Institution profile

Amrita Vishwa Vidyapeetham

Academic institutionnorthamerica · us
Official website
Research library36linked papers
Opportunities0open roles
Selected work

Representative Papers

ChaosProbe: A Neurochaotic Lens on Frozen Transformer Input-Embedding Spaces

Aug 03, 2026

This work addresses the challenge of characterizing the input embedding space structure of frozen Transformers without relying on downstream tasks or contextual computations. It introduces ChaosProbe, a novel method that pioneers the application of neural chaos dynamics to embedding analysis: by applying deterministic chaotic trajectory transformations to input embeddings and combining neuronal firing rates with entropy responses, it generates fixed-length structural fingerprints. This approach requires no training or task-specific adaptation, yet effectively reveals macroscopic relationships among embedding spaces. Experiments across four pretrained models and 80 neutral prompts demonstrate that multiple similarity metrics consistently recover both intra-family nearest neighbors and inter-family pairings, confirming the stability and validity of the proposed fingerprints.

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Machines that know they are aging: a framework for hardware-aware autonomous intelligence

Jul 30, 2026

This work addresses the critical challenge that autonomous systems often fail in practice due to hardware aging—such as battery degradation and sensor drift—which causes their actual capabilities to deviate from AI assumptions. To bridge this gap, the paper introduces the Aging-Aware Autonomous Intelligence (AAAI) framework, which uniquely integrates physics-of-failure–based hardware health estimation directly into the reasoning, planning, and execution loop. Without requiring additional hardware, AAAI enables self-awareness, adaptive inference, and survival-oriented decision-making. By dynamically adjusting task priorities and resource allocation, the approach supports graceful degradation and mission continuity in unreachable or safety-critical environments—such as deep-space exploration and implantable medical devices—thereby significantly enhancing system resilience and operational lifespan.

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Recent publications

Latest Papers

ChaosProbe: A Neurochaotic Lens on Frozen Transformer Input-Embedding Spaces

Aug 03, 2026

This work addresses the challenge of characterizing the input embedding space structure of frozen Transformers without relying on downstream tasks or contextual computations. It introduces ChaosProbe, a novel method that pioneers the application of neural chaos dynamics to embedding analysis: by applying deterministic chaotic trajectory transformations to input embeddings and combining neuronal firing rates with entropy responses, it generates fixed-length structural fingerprints. This approach requires no training or task-specific adaptation, yet effectively reveals macroscopic relationships among embedding spaces. Experiments across four pretrained models and 80 neutral prompts demonstrate that multiple similarity metrics consistently recover both intra-family nearest neighbors and inter-family pairings, confirming the stability and validity of the proposed fingerprints.

0 citationsRead paper

Machines that know they are aging: a framework for hardware-aware autonomous intelligence

Jul 30, 2026

This work addresses the critical challenge that autonomous systems often fail in practice due to hardware aging—such as battery degradation and sensor drift—which causes their actual capabilities to deviate from AI assumptions. To bridge this gap, the paper introduces the Aging-Aware Autonomous Intelligence (AAAI) framework, which uniquely integrates physics-of-failure–based hardware health estimation directly into the reasoning, planning, and execution loop. Without requiring additional hardware, AAAI enables self-awareness, adaptive inference, and survival-oriented decision-making. By dynamically adjusting task priorities and resource allocation, the approach supports graceful degradation and mission continuity in unreachable or safety-critical environments—such as deep-space exploration and implantable medical devices—thereby significantly enhancing system resilience and operational lifespan.

0 citationsRead paper