数据来源：ArXiv Domain LLM Domain Papers1. Agentic Structured Graph Traversal for Root Cause Analysis of Code-related Incidents in Cloud ApplicationsCloud incidents pose major operational challenges in production, with unresolved production cloud incidents cost on average over $2M per hour. Prior research identifies code- and configuration-related issues as the predominant category of root causes in cloud incidents. This paper introduces PRAXIS, an orchestrator that manages and deploys an agentic w ...

数据来源：ArXiv Domain LLM Domain Papers1. Training AI Co-Scientists Using Rubric RewardsAI co-scientists are emerging as a tool to assist human researchers in achieving their research goals. A crucial feature of these AI co-scientists is the ability to generate a research plan given a set of aims and constraints. The plan may be used by researchers for brainstorming, or may even be implemented after further refinement. However, language models currently struggle to generate research plans that fol ...

数据来源：ArXiv Domain LLM Domain Papers1. Optimizing Decoding Paths in Masked Diffusion Models by Quantifying UncertaintyMasked Diffusion Models (MDMs) offer flexible, non-autoregressive generation, but this freedom introduces a challenge: final output quality is highly sensitive to the decoding order. We are the first to formalize this issue, attributing the variability in output quality to the cumulative predictive uncertainty along a generative path. To quantify this uncertainty, we introduce D ...

数据来源：ArXiv Domain LLM Domain Papers1. RedSage: A Cybersecurity Generalist LLMCybersecurity operations demand assistant LLMs that support diverse workflows without exposing sensitive data. Existing solutions either rely on proprietary APIs with privacy risks or on open models lacking domain adaptation. To bridge this gap, we curate 11.8B tokens of cybersecurity-focused continual pretraining data via large-scale web filtering and manual collection of high-quality resources, spanning 28.6K docume ...

数据来源：ArXiv Domain LLM Domain Papers1. VideoGPA: Distilling Geometry Priors for 3D-Consistent Video GenerationWhile recent video diffusion models (VDMs) produce visually impressive results, they fundamentally struggle to maintain 3D structural consistency, often resulting in object deformation or spatial drift. We hypothesize that these failures arise because standard denoising objectives lack explicit incentives for geometric coherence. To address this, we introduce VideoGPA (Video Geometric P ...

数据来源：ArXiv Domain LLM Domain Papers1. EasyV2V: A High-quality Instruction-based Video Editing FrameworkWhile image editing has advanced rapidly, video editing remains less explored, facing challenges in consistency, control, and generalization. We study the design space of data, architecture, and control, and introduce \emph{EasyV2V}, a simple and effective framework for instruction-based video editing. On the data side, we compose existing experts with fast inverses to build diverse video pai ...

数据来源：ArXiv Domain LLM Domain Papers1. RedSage: A Cybersecurity Generalist LLMCybersecurity operations demand assistant LLMs that support diverse workflows without exposing sensitive data. Existing solutions either rely on proprietary APIs with privacy risks or on open models lacking domain adaptation. To bridge this gap, we curate 11.8B tokens of cybersecurity-focused continual pretraining data via large-scale web filtering and manual collection of high-quality resources, spanning 28.6K docume ...

数据来源：ArXiv Domain LLM Domain Papers1. Scalably Enhancing the Clinical Validity of a Task Benchmark with Physician OversightAutomating the calculation of clinical risk scores offers a significant opportunity to reduce physician administrative burden and enhance patient care. The current standard for evaluating this capability is MedCalc-Bench, a large-scale dataset constructed using LLM-based feature extraction and rule-based aggregation. However, treating such model-generated benchmarks as sta ...

数据来源：ArXiv Domain LLM Domain Papers1. SpaceTimePilot: Generative Rendering of Dynamic Scenes Across Space and TimeWe present SpaceTimePilot, a video diffusion model that disentangles space and time for controllable generative rendering. Given a monocular video, SpaceTimePilot can independently alter the camera viewpoint and the motion sequence within the generative process, re-rendering the scene for continuous and arbitrary exploration across space and time. To achieve this, we introduce an e ...

数据来源：ArXiv Domain LLM Domain Papers1. SpaceTimePilot: Generative Rendering of Dynamic Scenes Across Space and TimeWe present SpaceTimePilot, a video diffusion model that disentangles space and time for controllable generative rendering. Given a monocular video, SpaceTimePilot can independently alter the camera viewpoint and the motion sequence within the generative process, re-rendering the scene for continuous and arbitrary exploration across space and time. To achieve this, we introduce an e ...

数据来源：ArXiv Domain LLM Domain Papers1. SpaceTimePilot: Generative Rendering of Dynamic Scenes Across Space and TimeWe present SpaceTimePilot, a video diffusion model that disentangles space and time for controllable generative rendering. Given a monocular video, SpaceTimePilot can independently alter the camera viewpoint and the motion sequence within the generative process, re-rendering the scene for continuous and arbitrary exploration across space and time. To achieve this, we introduce an e ...

数据来源：ArXiv Domain LLM Domain Papers1. Effects of Structural Allocation of Geometric Task Diversity in Linear Meta-Learning ModelsMeta-learning aims to leverage information across related tasks to improve prediction on unlabeled data for new tasks when only a small number of labeled observations are available (“few-shot” learning). Increased task diversity is often believed to enhance meta-learning by providing richer information across tasks. However, recent work by Kumar et al. (2022) shows t ...

数据来源：ArXiv Domain LLM Domain Papers1. Reward-free Alignment for Conflicting ObjectivesDirect alignment methods are increasingly used to align large language models (LLMs) with human preferences. However, many real-world alignment problems involve multiple conflicting objectives, where naive aggregation of preferences can lead to unstable training and poor trade-offs. In particular, weighted loss methods may fail to identify update directions that simultaneously improve all objectives, and exis ...

数据来源：ArXiv Domain LLM Domain Papers1. Training AI Co-Scientists Using Rubric RewardsAI co-scientists are emerging as a tool to assist human researchers in achieving their research goals. A crucial feature of these AI co-scientists is the ability to generate a research plan given a set of aims and constraints. The plan may be used by researchers for brainstorming, or may even be implemented after further refinement. However, language models currently struggle to generate research plans that fol ...

数据来源：ArXiv Domain LLM Domain Papers1. SpaceTimePilot: Generative Rendering of Dynamic Scenes Across Space and TimeWe present SpaceTimePilot, a video diffusion model that disentangles space and time for controllable generative rendering. Given a monocular video, SpaceTimePilot can independently alter the camera viewpoint and the motion sequence within the generative process, re-rendering the scene for continuous and arbitrary exploration across space and time. To achieve this, we introduce an e ...