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From the 1 of 56 linked papers with an AI index.

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20242026
most citedOptimal Program Synthesis via Abstract Interpretation

6 citations · 17 across the 26 of their papers we have counts for

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cs.PL2026

Choose, Don't Label: Multiple-Choice Query Synthesis for Program Disambiguation

Celeste Barnaby, Danny Ding, Osbert Bastani +1

High-level specifications of code are inherently ambiguous, and prior systems have explored interactive techniques to help users clarify their intent and resolve such ambiguities.…

cs.PL20265 cited

Synthesizing Trajectory Queries from Examples

Stephen Mell, Favyen Bastani, Steve Zdancewic +1

Data scientists often need to write programs to process predictions of machine learning models, such as object detections and trajectories in video data. However, writing such quer…

cs.PL20266 cited

Optimal Program Synthesis via Abstract Interpretation

Stephen Mell, Steve Zdancewic, Osbert Bastani

We consider the problem of synthesizing programs with numerical constants that optimize a quantitative objective, such as accuracy, over a set of input-output examples. We propose…

cs.PL20262 cited

Opportunistically Parallel Lambda Calculus

Stephen Mell, Konstantinos Kallas, Steve Zdancewic +1

Scripting languages are widely used to compose external calls such as native libraries and network services. In such scripts, execution time is often dominated by waiting for these…

cs.PL2025

Active Learning for Neurosymbolic Program Synthesis

Celeste Barnaby, Qiaochu Chen, Ramya Ramalingam +2

The goal of active learning for program synthesis is to synthesize the desired program by asking targeted questions that minimize user interaction. While prior work has explored ac…

cs.PL2025

Quasar: A Programming Language Specialized for LLM Code Actions

Stephen Mell, Botong Zhang, David Mell +6

Large language models (LLMs) often call external tools to solve tasks. One effective strategy is for LLMs to write code, enabling them to use complex control flow such as condition…