TimeSeriesExamAgent combines templates and LLM agents to generate scalable time series reasoning benchmarks, demonstrating that current LLMs have limited performance on both abstract and domain-specific tasks.
Ecg-expert-qa: A benchmark for evaluating medical large language models in heart disease diagnosis
3 Pith papers cite this work. Polarity classification is still indexing.
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VitalAgent adds longitudinal memory and tool-augmented reasoning to an agent for reactive QA and proactive monitoring on ECG/PPG streams, reporting >25% gains over baselines on a new 1,862-pair + 90-hour benchmark.
CARE-ECG unifies ECG representation learning, causal graph-based diagnosis, and counterfactual assessment in an agentic LLM pipeline to improve accuracy and explanation faithfulness.
citing papers explorer
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TimeSeriesExamAgent: Creating Time Series Reasoning Benchmarks at Scale
TimeSeriesExamAgent combines templates and LLM agents to generate scalable time series reasoning benchmarks, demonstrating that current LLMs have limited performance on both abstract and domain-specific tasks.
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VitalAgent: A Tool-Augmented Agent for Reactive and Proactive Physiological Monitoring over Wearable Health Data
VitalAgent adds longitudinal memory and tool-augmented reasoning to an agent for reactive QA and proactive monitoring on ECG/PPG streams, reporting >25% gains over baselines on a new 1,862-pair + 90-hour benchmark.
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CARE-ECG: Causal Agent-based Reasoning for Explainable and Counterfactual ECG Interpretation
CARE-ECG unifies ECG representation learning, causal graph-based diagnosis, and counterfactual assessment in an agentic LLM pipeline to improve accuracy and explanation faithfulness.