2 citations · 2 across the 2 of their papers we have counts for
15 papers
NVIDIA-labs OO Agents: Native Python Object-Oriented Agents
Paul Furgale, Severin Klingler, James Nolan +12
Traditional agent development is split across prompt templates, tool schemas, callback code, and workflow graphs. We present NVIDIA Object-Oriented Agents (NOOA), a model-agnostic…
Mixture-of-Experts Graph Transformers for Interpretable Particle Collision Detection
Donatella Genovese, Alessandro Sgroi, Alessio Devoto +6
The Large Hadron Collider at CERN produces immense volumes of complex data from high-energy particle collisions, demanding sophisticated analytical techniques for effective interpr…
Universal Properties of Activation Sparsity in Modern Large Language Models
Filip Szatkowski, Patryk BÄdkowski, Alessio Devoto +5
Activation sparsity is an intriguing property of deep neural networks that has been extensively studied in ReLU-based models, due to its advantages for efficiency, robustness, and…
Attention Sinks in Diffusion Language Models
Maximo Eduardo Rulli, Simone Petruzzi, Edoardo Michielon +3
Masked Diffusion Language Models (DLMs) have recently emerged as a promising alternative to traditional Autoregressive Models (ARMs). DLMs employ transformer encoders with bidirect…
Expected Attention: KV Cache Compression by Estimating Attention from Future Queries Distribution
Alessio Devoto, Maximilian Jeblick, Simon Jégou
Memory consumption of the Key-Value (KV) cache represents a major bottleneck for efficient large language model inference. While attention-score-based KV cache pruning shows promis…
From KMMLU-Redux to KMMLU-Pro: A Professional Korean Benchmark Suite for LLM Evaluation
Seokhee Hong, Sunkyoung Kim, Guijin Son +3
The development of Large Language Models (LLMs) requires robust benchmarks that encompass not only academic domains but also industrial fields to effectively evaluate their applica…