arXiv:2608.07725v1 Announce Type: new Abstract: Average-reward reinforcement-learning regret is known up to logarithmic factors, but the numerical content of published guarantees is difficult to compare because…
arXiv:2604.26836v3 Announce Type: replace Abstract: Predictive safety filters (PSFs) leverage model predictive control to enforce constraint satisfaction during deep reinforcement learning (RL) exploration, yet their reliance…
arXiv:2608.09888v1 Announce Type: new Abstract: We introduce BDH-CQ, a reasoning model that combines in-context learning with recurrent latent reasoning. Inputs presented at inference time continuously update…
arXiv:2608.08743v1 Announce Type: new Abstract: Reinforcement learning (RL) seeks to optimize sequential decisions to maximize population-level benefits over time. However, when deployed in high-stakes settings such…
arXiv:2608.09873v1 Announce Type: cross Abstract: We introduce Sci-VBench, a comprehensive benchmark for evaluating knowledge- and reasoning-intensive video generation across scientific domains. It contains 1,253 expert-annotated examples…
arXiv:2510.06473v4 Announce Type: replace-cross Abstract: Understanding and modeling human mobility is central to challenges in transport planning, sustainable urban design, and public health. Despite decades of…
arXiv:2608.07737v1 Announce Type: new Abstract: This paper investigates whether the postmodern claim of unrestricted semantic indeterminacy, and its foundational Saussurean axiom of the arbitrary sign, are…
arXiv:2602.02704v2 Announce Type: replace Abstract: Reasoning over ultra-long documents requires synthesizing sparse evidence scattered across distant segments under strict memory constraints. While streaming agents enable scalable…
arXiv:2608.07636v1 Announce Type: cross Abstract: Deep-OCR (DeepSeek-OCR) advances document recognition by treating the visual modality as an optical compression medium, enabling long-context OCR at low token…
arXiv:2608.07681v1 Announce Type: new Abstract: Accurate and robust time series forecasting is essential in many applications involving physical processes, such as manufacturing monitoring and astrophysical event…
arXiv:2206.13280v4 Announce Type: replace Abstract: We show that deep binary ReLU networks and deep sparse ternary ReLU networks can approximate $beta$-H"older functions on $[0,1]^d$. We also…
arXiv:2608.08156v1 Announce Type: cross Abstract: In evolutionary algorithms powered by language models, the LLM acts as a single operator that simultaneously updates structural components (like control…
arXiv:2605.01729v3 Announce Type: replace-cross Abstract: Generative Flow Networks (GFlowNets) sample diverse structured objects in proportion to reward and have been applied to molecular discovery and biological-sequence…
arXiv:2608.08994v1 Announce Type: cross Abstract: Retrieving relevant evidence from noisy web data is challenging, particularly in sensitive domains containing incomplete reports, heterogeneous language, and irrelevant content.…
arXiv:2608.07540v1 Announce Type: new Abstract: AI systems increasingly operate between flexible input representations and formal objects used by downstream tools. A key challenge is recognizing when…
arXiv:2608.07629v1 Announce Type: new Abstract: Multilingual neural machine translation models such as NLLB-200 cover 200 languages but leave thousands unsupported, including most Grassfields Bantu languages of…
arXiv:2608.09637v1 Announce Type: new Abstract: Diffusion models have enabled high-quality video generation in recent years, but the high cost of iterative sampling hinders their practical deployment.…
arXiv:2608.07565v1 Announce Type: new Abstract: Conversational assistants increasingly recommend follow-up edits to help users continue a task. Existing systems primarily target text-only interactions, leaving image-creation conversations…
arXiv:2608.07719v1 Announce Type: new Abstract: Offline reinforcement learning repeatedly trains policies from a fixed transition pool, making redundant data costly across seeds and hyperparameters, while naive…
arXiv:2608.08541v1 Announce Type: cross Abstract: Spiking Transformers provide a promising paradigm for efficient visual processing with spike-driven computation, yet their Softmax-free Spiking Self-Attention (SSA) struggles to…
arXiv:2608.07537v1 Announce Type: new Abstract: In this study, we propose a framework that incorporates subjective evaluations provided by a Vision-Language Model (VLM) into the fitness evaluation…
arXiv:2608.08770v1 Announce Type: new Abstract: Diffusion models are increasingly used as controllable samplers, whose generations can be steered at inference time according to a chosen reward…
arXiv:2608.09251v1 Announce Type: cross Abstract: Large language model-based multi-agent systems have recently shown strong potential for complex, long-horizon tasks. However, existing methods mainly rely on coarse…
arXiv:2604.14556v2 Announce Type: replace-cross Abstract: Video object insertion places a user-specified object in an existing dynamic scene. Existing methods typically condition generation on text or a…