This paper proposes a preconditioning layer for stable weight conditioning in LLM training.

This paper proposes a Bayesian Optimization-based framework for multipath QUIC (MPQUIC) scheduling that jointly considers maximum upload completion time and total LTE usage, identifying Pareto-efficie…

This paper analyzes direction-of-arrival estimation using a tunable receive-side lossless reciprocal MiLAC combiner for antenna arrays and shows it can achieve the digital Cramér-Rao bound with fewer…

This paper introduces phase-to-primitive decomposition to enable Monte Carlo tree search (MCTS) on in-memory computing (IMC) systems, achieving significant energy efficiency and performance improvemen…

This paper proposes CertifiedCacheMPC, a caching system for Model Predictive Control in hierarchical quadruped controllers, ensuring primal feasibility and cost suboptimality.

The paper introduces a Variational Encrypted Model Predictive Control (VEMPC) protocol that enables online MPC execution using only encrypted polynomial operations, eliminating the need for intermedia…

The paper establishes conditions for QUBO formulations of combinatorial optimization problems that guarantee valid binary and feasible local minimizers using gradient-based methods.

This paper proposes a new method for AC/DC Power Factor Correction in single-phase On-Board Chargers for Electric Vehicles using a duty cycle predictive Model Predictive Current Control with real-time…

The paper introduces CAN-QA, a novel question-answering benchmark that reformulates CAN traffic analysis from a classification task to a reasoning task, demonstrating that current LLMs struggle with c…

The PopQuiz Attack is a novel black-box membership inference attack that successfully tests whether large language models memorize specific training data by framing the target data as multiple-choice…

This paper characterizes the performance of vision-language model inference on the Qualcomm SM8750 using FastVLM-0.5B as a case study, showing significant speedups and energy savings for different pha…

The authors identify confusion patterns in a large audio-language model and use them to curate diagnostic data for fine-tuning, achieving higher accuracy than the baseline.

The paper introduces LongVQUBench, a comprehensive benchmark for long-term video quality understanding with 1200 diverse videos and 1500 questions.

This paper investigates the use of a Random Forest surrogate model to predict molecular dynamics workload performance and recommend optimal hybrid MPI+OpenMP configurations without exhaustive benchmar…

The paper introduces CA-AC-MPC, a CUDA-accelerated variant of Actor-Critic Model Predictive Control, which significantly reduces the training and inference latency of AC-MPC while maintaining state-of…

The paper identifies and measures a critical failure mode where LLM agents violate policies by losing or corrupting directive-bearing state during the process of assembling the decision context, and p…

The paper introduces OmniMatBench, a comprehensive, human-calibrated multimodal reasoning benchmark covering 19 materials science subfields, revealing that current multimodal language models (MLLMs) h…

This paper establishes a direct connection between Approximate Message Passing (AMP) and the Convex Gaussian Min-max Theorem (CGMT) for regularized linear regression and M-estimation.