Stay updated with the latest research and technology news
arXiv:2602.04595v2 Announce Type: replace Abstract: Large Language Models (LLMs) are powerful but incur high memory and computation costs. Quantization is an effective solution, with INT...
arXiv:2602.05165v3 Announce Type: replace Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) has proven effective for enhancing the reasoning capabilities of Large Language Models (LLMs). However,...
arXiv:2602.05220v2 Announce Type: replace Abstract: Current audio foundation models typically rely on rigid, task-specific supervision, addressing isolated factors of audio rather than the whole. In...
arXiv:2602.05495v2 Announce Type: replace Abstract: Large language models (LLMs) achieve strong capabilities by scaling model capacity and training data, yet many real-world deployments rely on...
arXiv:2602.05695v2 Announce Type: replace Abstract: Large Language Models (LLMs) inference is central to modern AI applications, dominating worldwide datacenter workloads, making it critical to predict...
arXiv:2602.07135v3 Announce Type: replace Abstract: Loss landscapes are a powerful tool for understanding neural network optimization and generalization, yet traditional low-dimensional analyses often miss complex...
arXiv:2602.07754v2 Announce Type: replace Abstract: This study investigates students' perceptions of Artificial Intelligence (AI) grading systems in an undergraduate computer science course (n = 27),...
arXiv:2602.07854v3 Announce Type: replace Abstract: Predictive world models that simulate future observations under explicit camera control are fundamental to interactive AI. Despite rapid advances, current...
arXiv:2602.07883v2 Announce Type: replace Abstract: Agentic systems powered by Large Language Models (LLMs) have demonstrated remarkable potential in tackling complex, long-horizon tasks. However, their efficacy...
arXiv:2602.08104v2 Announce Type: replace Abstract: Multi-Agent Reinforcement Learning (MARL) is increasingly deployed in safety-critical domains, yet methods for interpretable failure detection and attribution remain underdeveloped....
arXiv:2602.08354v2 Announce Type: replace Abstract: Recent advancements in large reasoning models (LRMs) have greatly improved their capabilities on complex reasoning tasks through Long Chains of...
arXiv:2602.08535v4 Announce Type: replace Abstract: Generative modeling typically seeks the path of least action via deterministic flows (ODE). While effective for in-distribution tasks, we argue...
arXiv:2602.08550v2 Announce Type: replace Abstract: Human perception for effective object tracking in a 2D video stream arises from the implicit use of prior 3D knowledge...
arXiv:2602.08885v4 Announce Type: replace Abstract: Symbolic regression (SR) aims to discover interpretable analytical expressions that accurately describe observed data. Amortized SR promises to be much...
arXiv:2602.09084v2 Announce Type: replace Abstract: We study instruction-based image editing under professional workflows and identify three persistent challenges: (i) editors often over-edit, modifying content beyond...
arXiv:2602.09345v2 Announce Type: replace Abstract: AI agents are increasingly deployed in multi-tenant cloud environments, where they execute diverse tool calls within sandboxed containers, each call...
arXiv:2602.09467v3 Announce Type: replace Abstract: Traceability links are key information sources for software developers, connecting software artifacts. Such links play an important role, particularly between...
arXiv:2602.09548v2 Announce Type: replace Abstract: Binary Function Similarity (BFS), the problem of determining whether two binary functions originate from the same source code, has been...
arXiv:2602.09648v2 Announce Type: replace Abstract: Domain Generalized Video Semantic Segmentation (DGVSS) is trained on a single labeled driving domain and is directly deployed on unseen...
arXiv:2602.10116v2 Announce Type: replace Abstract: Real-world data collection for embodied agents remains costly and unsafe, calling for scalable, realistic, and simulator-ready 3D environments. However, existing...
arXiv:2602.10268v2 Announce Type: replace Abstract: We develop an efficient, unconditionally stable, variable step second order exponential time differencing scheme for the incompressible Navier Stokes equations...
arXiv:2602.10471v2 Announce Type: replace Abstract: Given that Large Language Models (LLMs) are increasingly applied to automate software development, comprehensive software assurance spans three distinct goals:...
arXiv:2602.11767v2 Announce Type: replace Abstract: Advances in large language models (LLMs) are driving a shift toward using reinforcement learning (RL) to train agents from iterative,...
arXiv:2602.11962v2 Announce Type: replace Abstract: The spread of election misinformation and harmful political content conveys misleading narratives and poses a serious threat to democratic integrity....