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Srijith Nair

2 accepted papers

2025

EcoLoRA: Communication-Efficient Federated Fine-Tuning of Large Language Models

EMNLP 2025

To address data locality and privacy restrictions, Federated Learning (FL) has recently been adopted to fine-tune large language models (LLMs), enabling improved performance on various downstream tasks without requiring aggregated data. However, the repeated exchange of model updates in FL can resul

Cited by 0SourcePDFScholar
2025

FSL-SAGE: Accelerating Federated Split Learning via Smashed Activation Gradient Estimation

ICML 2025poster

Collaborative training methods like Federated Learning (FL) and Split Learning (SL) enable distributed machine learning without sharing raw data. However, FL assumes clients can train entire models, which is infeasible for large-scale models. In contrast, while SL alleviates the client memory const…