1 citations · 1 across the 15 of their papers we have counts for
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Meta-Ctrl: Guaranteed Plan Generation by Decoupling Syntactic and Semantic Constraints
Gwen Yidou-Weng, Edward Sun, Tianyi Ma +5
LLMs generate fluent plans for robots but routinely violate the syntactic and se8mantic constraints they must satisfy to execute, and existing remedies trade formal guarantees agai…
Interpretable Causal Discovery via Causal-Effect Constraints
Cixuan Zhang, Guy Van den Broeck, Benjie Wang
Causal discovery aims to uncover the underlying causal relationships given data generated from a system. The goal, however, is not merely to predict causal edges given data, but al…
The RAIL Principles for Neurosymbolic AI: Reasoning, Assurances, Interfacing and Learning
Agnese Chiatti, Michael Cochez, Cristina Cornelio +14
Neurosymbolic AI systems that integrate machine learning and symbolic reasoning are rapidly gaining attention. They complement the data-intensive statistical approaches of neural n…
ExplainFuzz: Explainable and Constraint-Conditioned Test Generation with Probabilistic Circuits
Annaëlle Baiget, Jaron Maene, Seongmin Lee +3
Understanding and explaining the structure of generated test inputs is essential for effective software testing and debugging. Existing approaches--including grammar-based fuzzers,…
Breaking the Factorization Barrier in Diffusion Language Models
Ian Li, Zilei Shao, Benjie Wang +3
Diffusion language models theoretically allow for efficient parallel generation but are practically hindered by the ``factorization barrier'': the assumption that simultaneously pr…