activity
20172026
most citedFLeet: Online Federated Learning via Staleness Awareness and Performance Prediction

29 citations · 58 across the 7 of their papers we have counts for

collaborators

7 papers

cs.AI2026

Oracle Agent Memory as an Enterprise Memory Substrate for Long-Horizon AI Agents

Richmond Alake, Cesare Bernardis, Paul Cayet +10

Agent memory is a systems problem for long-horizon agents. Practical deployments require retention of task state across extended conversations, recovery of user-specific facts and…

cs.AI2025

Open Agent Specification (Agent Spec): A Unified Representation for AI Agents

Soufiane Amini, Yassine Benajiba, Cesare Bernardis +16

The proliferation of agent frameworks has led to fragmentation in how agents are defined, executed, and evaluated. Existing systems differ in their abstractions, data flow semantic…

cs.CL2025

Distill-C: Enhanced NL2SQL via Distilled Customization with LLMs

Cong Duy Vu Hoang, Gioacchino Tangari, Clemence Lanfranchi +10

The growing adoption of large language models (LLMs) in business applications has amplified interest in Natural Language to SQL (NL2SQL) solutions, in which there is competing dema…

cs.LG2020★ 29 cited

FLeet: Online Federated Learning via Staleness Awareness and Performance Prediction

Georgios Damaskinos, Rachid Guerraoui, Anne-Marie Kermarrec +3

Federated Learning (FL) is very appealing for its privacy benefits: essentially, a global model is trained with updates computed on mobile devices while keeping the data of users l…

stat.ML2018★ 25 cited

Asynchronous Byzantine Machine Learning (the case of SGD)

Georgios Damaskinos, El Mahdi El Mhamdi, Rachid Guerraoui +2

Asynchronous distributed machine learning solutions have proven very effective so far, but always assuming perfectly functioning workers. In practice, some of the workers can howev…

cs.IR2017★ 4 cited

Sequences, Items And Latent Links: Recommendation With Consumed Item Packs

Rachid Guerraoui, Erwan Le Merrer, Rhicheek Patra +1

Recommenders personalize the web content by typically using collaborative filtering to relate users (or items) based on explicit feedback, e.g., ratings. The difficulty of collecti…