9 papers
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…
mrCAD: Multimodal Refinement of Computer-aided Designs
William P. McCarthy, Saujas Vaduguru, Karl D. D. Willis +4
A key feature of human collaboration is the ability to iteratively refine the concepts we have communicated. In contrast, while generative AI excels at the \textit{generation} of c…
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…
Amortizing Pragmatic Program Synthesis with Rankings
Yewen Pu, Saujas Vaduguru, Priyan Vaithilingam +2
The usage of Rational Speech Acts (RSA) framework has been successful in building \emph{pragmatic} program synthesizers that return programs which, in addition to being logically c…
Generating Pragmatic Examples to Train Neural Program Synthesizers
Saujas Vaduguru, Daniel Fried, Yewen Pu
Programming-by-example is the task of synthesizing a program that is consistent with a set of user-provided input-output examples. As examples are often an under-specification of o…
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…
Amortizing Pragmatic Program Synthesis with Rankings
Yewen Pu, Saujas Vaduguru, Priyan Vaithilingam +2
In program synthesis, an intelligent system takes in a set of user-generated examples and returns a program that is logically consistent with these examples. The usage of Rational…
Efficient Pragmatic Program Synthesis with Informative Specifications
Saujas Vaduguru, Kevin Ellis, Yewen Pu
Providing examples is one of the most common way for end-users to interact with program synthesizers. However, program synthesis systems assume that examples consistent with the pr…
Sample-efficient Linguistic Generalizations through Program Synthesis: Experiments with Phonology Problems
Saujas Vaduguru, Aalok Sathe, Monojit Choudhury +1
Neural models excel at extracting statistical patterns from large amounts of data, but struggle to learn patterns or reason about language from only a few examples. In this paper,…