arXiv:2605.02730v1 Announce Type: cross
Abstract: Despite the success of Large-Vision Language Models (LVLMs), general optimization objectives (e.g., standard MLE) fail to constrain visual trajectories, leading to language bias and hallucination. To m…
arXiv:2604.27840v2 Announce Type: replace-cross
Abstract: Recently, large language models (LLMs) have shown great promise in time series forecasting. However, most existing LLM-based forecasting methods still follow a static generative paradigm that d…
arXiv:2605.01060v1 Announce Type: cross
Abstract: We present SURGE, a streaming GPU encoding system deployed in production to generate embeddings for over 800 million texts across 40,000 logical partitions. Production embedding pipelines face a tensio…
arXiv:2502.03506v2 Announce Type: replace-cross
Abstract: The Centralized Training with Decentralized Execution (CTDE) paradigm is widely used in cooperative multi-agent reinforcement learning. However, conventional methods based on CTDE can suffer fr…
arXiv:2605.01163v1 Announce Type: cross
Abstract: Shared embedding spaces are widely used for multimodal search and data curation. In practice, two problems often limit how well this works. First, embeddings can reflect modality more than meaning, so …
arXiv:2602.17205v2 Announce Type: replace-cross
Abstract: The detection limit of astronomical imaging observations is limited by several noise sources. Some of that noise is correlated between neighbouring image pixels and exposures, so in principle c…
arXiv:2509.19202v2 Announce Type: replace-cross
Abstract: We propose Parameter Space Analysis through Guided Visual Interpolations (ParamInter), a novel tool for high-dimensional input parameter space analysis by making interpolation towards optimal p…
arXiv:2605.00639v1 Announce Type: cross
Abstract: Autonomous science is transforming how we discover materials and chemical systems for advanced energy technologies. However, many initially promising systems never reach deployment. This “valley of dea…
arXiv:2510.13668v2 Announce Type: replace-cross
Abstract: Large Language Model (LLM) inference has emerged as a fundamental paradigm, however, variations in output length cause severe workload imbalance in the decode phase, particularly for long-outpu…
arXiv:2604.28139v2 Announce Type: replace-cross
Abstract: LLM agents are expected to complete end-to-end units of work across software tools, business services, and local workspaces. Yet many agent benchmarks freeze a curated task set at release time …