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Maria Garcia de la Banda

5 accepted papers

2026

MATA: A Trainable Hierarchical Automaton System for Multi-Agent Visual Reasoning

ICLR 2026poster

Recent vision-language models have strong perceptual ability but their implicit reasoning is hard to explain and easily generates hallucinations on complex queries. Compositional methods improve interpretability, but most rely on a single agent or hand-crafted pipeline and cannot decide when to coll…

Cited by 0SourcecodeScholar
2026

NEUSIS: A Compositional Neuro-Symbolic Framework for Autonomous Perception, Reasoning, and Planning in Complex UAV Search Missions

ICRA 2026poster

This paper addresses the problem of autonomous UAV search missions, where a UAV must locate specific Entities of Interest (EOIs) within a time limit, based on brief descriptions in large, hazard-prone environments with keep-out zones. The UAV must perceive, reason, and make decisions with limited an…

2025

NAVER: A Neuro-Symbolic Compositional Automaton for Visual Grounding with Explicit Logic Reasoning

ICCV 2025poster

Visual Grounding (VG) tasks, such as referring expression detection and segmentation tasks are important for linking visual entities to context, especially in complex reasoning tasks that require detailed query interpretation. This paper explores VG beyond basic perception, highlighting challenges f…

2025

NEUSIS: A Compositional Neuro-Symbolic Framework for Autonomous Perception, Reasoning, and Planning in Complex UAV Search Missions

RA-L 2025

This paper addresses the problem of autonomous UAV search missions, where a UAV must locate specific Entities of Interest (EOIs) within a time limit, based on brief descriptions in large, hazard-prone environments with keep-out zones. The UAV must perceive, reason, and make decisions with limited an

Cited by 14SourceScholar
2024

Automatic Core-Guided Reformulation via Constraint Explanation and Condition Learning

AAAI 2024technical

SAT and propagation solvers often underperform for optimisation models whose objective sums many single-variable terms. MaxSAT solvers avoid this by detecting and exploiting cores: subsets of these terms that cannot collectively take their lower bounds. Previous work has shown manual analysis of cor…

Cited by 3SourcePDFScholar