Papers by Rithwik Kerur

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Challenge:	Large language models have demonstrated impressive capabilities across diverse tasks . however, their ability to generate valid graph structures remains underexplored .
Approach:	They evaluate large language models on five specialized graph generation tasks . they also test the models using 3 different prompt types: direct, iterative feedback, and program-augmented.
Outcome:	The proposed models solve twice as many tasks as general-purpose models, compared to their general-usage peers.