Papers by Vikram Nelvoy Rajendiran
Unlocking the Edge deployment and ondevice acceleration of multi-LoRA enabled one-for-all foundational LLM (2026.findings-acl)
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Sravanth Kodavanti, Sowmya Vajrala, Srinivas Soumitri Miriyala, Utsav Tiwari, Uttam Kumar, Utkarsh Kumar Mahawar, Achal Pratap Singh, Arya D, Narendra Mutyala, Vikram Nelvoy Rajendiran, Sharan Kumar Allur, Euntaik Lee, Dohyoung Kim, HyeonSu Lee, Gyusung Cho, JungBae Kim
| Challenge: | a framework for efficient on-device inference of large language models is needed for smartphones . memory, latency, and runtime flexibility are constraints for large language model deployments. |
| Approach: | They propose a hardware-aware framework for efficient on-device inference of a LLaMA-based multilingual foundation model for Samsung Galaxy S24 and S25 devices with SM8650 and SM8750 chipsets respectively. |
| Outcome: | The proposed framework improves memory, latency and performance across 9 languages and 8 tasks. |