arXiv Artificial IntelligenceScaling Near-Optimal SFT-RL Annotation Budget Allocation from Small to Large LLMs
arXiv:2609.01573v1 Announce Type: cross Abstract: How to divide a fixed annotation budget between supervised…
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arXiv Artificial IntelligencearXiv:2609.01573v1 Announce Type: cross Abstract: How to divide a fixed annotation budget between supervised…
arXiv Artificial IntelligencearXiv:2609.01564v1 Announce Type: cross Abstract: Large language models (LLMs) struggle to classify text into…
arXiv Artificial IntelligencearXiv:2609.01560v1 Announce Type: cross Abstract: We present H3-World, an efficient framework that turns the…
arXiv Artificial IntelligencearXiv:2609.01556v1 Announce Type: cross Abstract: We evaluate embedding retrieval where surface form and…
arXiv Artificial IntelligencearXiv:2609.01554v1 Announce Type: cross Abstract: Automated lesion segmentation in whole-body PET/CT is…
arXiv Artificial IntelligencearXiv:2609.01535v1 Announce Type: cross Abstract: This paper explores whether large language models (LLMs)…
arXiv Artificial IntelligencearXiv:2609.01525v1 Announce Type: cross Abstract: A durable assumption holds that graph analytics requires a…
arXiv Artificial IntelligencearXiv:2609.01515v1 Announce Type: cross Abstract: Temporal reasoning benchmarks for Video-LLMs are often…
arXiv Artificial IntelligencearXiv:2609.01495v1 Announce Type: cross Abstract: Security evaluations of decentralized federated learning…
arXiv Artificial IntelligencearXiv:2609.01491v1 Announce Type: cross Abstract: The growing rate at which LLM agents interact with one…
arXiv Artificial IntelligencearXiv:2609.01487v1 Announce Type: cross Abstract: Skill-augmented agents load reusable skills as persistent…
arXiv Artificial IntelligencearXiv:2609.01455v1 Announce Type: cross Abstract: Benign fine-tuning severely weakens the safety alignment of…