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20242026
most citedAccounting for Sycophancy in Language Model Uncertainty Estimation

1 citations · 3 across the 12 of their papers we have counts for

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cs.CL2024★ 1 cited

Accounting for Sycophancy in Language Model Uncertainty Estimation

Anthony Sicilia, Mert Inan, Malihe Alikhani

Effective human-machine collaboration requires machine learning models to externalize uncertainty, so users can reflect and intervene when necessary. For language models, these rep…

cs.CL2024

Learning Multimodal Cues of Children's Uncertainty

Qi Cheng, Mert İnan, Rahma Mbarki +6

Understanding uncertainty plays a critical role in achieving common ground (Clark et al.,1983). This is especially important for multimodal AI systems that collaborate with users t…

cs.CL2024

Generating Signed Language Instructions in Large-Scale Dialogue Systems

Mert İnan, Katherine Atwell, Anthony Sicilia +2

We introduce a goal-oriented conversational AI system enhanced with American Sign Language (ASL) instructions, presenting the first implementation of such a system on a worldwide m…

cs.CL2024

Dialogue with Robots: Proposals for Broadening Participation and Research in the SLIVAR Community

Casey Kennington, Malihe Alikhani, Heather Pon-Barry +20

The ability to interact with machines using natural human language is becoming not just commonplace, but expected. The next step is not just text interfaces, but speech interfaces…

cs.CL2024★ 1 cited

Learning to Generate Context-Sensitive Backchannel Smiles for Embodied AI Agents with Applications in Mental Health Dialogues

Maneesh Bilalpur, Mert Inan, Dorsa Zeinali +2

Addressing the critical shortage of mental health resources for effective screening, diagnosis, and treatment remains a significant challenge. This scarcity underscores the need fo…