6 papers
Solver-Aware Decompositions for Programming-by-Example: When Dividing Requires Knowing how to Conquer
Janis Zenkner, Tobias Sesterhenn, Tim Grams +1
Decomposition-based Programming-by-example (PBE) scales performance by splitting tasks into subtasks that a learned synthesizer solves: a decomposer predicts intermediate subgoals,…
MCP4IFC: IFC-Based Building Design Using Large Language Models
Bharathi Kannan Nithyanantham, Tobias Sesterhenn, Ashwin Nedungadi +4
Bringing generative AI into the architecture, engineering and construction (AEC) field requires systems that can translate natural language instructions into actions on standardize…
A Compute-Matched Re-Evaluation of TroVE on MATH
Tobias Sesterhenn, Ian Berlot-Attwell, Janis Zenkner +1
Reusing established theorems and formulas is central to mathematical problem solving, serving as essential building blocks for tackling increasingly complex challenges. Recent work…
Beyond Either-Or Reasoning: Transduction and Induction as Cooperative Problem-Solving Paradigms
Janis Zenkner, Tobias Sesterhenn, Christian Bartelt
Traditionally, in Programming-by-example (PBE) the goal is to synthesize a program from a small set of input-output examples. Lately, PBE has gained traction as a few-shot reasonin…
Shedding Light in Task Decomposition in Program Synthesis: The Driving Force of the Synthesizer Model
Janis Zenkner, Tobias Sesterhenn, Christian Bartelt
Task decomposition is a fundamental mechanism in program synthesis, enabling complex problems to be broken down into manageable subtasks. ExeDec, a state-of-the-art program synthes…
AbstractBeam: Enhancing Bottom-Up Program Synthesis using Library Learning
Janis Zenkner, Lukas Dierkes, Tobias Sesterhenn +1
LambdaBeam is a state-of-the-art, execution-guided algorithm for program synthesis that utilizes higher-order functions, lambda functions, and iterative loops within a Domain-Speci…