This paper proposes AD-Mamba, a multi-stage knowledge distillation framework that improves the performance of state space models in audio classification tasks.

The paper proposes SISA (SSM-Informed Softmax Attention), a novel hybrid attention mechanism that integrates state-space model (SSM) importance signals directly into the attention score, achieving sta…

Zamba2-VL is a new suite of vision-language models built on the Zamba2 hybrid architecture, achieving state-of-the-art performance and significantly improved inference efficiency compared to leading T…

This study systematically evaluates Vision Mamba models for detecting AI-generated images, finding that while they show promise, their current strengths and limitations must be understood relative to…

Introduces U$^2$Mamba, a U-structured network for salient object detection with improved local feature extraction and contextual information.

This paper presents MAMO, a multi-agent reinforcement learning approach to tackle the problem of balancing cost minimization and constraint satisfaction in dynamic environments.

The paper proposes PC-MambaSDE, a physically-constrained continuous-time framework that accurately predicts Remaining Useful Life (RUL) despite irregular sensor observations and ensures physically pla…

A new deep learning method, Mamba Transformer, is proposed for accurate single-shot 3D reconstruction from a single high frequency fringe image.

The paper proposes RPCASSM, a novel state space model leveraging Robust PCA (RPCA) to accurately detect and segment infrared small targets by separately modeling background and target information base…

This paper proposes a novel restart strategy for the CMA-ES algorithm called Multi-Start Clustering CMA-ES (MSC-CMA-ES) that improves performance on multimodal optimization problems.

The paper introduces COSM, a cooperative scheduling framework to facilitate concurrent operation of Processing-in-Memory (PIM) and CPU tasks on mobile platforms, improving PIM throughput by up to 2.8x…

This study benchmarks four local LLMs for natural-language-to-SQL querying in biopharma manufacturing, finding that general-purpose code-tuned models like Llama 3.1 8B and Qwen 2.5 Coder 7B outperform…

This paper proves the strong NP-completeness and APX-completeness of the Symmetric Numerical Three-Dimensional Matching problem.

EnergyMamba proposes an uncertainty-aware, graph-enhanced selective state space model to significantly improve both the accuracy and reliability of energy consumption prediction by explicitly modeling…

MyoSem introduces an EMG-action semantic alignment framework that transforms low-level muscle signals into a shared semantic space, enabling bidirectional retrieval between EMG data and natural langua…

This paper systematically studies the potential of prompt optimization in multi-agent systems (MAS) across various setups, revealing significant gains but also open challenges.