9 papers
HPO: Hysteretic Policy Optimization for Stable and Efficient Training under Sparse-Reward Regime
Mohamed Sana, Nicola Piovesan, Antonio De Domenico +2
We investigate a narrow but common failure mode of GRPO-style reinforcement learning in the context of sparse verifiable rewards: early updates contain more responses with negative…
TeleTables: A Benchmark for Large Language Models in Telecom Table Interpretation
Anas Ezzakri, Nicola Piovesan, Mohamed Sana +3
Language Models (LLMs) are increasingly explored in the telecom industry to support engineering tasks, accelerate troubleshooting, and assist in interpreting complex technical docu…
Telco-oRAG: Optimizing Retrieval-augmented Generation for Telecom Queries via Hybrid Retrieval and Neural Routing
Andrei-Laurentiu Bornea, Fadhel Ayed, Antonio De Domenico +3
Artificial intelligence will be one of the key pillars of the next generation of mobile networks (6G), as it is expected to provide novel added-value services and improve network p…
KVCompose: Efficient Structured KV Cache Compression with Composite Tokens
Dmitry Akulov, Mohamed Sana, Antonio De Domenico +3
Large language models (LLMs) rely on key-value (KV) caches for efficient autoregressive decoding; however, cache size grows linearly with context length and model depth, becoming a…
Goal-Oriented Time-Series Forecasting: Foundation Framework Design
Luca-Andrei Fechete, Mohamed Sana, Fadhel Ayed +4
Conventional time-series forecasting methods typically aim to minimize overall prediction error, without accounting for the varying importance of different forecast ranges in downs…
Reasoning Language Models for Root Cause Analysis in 5G Wireless Networks
Mohamed Sana, Nicola Piovesan, Antonio De Domenico +4
Root Cause Analysis (RCA) in mobile networks remains a challenging task due to the need for interpretability, domain expertise, and causal reasoning. In this work, we propose a lig…