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20232025
most citedAsking More Informative Questions for Grounded Retrieval

1 citations · 1 across the 11 of their papers we have counts for

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cs.CL2025

Success and Cost Elicit Convention Formation for Efficient Communication

Saujas Vaduguru, Yilun Hua, Yoav Artzi +1

Humans leverage shared conversational context to become increasingly successful and efficient at communicating over time. One manifestation of this is the formation of ad hoc lingu…

cs.CL2025

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…

cs.CL2025

Analyzing Information Sharing and Coordination in Multi-Agent Planning

Tianyue Ou, Saujas Vaduguru, Daniel Fried

Multi-agent systems (MASs) have pushed the boundaries of large language model (LLM) agents in domains such as web research and software engineering. However, long-horizon, multi-co…

cs.CL2024

Is the Pope Catholic? Yes, the Pope is Catholic. Generative Evaluation of Non-Literal Intent Resolution in LLMs

Akhila Yerukola, Saujas Vaduguru, Daniel Fried +1

Humans often express their communicative intents indirectly or non-literally, which requires their interlocutors -- human or AI -- to understand beyond the literal meaning of words…

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.CL2023★ 1 cited

Asking More Informative Questions for Grounded Retrieval

Sedrick Keh, Justin T. Chiu, Daniel Fried

When a model is trying to gather information in an interactive setting, it benefits from asking informative questions. However, in the case of a grounded multi-turn image identific…

cs.CL2023

Symbolic Planning and Code Generation for Grounded Dialogue

Justin T. Chiu, Wenting Zhao, Derek Chen +3

Large language models (LLMs) excel at processing and generating both text and code. However, LLMs have had limited applicability in grounded task-oriented dialogue as they are diff…