2 citations · 3 across the 6 of their papers we have counts for
7 papers
Self-Play Search Distillation for Large Language Model Reasoning
Lorenzo Molfetta, Wai-Chung Kwan, Giacomo Frisoni +5
Improving reasoning abilities in Large Language Models (LLMs) requires high-quality data that exposes difficult decisions, competing alternatives, and their consequences. Data scar…
Sycophants in the Courtroom: Are LLMs Fragile to Juridical Authority and Evolving Legal Standards?
Lorenzo Molfetta, Alessio Cocchieri, Luca Ragazzi +3
In medicine, claims remain valid when supported by empirical evidence grounded in stable biological reality. In law, by contrast, truth is contingent, defined by jurisdiction, temp…
PORTS: Preference-Optimized Retrievers for Tool Selection with Large Language Models
Lorenzo Molfetta, Giacomo Frisoni, Nicolò Monaldini +1
Integrating external tools with Large Language Models (LLMs) has emerged as a promising paradigm for accomplishing complex tasks. Since LLMs still struggle to effectively manage la…
Graph-of-Mark: Promote Spatial Reasoning in Multimodal Language Models with Graph-Based Visual Prompting
Giacomo Frisoni, Lorenzo Molfetta, Mattia Buzzoni +1
Recent advances in training-free visual prompting, such as Set-of-Mark, have emerged as a promising direction for enhancing the grounding capabilities of multimodal language models…
Neuro-Symbolic Artificial Intelligence: A Task-Directed Survey in the Black-Box Models Era
Giovanni Pio Delvecchio, Lorenzo Molfetta, Gianluca Moro
The integration of symbolic computing with neural networks has intrigued researchers since the first theorizations of Artificial intelligence (AI). The ability of Neuro-Symbolic (N…
FEAST: Retrieval-Augmented Multi-Hierarchical Food Classification for the FoodEx2 System
Lorenzo Molfetta, Alessio Cocchieri, Stefano Fantazzini +3
Hierarchical text classification (HTC) and extreme multi-label classification (XML) tasks face compounded challenges from complex label interdependencies, data sparsity, and extrem…
Mixture of Masters: Sparse Chess Language Models with Player Routing
Giacomo Frisoni, Lorenzo Molfetta, Davide Freddi +1
Modern chess language models are dense transformers trained on millions of games played by thousands of high-rated individuals. However, these monolithic networks tend to collapse…