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Bilge Mutlu

4 papers hereh-index 694 citations16 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • last author4

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.RO2
  • cs.AI1
  • cs.HC1
same name
  • Bilge Mutlu — 21 papers
  • Bilge Mutlu — 16 papers, h 57
  • Bilge Mutlu — 6 papers, h 4
  • Bilge Mutlu — 5 papers, h 5
  • Bilge Mutlu — 3 papers, h 4
  • Bilge Mutlu — 2 papers, h 2

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20242026
most citedUnderstanding Generative AI in Robot Logic Parametrization

1 citations · 1 across the 3 of their papers we have counts for

collaborators

4 papers

cs.AI2026

U-Define: Designing User Workflows for Hard and Soft Constraints in LLM-Based Planning

Christine P Lee, Xinyu Jessica Wang, Aws Albarghouthi +2

LLMs are increasingly used for end-user task planning, yet their black-box nature limits users' ability to ensure reliability and control. While recent systems incorporate verifica…

cs.RO2026

RoboCritics: Enabling Reliable End-to-End LLM Robot Programming through Expert-Informed Critics

Callie Y. Kim, Nathan Thomas White, Evan He +2

End-user robot programming grants users the flexibility to re-task robots in situ, yet it remains challenging for novices due to the need for specialized robotics knowledge. Large…

cs.HC2025

VeriPlan: Integrating Formal Verification and LLMs into End-User Planning

Christine Lee, David Porfirio, Xinyu Jessica Wang +2

Automated planning is traditionally the domain of experts, utilized in fields like manufacturing and healthcare with the aid of expert planning tools. Recent advancements in LLMs h…

cs.RO2024★ 1 cited

Understanding Generative AI in Robot Logic Parametrization

Yuna Hwang, Arissa J. Sato, Pragathi Praveena +2

Leveraging generative AI (for example, Large Language Models) for language understanding within robotics opens up possibilities for LLM-driven robot end-user development (EUD). Des…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.