Proposes agentic framework-based reproduction with a slot-binding interface to turn 16 PHM papers into standardized, assumption-aware benchmark implementations.
Argos: Agentic time-series anomaly detection with autonomous rule generation via large language models, 2025
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A survey proposing a taxonomy of Injective, Bridging, and Internal Alignment paradigms to evolve TSA into user-driven Time Series Question Answering with LLMs.
An integrated framework using autoencoders, deep reinforcement learning, and LLMs automates risk-based prioritization and contextual analysis of suspicious network traffic within Splunk SOC environments.
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From paper to benchmark: agentic, framework-based reproduction of under-specified methods in machine health intelligence
Proposes agentic framework-based reproduction with a slot-binding interface to turn 16 PHM papers into standardized, assumption-aware benchmark implementations.
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From Time Series Analysis to Question Answering: A Survey in the LLM Era
A survey proposing a taxonomy of Injective, Bridging, and Internal Alignment paradigms to evolve TSA into user-driven Time Series Question Answering with LLMs.
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Policy-Guided Threat Hunting: An LLM enabled Framework with Splunk SOC Triage
An integrated framework using autoencoders, deep reinforcement learning, and LLMs automates risk-based prioritization and contextual analysis of suspicious network traffic within Splunk SOC environments.