12 papers
Two-atom Dicke model with atom-atom interaction
Lin Jiao, Han Pu
Interactions among emitters provide a powerful means of controlling collective light--matter phenomena, yet their role in superradiant criticality has not been thoroughly investiga…
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…
Learning Tractable Distributions Of Language Model Continuations
Gwen Yidou-Weng, Ian Li, Anji Liu +4
Controlled generation imposes sequence-level constraints (syntax, style, safety) that depend on future tokens, making exact conditioning of an autoregressive LM intractable. Tracta…
How to Marginalize in Causal Structure Learning?
William Zhao, Guy Van den Broeck, Benjie Wang
Bayesian networks (BNs) are a widely used class of probabilistic graphical models employed in numerous application domains. However, inferring the network's graphical structure fro…