159 citations · 235 across the 19 of their papers we have counts for
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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…
Learning a Hierarchical Planner from Humans in Multiple Generations
Leonardo Hernandez Cano, Yewen Pu, Robert D. Hawkins +2
A typical way in which a machine acquires knowledge from humans is by programming. Compared to learning from demonstrations or experiences, programmatic learning allows the machine…
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…
The Usability of Pragmatic Communication in Regular Expression Synthesis
Priyan Vaithilingam, Yewen Pu, Elena L. Glassman
Programming-by-example (PBE) systems aim to alleviate the burden of programming. However, user-specified examples are often ambiguous, leaving multiple programs to satisfy the spec…
ANPL: Towards Natural Programming with Interactive Decomposition
Di Huang, Ziyuan Nan, Xing Hu +8
Though LLMs are capable of generating plausible programs, it's challenging to interact with the LLMs further to revise the program, especially if the user's specific requirements a…