Tag: prompt engineering
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When Does LLM Self-Correction Improve Accuracy?
Explore when iterative self-correction benefits large language models using control-theoretic Markov diagnostics and verify-first interventions.
JTPRO: Optimizing Tool Use in Language Agents
Discover JTPRO, a framework that enhances tool-calling accuracy and efficiency in language agents through joint prompt and schema optimization.
How Enhancing LLM Reasoning Increases Tool Hallucination
Explore how improving reasoning in large language models can amplify tool hallucination and the trade-offs involved in balancing capability and reliability...
Architectural Limits and Design Challenges in Human-LLM Systems
Explore the architectural limits, metacognitive co-option, and design challenges in human-LLM systems to enhance user autonomy and cognitive integrity.
Facial Expression Integration for Empathetic LLM Tutoring
Enhance LLM tutoring with facial-expression-aware prompting to boost empathy and engagement in AI-driven educational tools.