arXiv:2604.25724v1 Announce Type: new Abstract: Modern enterprise AI applications increasingly rely on compound AI systems – architectures that compose multiple models, retrievers, and tools to accomplish complex tasks. Deploying such systems in production demands inference infrastructure that can efficiently serve concurrent, heterogeneous model invocations while maintaining cost-effectiveness and low latency. This paper presents a production […]
QAROO: AI-Driven Online Task Offloading for Energy-Efficient and Sustainable MEC Networks
arXiv:2604.25740v1 Announce Type: new Abstract: With the rapid advancement of artificial intelligence (AI) and intelligent science, intelligent edge computing has been widely adopted. However, the limitations of traditional methods, such as poor adaptability and the slow convergence of heuristic algorithms, are becoming increasingly evident. To enable sustainable and resource-efficient edge applications, this paper proposes an […]
StratFormer: Adaptive Opponent Modeling and Exploitation in Imperfect-Information Games
arXiv:2604.25796v1 Announce Type: new Abstract: We present StratFormer, a transformer-based meta-agent that learns to simultaneously model and exploit opponents in imperfect-information games through a two-phase curriculum. The first phase trains an opponent modeling head to identify behavioral patterns from action histories while the agent plays a game-theoretic optimal (GTO) policy. The second phase progressively shifts […]
Action-Aware Generative Sequence Modeling for Short Video Recommendation
arXiv:2604.25834v1 Announce Type: new Abstract: With the rapid development of the Internet, users have increasingly higher expectations for the recommendation accuracy of online content consumption platforms. However, short videos often contain diverse segments, and users may not hold the same attitude toward all of them. Traditional binary-classification recommendation models, which treat a video as a […]
ADEMA: A Knowledge-State Orchestration Architecture for Long-Horizon Knowledge Synthesis with LLMAgents
arXiv:2604.25849v1 Announce Type: new Abstract: Long-horizon LLM tasks often fail not because a single answer is unattainable, but because knowledge states drift across rounds, intermediate commitments remain implicit, and interruption fractures the evolving evidence chain. This paper presents ADEMA as a knowledge-state orchestration architecture for long-horizon knowledge synthesis rather than as a generic multi-agent runtime. […]
Back to Repair: A Minimal Denoising Network for Time Series Anomaly Detection
arXiv:2604.17388v2 Announce Type: cross Abstract: We introduce JuRe (Just Repair), a minimal denoising network for time series anomaly detection that exposes a central finding: architectural complexity is unnecessary when the training objective correctly implements the manifold-projection principle. JuRe consists of a single depthwise-separable convolutional residual block with hidden dimension 128, trained to repair corrupted time […]
Comparative Study of Bending Analysis using Physics-Informed Neural Networks and Numerical Dynamic Deflection in Perforated nanobeam
arXiv:2604.24768v1 Announce Type: cross Abstract: In this chapter, we investigate the bending behavior of a perforated nanobeam subjected to sinusoidal loading using an efficient and computationally robust Physics-Informed Functional Link Constrained Framework with Domain Mapping (DFL-TFC) method. Our aim is to determine the relationship between static bending response and dynamic deflection of a perforated nanobeam […]
Liquid Neural Network Models for Natural Gas Spot Price Time-Series Forecasting
arXiv:2604.24788v1 Announce Type: cross Abstract: Natural gas is undoubtedly an essential component of the global energy system. Accurate short-term forecasting of natural gas price is challenging due to pronounced volatility driven by seasonal demand patterns, geopolitical developments, and shifting macroeconomic conditions. The nonlinear dynamics and frequent regime changes can limit the effectiveness of traditional time-series […]
Salca: A Sparsity-Aware Hardware Accelerator for Efficient Long-Context Attention Decoding
arXiv:2604.24820v1 Announce Type: cross Abstract: Long contexts improve capabilities of large language models but pose serious hardware challenges: compute and memory footprints grow linearly with sequence length. Particularly, the decoding phase continuously accesses massive KV cache, dramatically increasing bandwidth and computing pressure. Existing accelerators are primarily designed and evaluated for short contexts. They suffer from […]
Neuronal electricality founded in murburn-thermodynamic principles: 1. Background and basic theoretical formulation
arXiv:2604.24772v1 Announce Type: new Abstract: Trans-membrane gradients and fluxes of cations (H+, Na+, K+, etc.) were deemed to be the rationale of electrical activities of aerobic cells/organelles, as per classical perceptions. Murburn concept (an umbrella of theorization based in stochastic redox processes) has afforded novel models for various metabolic, bioenergetic and electrophysiological outcomes. Herein, the […]
Incompressible Knowledge Probes: Estimating Black-Box LLM Parameter Counts via Factual Capacity
arXiv:2604.24827v1 Announce Type: cross Abstract: Closed-source frontier labs do not disclose parameter counts, and the standard alternative — inference economics — carries $2times$+ uncertainty from hardware, batching, and serving-stack assumptions external to the model. We exploit a tighter intrinsic bound: storing $F$ facts requires at least $F/$(bits per parameter) weights, so measuring how much a […]
Suiren-1.0 Technical Report: A Family of Molecular Foundation Models
arXiv:2603.21942v4 Announce Type: replace-cross Abstract: We introduce Suiren-1.0, a family of molecular foundation models for the accurate modeling of diverse organic systems. Suiren-1.0 comprising three specialized variants (Suiren-Base, Suiren-Dimer, and Suiren-ConfAvg) is integrated within an algorithmic framework that bridges the gap between 3D conformational geometry and 2D statistical ensemble spaces. We first pre-train Suiren-Base (1.8B […]