languages or new languages for established tasks.
Approach: They propose an adapter-based parameter-efficient fine-tuning strategy for continual learning in multilingual models.
Outcome: The proposed approach outperforms other parameter-efficient approaches without access to historical data for replay.
Evaluation of Deep Gaussian Processes for Text Classification (2020.lrec-1)

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Challenge: Existing models for text classification are limited by the expressability limit and require enormous empirical efforts to come up with a robust model architecture.
Approach: They propose a Bayesian non-parametric Bayessian nonparametric model with strong function compositionality for the task of Text Classification.
Outcome: The proposed models outperform shallow and deep Gaussian processes on the TREC (Text REtrieval Conference) datasets.

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