10 citations · 71 across the 49 of their papers we have counts for
7 papers · 1 filter
Agentic Cognitive Depth: Operational Criteria for Evaluating LLM Agents
Nijesh Upreti, Chris Sypherd, Vaishak Belle
Agentic large language model (LLM) systems are commonly implemented as an LLM in a loop with Planning, Memory, Tools, and Control Flow. This application-focused view connects agent…
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…
Vancomycert: A Certified Neuro-Symbolic Drug Delivery System (Case Study)
Alistair Sirman, Fleur Conway, Jessica Ciupa +7
Neural network controllers for autonomous decision-making are well-established in cyber-physical systems, yet their deployment in safety-critical healthcare settings remains largel…
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…
Used Car Salesbots? Honesty and Credulity of LLMs as Bargaining Agents under Partial Information
Antonio Valerio Miceli-Barone, Vaishak Belle, Shay B. Cohen
In this work we study agents in simulated bargaining scenarios, where a buyer and a seller communicate through a text channel and attempt to negotiate mutually beneficial trades, u…