Author

Subhransu Das

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Preprint Aug 2026

When Does Latent Communication Pay? A Causal Audit of Relayed KV Caches in Multi-Agent LLMs

Multi-agent LLM systems relay key-value caches instead of text and credit their gains to exchanged"latent thoughts". That credit is a claim about which example's cache is relayed, not merely that one is. We audit it causally in released systems. The cache is replaced with deranged (mismatched-example), zeroed, and mome...

Jiaming Cheng, Subhransu Das, Rajiv Ramnath · 3 citations

Book Open access Jul 2026

Phase-Wise Analysis of LLM Inference Acceleration on GPU, CPU, and Edge Device

This study presents a cross-platform, multi-model empirical study, where several important observations are brought, including the contrastive effect of quantization under different hardware bottlenecks, along with a quantification of runtime delays caused by the lack of parallelism in the ARM architecture.

Subhransu Das, Jiaming Cheng, Swathi Vallabhajosyula et al. · Practice and Experience in A... · 0 citations

Review Aug 2026

Large Models for Small Devices: Recent Advances and Empirical Analysis of Edge AI Deployment

This work surveys dozens of recent works that report compression results on real hardware and extracts practical deployment guidelines from them, and deploys compact language and image models on GPU, CPU, and Raspberry Pi platforms across question answering and image segmentation.

Subhransu Das, Jiaming Cheng, Arnav Kumar et al. · 0 citations