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This paper introduces a production enterprise analytics system that inverts the interaction model from question-first to analyst-first through domain-expert skills and knowledge compilation, enabling proactive analytics with verified metrics and suggested questions.
This feasibility study compares a standalone LLM with a pre-specified agentic pipeline for explaining ICU mortality predictions, finding that the agentic approach improves guideline grounding and patient-specific detail but requires attribution-based checks for safety.
HarnessEval-W is an agentic pipeline that automates human evaluation for world models by generating transparent evidence trees instead of opaque scores, enhancing trust and inspection in benchmarking.
A new state-of-the-art agentic pipeline has been introduced for easy music video creation, leveraging AI to streamline the process.
The author shares their experience building a local agentic pipeline on a budget, concluding that rigid Python code outperforms flexible AI agents for reliability and resource usage.
A self-optimizing agentic pipeline that improves benchmark performance from ~30% to ~90% on TerminalBench, and can be extended to everyday chats by logging interactions, reflecting with a local model, and injecting lessons into future system prompts.