4 citations · 10 across the 19 of their papers we have counts for
3 papers · 2 filters
Adaptive LLM-Symbolic Reasoning via Dynamic Logical Solver Composition
Lei Xu, Pierre Beckmann, Marco Valentino +1
Neuro-symbolic NLP methods aim to leverage the complementary strengths of large language models and formal logical solvers. However, current approaches are mostly static in nature,…
Faithful and Robust LLM-Driven Theorem Proving for NLI Explanations
Xin Quan, Marco Valentino, Louise A. Dennis +1
Natural language explanations play a fundamental role in Natural Language Inference (NLI) by revealing how premises logically entail hypotheses. Recent work has shown that the inte…
Improving Chain-of-Thought Reasoning via Quasi-Symbolic Abstractions
Leonardo Ranaldi, Marco Valentino, Andrè Freitas
Chain-of-Though (CoT) represents a common strategy for reasoning in Large Language Models (LLMs) by decomposing complex tasks into intermediate inference steps. However, explanatio…