AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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Although Large Language Models (LLMs) have demonstrated potential in clinical documentation, generating the rigorous, evidence-based reasoning required for unprecedented, atypical, and rare disease case reports remains a significant challenge. We present MedCaseAgent, an end-to-end agentic reasoning paradigm that bridg...
This work introduces CoDA, a framework in which a simulation data engine and an action policy co-evolve through a shared heterogeneous memory of environment construction, policy failures, and learning progress, and proposes Text2potential to convert these diagnoses into staged potentials for action-chunk value learning...
High-resolution 3D generation increasingly relies on voxel latents and multi-stage pipelines that first predict active structure and then synthesize local geometry. While effective, this design fragments continuous surfaces into many local tokens, inflates generation cost, and often weakens topological consistency for...
GraphVid is introduced, a graph-conditioned image-to-video generation model that enables interactive control through structured interaction graphs that delivers strong controllability and video quality and highlights the potential of structured semantic interfaces as a powerful paradigm for controllable video generatio...
Video editing spans diverse editing paradigms, yet achieving high-quality instruction-guided and subject-guided editing within a single unified framework remains challenging. We introduce EditVid, a training-free framework combining sparse causal memory for local coherence, correspondence-based post-attention token inj...
This work proposes ChronoVision, a multimodal framework designed to align visual logic with latent imagery, and introduces Vbvr-VQA, a novel dataset that evaluates temporal tracking by reformulating video reasoning into a strict image-ordering task.
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