1 citations · 3 across the 12 of their papers we have counts for
12 papers
From Task Success to Productive Success: Evaluating Human-AI Collaboration by Quality and Cost
Saki Imai, Mert İnan, Malihe Alikhani
AI productivity is often measured by task completion time, economic value, or improvements in outcome quality. However, these measures usually treat collaboration as a black box wh…
DiscoSign: Discourse-Aware Text to Sign Language Gloss Translation
Vasileios Baltatzis, Mert Inan, Connor Gillis +4
Sign language processing systems have traditionally operated at the sentence level, ignoring critical discourse phenomena fundamental to sign language comprehension. We introduce D…
Identifying & Interactively Refining Ambiguous User Goals for Data Visualization Code Generation
Mert İnan, Anthony Sicilia, Alex Xie +3
Establishing shared goals is a fundamental step in human-AI communication. However, ambiguities can lead to outputs that seem correct but fail to reflect the speaker's intent. In t…
How Pragmatics Shape Articulation: A Computational Case Study in STEM ASL Discourse
Saki Imai, Lee Kezar, Laurel Aichler +5
Most state-of-the-art sign language models are trained on interpreter or isolated vocabulary data, which overlooks the variability that characterizes natural dialogue. However, hum…
Measuring How (Not Just Whether) VLMs Build Common Ground
Saki Imai, Mert İnan, Anthony Sicilia +1
Large vision language models (VLMs) increasingly claim reasoning skills, yet current benchmarks evaluate them in single-turn or question answering settings. However, grounding is a…
SiLVERScore: Semantically-Aware Embeddings for Sign Language Generation Evaluation
Saki Imai, Mert İnan, Anthony Sicilia +1
Evaluating sign language generation is often done through back-translation, where generated signs are first recognized back to text and then compared to a reference using text-base…
Better Slow than Sorry: Introducing Positive Friction for Reliable Dialogue Systems
Mert İnan, Anthony Sicilia, Suvodip Dey +6
While theories of discourse and cognitive science have long recognized the value of unhurried pacing, recent dialogue research tends to minimize friction in conversational systems.…
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…
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…
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…
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…
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…