3 citations · 5 across the 25 of their papers we have counts for
6 papers · 1 filter
Tropical Reinforcement Learning
Arip Asadulaev, Aladin Djuhera, Karim Salta +3
Reinforcement learning for large language models typically maximizes expected return, adding up the probabilities of all successful trajectories. However, the classical sum formula…
Variational Probabilistic Quantization for Secret Key Generation
Xinyang Li, Vlad C. Andrei, Peter J. Gu +3
Secret key generation from correlated observations at Alice and Bob, in the presence of an eavesdropper Eve, underpins physical-layer security. Classical pipelines quantize by hand…
Poli-Bias: Understanding and Measuring Large Language Model Biases in International Political Conflicts
Massi-Nissa Abboud, Aladin Djuhera, Elena Cabrio +1
Measuring political bias in large language models (LLMs) remains challenging as it can manifest through subtle differences in framing, argumentation, and legal reasoning that are d…
Against the Monolithic Wireless World Model: Why NextG Needs Composable and Agentic Intelligence
Aladin Djuhera, Farhan Ahmed, Vlad C. Andrei +4
AI-native 6G visions increasingly invoke wireless foundation models, large multimodal models, and wireless world models as the natural endpoint of AI-native networking, drawing an…
MambaCSP: Hybrid-Attention State Space Models for Hardware-Efficient Channel State Prediction
Aladin Djuhera, Haris Gacanin, Holger Boche
Recent works have demonstrated that attention-based transformer and large language model (LLM) architectures can achieve strong channel state prediction (CSP) performance by captur…
TSR: Trajectory-Search Rollouts for Multi-Turn RL of LLM Agents
Aladin Djuhera, Swanand Kadhe, Swanand Ravindra Kadhe +4
Advances in large language models (LLMs) are driving a shift toward using reinforcement learning (RL) to train agents from iterative, multi-turn interactions across tasks. However,…