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From the 1 of 8 linked papers with an AI index.

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8 papers

cs.CL2026

Unsure but Certain: Uncovering the Representation-Confidence Gap in Diffusion Language Models

Saurabh Yadav, Badri Narayana Patro, Vijay Srinivas Agneeswaran

Diffusion language models use broad context to create text, suggesting they might handle input noise better than standard models. Testing reveals this is only partially true. Inter…

cs.AI2026

Beyond the Bidirectional Promise: Re-evaluating the Robustness of Diffusion Language Models

Saurabh Yadav, Badri Narayana Patro, Vijay Srinivas Agneeswaran

The paper evaluates how diffusion-based language models handle noisy inputs and adversarial attacks compared to traditional autoregressive models, finding that while they resist ce…

eess.SP2026

NAKUL-Med: Spectral-Graph State Space Models with Dynamics Kernels for Medical Signals

Badri N. Patro, Vijay S. Agneeswaran

State space models (SSMs) achieve linear-time complexity but struggle with multi-channel physiological signals due to three limitations: fixed kernels cannot capture multi-scale te…

cs.CV2026

HAMSA: Scanning-Free Vision State Space Models via SpectralPulseNet

Badri N. Patro, Vijay S. Agneeswaran

Vision State Space Models (SSMs) like Vim, VMamba, and SiMBA rely on complex scanning strategies to adapt sequential SSMs to process 2D images, introducing computational overhead a…

cs.CV2026

Counting Without Numbers and Finding Without Words

Badri Narayana Patro

Every year, 10 million pets enter shelters, separated from their families. Despite desperate searches by both guardians and lost animals, 70% never reunite, not because matches do…

cs.LG2026

LLMOrbit: A Circular Taxonomy of Large Language Models -From Scaling Walls to Agentic AI Systems

Badri N. Patro, Vijay S. Agneeswaran

The field of artificial intelligence has undergone a revolution from foundational Transformer architectures to reasoning-capable systems approaching human-level performance. We pre…