113 citations · 229 across the 41 of their papers we have counts for
48 papers
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…
STaD: Scaffolded Task Design for Identifying Compositional Skill Gaps in LLMs
Sungeun An, Swanand Ravindra Kadhe, Shailja Thakur +2
Benchmarks are often used as a standard to understand LLM capabilities in different domains. However, aggregate benchmark scores provide limited insight into compositional skill ga…
AgentSCOPE: Evaluating Contextual Privacy Across Agentic Workflows
Ivoline C. Ngong, Keerthiram Murugesan, Swanand Kadhe +3
Agentic systems are increasingly acting on users' behalf, accessing calendars, email, and personal files to complete everyday tasks. Privacy evaluation for these systems has focuse…
Entropy-Aware On-Policy Distillation of Language Models
Woogyeol Jin, Taywon Min, Yongjin Yang +5
On-policy distillation is a promising approach for transferring knowledge between language models, where a student learns from dense token-level signals along its own trajectories.…
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,…
In-Context Probing for Membership Inference in Fine-Tuned Language Models
Zhexi Lu, Hongliang Chi, Nathalie Baracaldo +3
Membership inference attacks (MIAs) pose a critical privacy threat to fine-tuned large language models (LLMs), especially when models are adapted to domain-specific tasks using sen…