Papers by Sangeetha Abdu Jyothi
LinguaLinked: Distributed Large Language Model Inference on Mobile Devices (2024.acl-demos)
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| Challenge: | Recent research shows that large language models demonstrate enhanced capabilities in various language tasks. |
| Approach: | They introduce a system for decentralized, distributed LLM inference on mobile devices . they use optimized model assignment technique to segment LLMs and linear optimization to align segments with each device . |
| Outcome: | The proposed system performs well on high-end to low-end Android devices. |
CoopQ: Cooperative Game Inspired Layerwise Mixed Precision Quantization for LLMs (2026.findings-acl)
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| Challenge: | Existing methods for large language models struggle when the average precision drops below four bits, limiting deployment on resourceconstrained devices such as mobiles, edge sensors, or standard GPUs. |
| Approach: | They propose a game-like game-inspired mixed-precision quantization method which translates these Shapley estimates into a binary quadratic optimization formulation, assigning either 2 or 4-bit precision to layers under strict memory constraints. |
| Outcome: | The proposed method reduces Perplexity by 20 – 80 % across average precisions spanning 4 bit down to 2 bit, compared to methods relying on isolated metrics. |