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20172026
most citedReasoning Beyond Limits: Advances and Open Problems for LLMs

22 citations · 43 across the 29 of their papers we have counts for

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Showing 2026Show all

9 papers · 1 filter

cs.AI2026

LIDSA: Cognitive Arbitration for Signal-Free Autonomous Intersection Management

Abderrahmane Lakas, Mohamed Amine Ferrag, Merouane Debbah

Large language models (LLMs) show strong potential for Intelligent Transportation Systems (ITS), particularly in tasks requiring situational reasoning and multi-agent coordination.…

cs.LG2026

VARS-FL: Validation-Aligned Client Selection for Non-IID Federated Learning in IoT Systems

Mohamed Lakas, Mohamed Amine Ferrag

Federated learning (FL) systems typically employ stateless client selection, treating each communication round independently and ignoring accumulated evidence of client contributio…

cs.NI2026

6G Needs Agents: Toward Agentic AI-Native Networks for Autonomous Intelligence

Mohamed Amine Ferrag, Abderrahmane Lakas, Merouane Debbah

Sixth-generation (6G) networks are increasingly envisioned as AI-native infrastructures integrating communication, sensing, and computing into a unified fabric. However, existing a…

cs.LG2026

FreeGNN: Continual Source-Free Graph Neural Network Adaptation for Renewable Energy Forecasting

Abderaouf Bahi, Amel Ourici, Ibtissem Gasmi +3

Accurate forecasting of renewable energy generation is essential for efficient grid management and sustainable power planning. However, traditional supervised models often require…

cs.NI2026

How Small Can 6G Reason? Scaling Tiny-to-Small Language Models for AI-Native Networks

Mohamed Amine Ferrag, Abderrahmane Lakas, Merouane Debbah

Emerging 6G visions, reflected in ongoing standardization efforts within 3GPP, IETF, ETSI, ITU-T, and the O-RAN Alliance, increasingly characterize networks as AI-native systems in…

cs.NI2026

6G-Bench: An Open Benchmark for Semantic Communication and Network-Level Reasoning with Foundation Models in AI-Native 6G Networks

Mohamed Amine Ferrag, Abderrahmane Lakas, Merouane Debbah

This paper introduces 6G-Bench, an open benchmark for evaluating semantic communication and network-level reasoning in AI-native 6G networks. 6G-Bench defines a taxonomy of 30 deci…