3 citations · 5 across the 25 of their papers we have counts for
26 papers
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,…
Real-Time Multi-Target Detection and Tracking with mmWave 5G NR Waveforms on RFSoC
Xinyang Li, Hian Zing Voon, Vlad C. Andrei +5
We demonstrate a real-time implementation of multi-target detection and tracking using 5G New Radio (NR) physical downlink shared channel (PDSCH) waveform with 400 MHz bandwidth at…
When Data is the Algorithm: A Systematic Study and Curation of Preference Optimization Datasets
Aladin Djuhera, Farhan Ahmed, Swanand Ravindra Kadhe +3
Aligning large language models (LLMs) is a central objective of post-training, often achieved through reward modeling and reinforcement learning methods. Among these, direct prefer…
Variational Secret Common Randomness Extraction
Xinyang Li, Vlad C. Andrei, Peter J. Gu +3
This paper studies the problem of extracting common randomness (CR) or secret keys from correlated random sources observed by two legitimate parties, Alice and Bob, through public…
Fixing It in Post: A Comparative Study of LLM Post-Training Data Quality and Model Performance
Aladin Djuhera, Swanand Ravindra Kadhe, Syed Zawad +3
Recent work on large language models (LLMs) has increasingly focused on post-training and alignment with datasets curated to enhance instruction following, world knowledge, and spe…
"Don't Do That!": Guiding Embodied Systems through Large Language Model-based Constraint Generation
Amin Seffo, Aladin Djuhera, Masataro Asai +1
Recent advancements in large language models (LLMs) have spurred interest in robotic navigation that incorporates complex spatial, mathematical, and conditional constraints from na…
SafeCOMM: A Study on Safety Degradation in Fine-Tuned Telecom Large Language Models
Aladin Djuhera, Swanand Ravindra Kadhe, Farhan Ahmed +4
Fine-tuning large language models (LLMs) on telecom datasets is a common practice to adapt general-purpose models to the telecom domain. However, little attention has been paid to…
Computation of Capacity-Distortion-Cost Functions for Continuous Memoryless Channels
Xinyang Li, Ziyou Tang, Vlad C. Andrei +3
This paper aims at computing the capacity-distortion-cost (CDC) function for continuous memoryless channels, which is defined as the supremum of the mutual information between chan…
Exploiting Beamforming for Enforcing Semantic Secrecy in 5G NR mmWave Communications
Luis Torres-Figueroa, Johannes Voichtleitner, Ullrich J. Mönich +3
We experimentally investigate the performance of semantically-secure physical layer security (PLS) in 5G new radio (NR) mmWave communications during the initial cell search procedu…
Computing Capacity-Cost Functions for Continuous Channels in Wasserstein Space
Xinyang Li, Vlad C. Andrei, Ullrich J. Mönich +2
This paper investigates the problem of computing capacity-cost (C-C) functions for continuous channels. Motivated by the Kullback-Leibler divergence (KLD) proximal reformulation of…
SafeMERGE: Preserving Safety Alignment in Fine-Tuned Large Language Models via Selective Layer-Wise Model Merging
Aladin Djuhera, Swanand Ravindra Kadhe, Farhan Ahmed +2
Fine-tuning large language models (LLMs) is a common practice to adapt generalist models to specialized domains. However, recent studies show that fine-tuning can erode safety alig…
A Simultaneous Decoding Approach to Joint State and Message Communications
Xinyang Li, Yiqi Chen, Vlad C. Andrei +3
The capacity-distortion (C-D) trade-offs for joint state and message communications (JSMC) over single- and multi-user channels are investigated, where the transmitters have access…
SE(3)-Based Trajectory Optimization and Target Tracking in UAV-Enabled ISAC Systems
Dongxiao Xu, Xinyang Li, Vlad C. Andrei +3
This paper presents a novel approach to enhance sensing capabilities in UAV-enabled MIMO-OFDM ISAC systems by leveraging UAV mobility as a mono-static radar. By integrating uniform…
Deep-Unrolling Multidimensional Harmonic Retrieval Algorithms on Neuromorphic Hardware
Vlad C. Andrei, Alexandru P. Drăguţoiu, Gabriel Béna +5
This paper explores the potential of conversion-based neuromorphic algorithms for highly accurate and energy-efficient single-snapshot multidimensional harmonic retrieval (MHR). By…
R-MTLLMF: Resilient Multi-Task Large Language Model Fusion at the Wireless Edge
Aladin Djuhera, Vlad C. Andrei, Mohsen Pourghasemian +3
Multi-task large language models (MTLLMs) are important for many applications at the wireless edge, where users demand specialized models to handle multiple tasks efficiently. Howe…
SCoTT: Strategic Chain-of-Thought Tasking for Wireless-Aware Robot Navigation in Digital Twins
Aladin Djuhera, Amin Seffo, Vlad C. Andrei +2
Path planning under wireless performance constraints is a complex challenge in robot navigation. However, naively incorporating such constraints into classical planning algorithms…
An Achievable Rate-Distortion Region for Joint State and Message Communication over Multiple Access Channels
Xinyang Li, Vlad C. Andrei, Ullrich J. Mönich +1
This paper derives an achievable rate-distortion (R-D) region for the state-dependent discrete memoryless multiple access channel (SD-DMMAC), where the generalized feedback and cau…
R-SFLLM: Jamming Resilient Framework for Split Federated Learning with Large Language Models
Aladin Djuhera, Vlad C. Andrei, Xinyang Li +3
Split federated learning (SFL) is a compute-efficient paradigm in distributed machine learning (ML), where components of large ML models are outsourced to remote servers. A signifi…
Resilient-By-Design Framework for MIMO-OFDM Communications under Smart Jamming
Vlad C. Andrei, Aladin Djuhera, Xinyang Li +3
Native jamming mitigation is essential for addressing security and resilience in future 6G wireless networks. In this paper a resilient-by-design framework for effective anti-jammi…