9 papers
Calibration Drift Under Reasoning: How Chain-of-Thought Budgets Induce Overconfidence in Large Language Models
Prakul Sunil Hiremath, Harshit R. Hiremath
The ability of large language models (LLMs) to express calibrated uncertainty is important for safe deployment. Chain-of-thought (CoT) reasoning is widely used to improve accuracy…
Early Detection of Latent Microstructure Regimes in Limit Order Books
Prakul Sunil Hiremath, Vruksha Arun Hiremath
Limit order books can transition rapidly from stable to stressed conditions, yet standard early-warning signals such as order flow imbalance and short-term volatility are inherentl…
Sensitivity Uncertainty Alignment in Large Language Models
Prakul Sunil Hiremath, Harshit R. Hiremath
We propose Sensitivity-Uncertainty Alignment (SUA), a framework for analyzing failures of large language models under adversarial and ambiguous inputs. We argue that adversarial se…
Photonic AI: A Hybrid Diffractive Holographic Neural System for Passive Optical Real-Time Image Classification
Prakul Sunil Hiremath
Edge intelligence is constrained by the energy and latency costs of shuttling data through electronic memory hierarchies. Optical systems offer a fundamentally different computatio…
Regret-Aware Policy Optimization: Environment-Level Memory for Replay Suppression under Delayed Harm
Prakul Sunil Hiremath
Safety in reinforcement learning (RL) is typically enforced through objective shaping while keeping environment dynamics stationary with respect to observable state-action pairs. U…
GIRL: Generative Imagination Reinforcement Learning via Information-Theoretic Hallucination Control
Prakul Sunil Hiremath
Model-based reinforcement learning (MBRL) improves sample efficiency by optimizing policies inside imagined rollouts, but long-horizon planning degrades when model errors compound…
The Hiremath Early Detection (HED) Score: A Measure-Theoretic Evaluation Standard for Temporal Intelligence
Prakul Sunil Hiremath
We introduce the Hiremath Early Detection (HED) Score, a principled, measure-theoretic evaluation criterion for quantifying the time-value of information in systems operating over…
Learning Nonlinear Regime Transitions via Semi-Parametric State-Space Models
Prakul Sunil Hiremath
We develop a semi-parametric state-space model for time-series data with latent regime transitions. Classical Markov-switching models use fixed parametric transition functions, suc…
PARD-SSM: Probabilistic Cyber-Attack Regime Detection via Variational Switching State-Space Models
Prakul Sunil Hiremath, PeerAhammad M Bagawan, Sahil Bhekane
Modern adversarial campaigns unfold as sequences of behavioural phases - Reconnaissance, Lateral Movement, Intrusion, and Exfiltration - each often indistinguishable from legitimat…