# CAREER: Shaping Embodied Intelligence Through Language-Guided Introspection

> **NSF 01002627DB NSF RESEARCH & RELATED ACTIVIT** · University of Illinois at Urbana-Champaign (IL) · $600,000

## Abstract

Artificial intelligence (AI) systems are increasingly deployed in real-world physical environments to assist in factories, hospitals, warehouses, and other dynamic settings, where safety, reliability, and effective human-AI collaboration are essential. Yet current AI agents still fail in ways that are difficult to detect, explain, and correct. They often misinterpret instructions, fail to recognize when their own reasoning is flawed, struggle to recover from errors, and persist in unsafe or ineffective behavior. This project addresses these limitations by developing a new generation of AI agents that can monitor their reasoning, draw on past experience to evaluate and explain their decisions, and adapt their internal understanding of the world based on corrective feedback. Such self-regulating AI agents will be more reliable, more transparent, and safer to deploy in complex physical environments. Beyond advancing the science of AI, this project translates research into learning experiences, student mentoring, interactive demonstrations, and community engagement activities that expand AI literacy and strengthen AI workforce readiness.

This project develops a unified framework for embodied intelligence in which language serves as a cognitive mechanism for self-monitoring, self-evaluation, and self-regulation. First, the research develops introspective reasoning methods that enable agents to detect, attribute, and mitigate perceptual and reasoning failures during task execution. Second, the research develops reflective explanation mechanisms grounded in episodic memory, enabling agents to retrieve relevant past experiences and their associated reasoning to assess ongoing decisions and proactively seek targeted human feedback. Third, the research develops language-guided self-organizing world models that enable agents to revise their internal beliefs and dynamically adapt decision-making in response to evolving feedback and introspective diagnostics. The project will

## Key facts

- **NSF award ID:** 2542328
- **Awardee organization:** University of Illinois at Urbana-Champaign (IL)
- **SAM.gov UEI:** Y8CWNJRCNN91
- **PI:** Ismini Lourentzou
- **Primary program:** 01002627DB NSF RESEARCH & RELATED ACTIVIT
- **All programs:** Artificial Intelligence (AI), CAREER-Faculty Erly Career Dev, ROBUST INTELLIGENCE
- **Estimated total:** $600,000
- **Funds obligated:** $356,787
- **Transaction type:** Continuing Grant
- **Period:** 07/15/2026 → 06/30/2031

## Primary source

NSF Award Search: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2542328

## Citation

> US National Science Foundation, Award 2542328, CAREER: Shaping Embodied Intelligence Through Language-Guided Introspection. Retrieved via AI Analytics 2026-07-04 from https://api.ai-analytics.org/grant/nsf/2542328. Licensed CC0.

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