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20242026
most citedTRIP-PAL: Travel Planning with Guarantees by Combining Large Language Models and Automated Planners

8 citations · 9 across the 11 of their papers we have counts for

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Showing 2026Show all

5 papers · 1 filter

cs.AI2026

Cycle-Consistent Neural Explanation of Formal Verification Certificates

Andoni Rodriguez, Alberto Pozanco, Daniel Borrajo

Formal verification produces machine-checkable certificates that attest to the satisfaction or violation of temporal properties, yet these certificates remain opaque to non-special…

cs.CR2026

Is Your Agent Playing Dead? Deployed LLM Agents Exhibit Constraint-Evasive Fabrication and Thanatosis

Andoni Rodríguez, Alberto Pozanco, Daniel Borrajo

This paper presents and characterizes a spectrum of previously unreported behaviours we term Constraint-Evasive Fabrication (CEF): when an LLM agent operates under irreconcilable c…

cs.AI2026

Counterfactual Reasoning in Automated Planning

Alberto Pozanco, Daniel Borrajo, Manuela Veloso

Automated planning traditionally assumes that all aspects of a planning task (initial state, goals, and available actions) are fully specified in advance, an approach well-suited t…

cs.AI2026

Planning Task Shielding: Detecting and Repairing Flaws in Planning Tasks through Turning them Unsolvable

Alberto Pozanco, Pietro Totis, Marianela Morales +1

Most research in planning focuses on generating a plan to achieve a desired set of goals. However, a goal specification can also be used to encode a property that should never hold…

cs.AI2026

Semantic Partial Grounding via LLMs

Giuseppe Canonaco, Alberto Pozanco, Daniel Borrajo

Grounding is a critical step in classical planning, yet it often becomes a computational bottleneck due to the exponential growth in grounded actions and atoms as task size increas…