1 citations · 1 across the 7 of their papers we have counts for
8 papers
Metro-WM: Long-Horizon Latent Planning with Realisable Sub-Goals
Royson Lee, Fady Rezk, Titouan Parcollet +2
Model-predictive control with Joint-Embedding Predictive Architectures (JEPAs) provides a strong zero-shot goal-reaching planner, but it is only effective over short planning horiz…
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…
Query Symbolically or Retrieve Semantically? A Dataset and Method for Semi-Structured Question Answering
Mateusz Czyżnikiewicz, Ryszard Tuora, Adam Kozakiewicz +6
Retrieval-Augmented Generation (RAG) systems for question answering typically retrieve evidence by semantic similarity between the query and document chunks. While effective for un…
Better Later Than Sooner: Neuro-Symbolic Knowledge Graph Construction via Ontology-grounded Post-extraction Correction
Lorenzo Loconte, Timothy Hospedales, Cristina Cornelio
Question answering (QA) is a core challenge in AI, particularly for complex queries requiring multi-hop reasoning across documents, or symbolic operations like aggregation or exhau…
The Need for Verification in AI-Driven Scientific Discovery
Cristina Cornelio, Takuya Ito, Ryan Cory-Wright +2
Artificial intelligence (AI) is transforming the practice of science. Machine learning and large language models (LLMs) can generate hypotheses at a scale and speed far exceeding t…
Error Detection and Correction for Interpretable Mathematics in Large Language Models
Yijin Yang, Cristina Cornelio, Mario Leiva +1
Recent large language models (LLMs) have demonstrated the ability to perform explicit multi-step reasoning such as chain-of-thought prompting. However, their intermediate steps oft…
Hierarchical Planning for Complex Tasks with Knowledge Graph-RAG and Symbolic Verification
Cristina Cornelio, Flavio Petruzzellis, Pietro Lio
Large Language Models (LLMs) have shown promise as robotic planners but often struggle with long-horizon and complex tasks, especially in specialized environments requiring externa…
Recover: A Neuro-Symbolic Framework for Failure Detection and Recovery
Cristina Cornelio, Mohammed Diab
Recognizing failures during task execution and implementing recovery procedures is challenging in robotics. Traditional approaches rely on the availability of extensive data or a t…