Papers by Harsh Lara

1 papers
MoDE: Effective Multi-task Parameter Efficient Fine-Tuning with a Mixture of Dyadic Experts (2025.findings-naacl)

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Challenge: Recent efforts have explored mixtures of LoRA modules for multi-task settings, but this study reveals redundancy in the down-projection matrix of these architectures.
Approach: They propose a method to share down-projection matrix across tasks and employ atomic rank-one adapters coupled with routers that allow more sophisticated task-level specialization.
Outcome: The proposed method outperforms state-of-the-art models on a SNI benchmark and provides a practical solution for deploying lightweight models.

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