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M. Dredze

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#artificial intelligence Preprint Oct 2026

Accurate but Not Humble: Evaluating Epistemic Humility in LLM Agents under Knowledge Conflict

When retrieved evidence contradicts an agent's prior beliefs, does it revise its answer, acknowledge uncertainty, or persist with an incorrect conclusion? Existing evaluations of agentic systems focus primarily on task success, offering limited insight into how agents handle such conflicts. We propose to evaluate agent...

Kaiser Sun, Bernal Jiménez Gutiérrez, Hong-Jun Liu et al. · 0 citations
Book Open access Aug 2026

Information Satisfaction: A Reader-Centered Axis for Summarization Evaluation

An expert human evaluation is conducted, measuring summary preferences based on information satisfaction given a specific person’s background and use case, and finds that both traditional and LLM-based metrics are insufficient measures of information satisfaction and agree poorly with human judgment.

Isabel Cachola, W. Walden, Reno Kriz et al. · 0 citations
#natural language process... Preprint Sep 2026

On the Behavioral Traits of LLM Agents

This work proposes A-B-D to infer traits bottom-up from behavioral data (B-data), namely how agents act on their environment and communicate with users, as recorded in existing trajectories, and offers a new lens for understanding AI personality.

Hao-Kai Zhao, Jie Gao, Yunze Xiao et al. · 0 citations
#natural language process... Preprint Sep 2026

Where Does Retrieval-Based Open-Ended Evaluation Fail? Automatic Taxonomy Induction from Long-Form Medical Answer Factuality Verification

Analysis reveals that scaling model size, adding reasoning effort, expanding to authoritative web sources, and applying medical fine-tuning do not resolve these failure modes, demonstrating that they represent fundamental limitations of the retrieve-then-verify paradigm in open-ended medical settings rather than artifa...

He-Yuan Huang, Ji Dai, Alexandra DeLucia et al. · 0 citations
Open access Jul 2026

Evaluating Healthcare Provider and Artificial Intelligence Chatbot Responses to Patient Messages from a Health System Using the CREATE TRUST Framework.

Integration of artificial intelligence chatbots into healthcare requires rigorous, patient-centered evaluation. This study implements the CREATE TRUST framework-a novel tool evaluating both clinical substance and communication style-to compare responses from healthcare providers (HCPs) and two AI chatbots (GPT-4, Mixtr...

Matthew R. Allen, V. Tiyyala, Armaan S Johal et al. · 0 citations
Review Jul 2026

Generative AI in the Care of Older Adults: A Position Statement From the American Geriatrics Society.

GenAI should augment, not replace, clinical judgment and relational care, and responsible use in geriatrics requires transparency, clinician-in-the-loop oversight, validation in older adult populations using age-relevant outcomes, and governance safeguards to protect dignity, safety, and equity.

A. Bharija, Ariba Khan, J. Pavon et al. · 1 citation

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