most citedHumanity's Last Exam

18 citations · 18 across the 5 of their papers we have counts for

collaborators

7 papers

cs.LG2026

Steering Vectors are an Adversarial Attack Surface

Abzal Aidakhmetov, Donato Crisostomi, Tommaso Mencattini +3

Activation steering has become a popular way to control Large Language Model (LLM) behavior without fine-tuning. Since the technique is plug-and-play, users share datasets and prec…

cs.LG2026

Model Merging: Foundations and Algorithms

Donato Crisostomi

Modern deep learning usually treats models as separate artifacts: trained independently, specialized for particular purposes, and replaced when improved versions appear. This thesi…

cs.CL2026

Multi-objective Evolutionary Merging Enables Efficient Reasoning Models

Mario Iacobelli, Adrian Robert Minut, Tommaso Mencattini +5

Reasoning models achieve strong performance on complex problems by leveraging long chains of thought, but this deliberate reasoning incurs substantial inference-time cost. The Long…

cs.LG2026

MASS: MoErging through Adaptive Subspace Selection

Donato Crisostomi, Alessandro Zirilli, Antonio Andrea Gargiulo +5

Model merging has recently emerged as a lightweight alternative to ensembling, combining multiple fine-tuned models into a single set of parameters with no additional training over…

cs.LG202618 cited

Humanity's Last Exam

Long Phan, Alice Gatti, Ziwen Han +1144

Benchmarks are important tools for tracking the rapid advancements in large language model (LLM) capabilities. However, benchmarks are not keeping pace in difficulty: LLMs now achi…

cs.LG2025

Model Merging Improves Zero-Shot Generalization in Bioacoustic Foundation Models

Davide Marincione, Donato Crisostomi, Roberto Dessi +2

Foundation models capable of generalizing across species and tasks represent a promising new frontier in bioacoustics, with NatureLM being one of the most prominent examples. While…