4 citations · 27 across the 29 of their papers we have counts for
29 papers · 1 filter
Soft Symbol Grounding for Prototypical Concepts
Marcos Galván-López, Nijesh Upreti, Hiram Calvo +2
Neuro-symbolic models are usually trained with supervision only on final labels, leaving the intermediate concepts unobserved. Since many concept assignments are consistent with a…
Generate in the Chart, Not on the Boundary: Function-Symbol Grounding for Hard Constraints in LTN-GANs
Nijesh Upreti, Vaishak Belle
Logic Tensor Network-Enhanced Generative Adversarial Networks (LTN-GANs) inject background knowledge by grounding each logical axiom as a predicate and training the generator to ra…
DeepSWIP: Quotient-WMC Counterfactuals for Neural Probabilistic Logic Programs
Saimun Habib, Vaishak Belle, Fengxiang He
Neurosymbolic systems such as DeepProbLog combine neural perception with probabilistic logic, but standard inference is associational. Counterfactual reasoning additionally require…
Tractable Hierarchical Control of Autoregressive Language Models
Max Scribner, Antonio Vergari, Vaishak Belle
Constraining the generation of autoregressive large language models (LLMs) is an important component of integrating language models into formal systems. In the generation of code a…
Neuro-symbolic Weak Supervision: Theory and Semantics
Nijesh Upreti, Vaishak Belle
Weak supervision enables machine learning models to learn from limited or noisy labels, but it introduces challenges in reliability and semantic clarity, particularly in multi-inst…
A Counterfactual Cause in Situation Calculus
Daxin Liu, Vaishak Belle
Perhaps the most popular modern formulation of actual causality is the HP account by Halpern and Pearl. Recent advancement has focused on extension of HP account to lift its limite…