by ODEFTO AI Labs
arXiv:2511.00097v2 Announce Type: replace-cross Abstract: Graph incremental learning (GIL), which continuously updates graph models by sequential knowledge acquisition, has garnered…
arXiv:2603.07926v2 Announce Type: replace-cross Abstract: Test-time adaptation (TTA) has been widely explored to prevent performance degradation when test data differ…
arXiv:2603.09425v1 Announce Type: cross Abstract: We present CERES (Calibrated Early-warning and Risk Estimation System), an automated probabilistic forecasting system for…
arXiv:2603.09434v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly deployed across diverse real-world applications and user communities. As…
arXiv:2603.08640v2 Announce Type: replace-cross Abstract: AI agents have become surprisingly proficient at software engineering over the past year, largely due…
arXiv:2603.08835v1 Announce Type: new Abstract: The rapid adoption of LLM-based agentic systems has produced a rich ecosystem of frameworks (smolagents,…
arXiv:2603.05437v2 Announce Type: replace-cross Abstract: Weakly-Supervised Dense Video Captioning aims to localize and describe events in videos trained only on…
arXiv:2603.08059v1 Announce Type: cross Abstract: With the rapid advancement of commercial multi-modal models, image editing has garnered significant attention due…
arXiv:2603.08090v1 Announce Type: cross Abstract: Significant progress has been achieved in subject-driven text-to-image (T2I) generation, which aims to synthesize new…
arXiv:2603.05768v2 Announce Type: replace-cross Abstract: Model merging integrates multiple task-specific models into a single consolidated one. Recent research has made…