1 citations · 1 across the 8 of their papers we have counts for
9 papers
Lost in Aggregation: How Benchmarks Overlook Irreplaceable Model Strengths
Andrej Tschalzev, Stefan Lüdtke, Heiner Stuckenschmidt +1
Tabular machine learning benchmarks typically summarize performance by averaging scores, ranks, or pairwise wins across datasets. Such aggregates are useful for selecting robust de…
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,…
Explaining Tabular Foundation Model Differences Through Meta-Features
Markus Herre, Andrej Tschalzev, Sascha Marton +1
With the rise of tabular foundation models alongside traditional models still performing well on many tasks, choosing the right model for a tabular dataset remains difficult. We in…
BIM-Edit: Benchmarking Large Language Models for IFC-Based Building Information Modeling
Bharathi Kannan Nithyanantham, Clemens Kujat, Tobias Sesterhenn +5
Large language models (LLMs) are increasingly applied to computer-aided design (CAD) to generate design artifacts from textual instructions. In engineering practice, this requires…
TabPrep: Closing the Feature Engineering Gap in Tabular Benchmarks
Andrej Tschalzev, Nick Erickson, Yuyang Wang +4
Progress in tabular machine learning has largely focused on increasingly sophisticated model architectures. At the same time, feature engineering remains a critical yet underexplor…
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…