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arXiv:2604.01762v1 Announce Type: cross Abstract: Parameter-efficient fine-tuning (PEFT) has emerged as a crucial paradigm for adapting large language models (LLMs)...
arXiv:2604.01639v1 Announce Type: new Abstract: Large language models demonstrate strong performance on mathematical reasoning benchmarks, yet remain surprisingly fragile to...
arXiv:2604.01195v2 Announce Type: replace Abstract: Search agents, which integrate language models (LMs) with web search, are becoming crucial for answering...
arXiv:2604.01630v1 Announce Type: new Abstract: Despite emerging use in Indonesian classrooms, there is limited large-scale, teacher-centred evidence on how AI...

Video editing has always had a dirty secret: removing an object from footage is easy; making the scene look like...
arXiv:2604.00130v1 Announce Type: new Abstract: Chain-of-Thought (CoT) prompting has significantly improved the reasoning capabilities of large language models (LLMs). However,...
arXiv:2602.23440v3 Announce Type: replace Abstract: Reinforcement learning has emerged as an effective paradigm for training large language models to interleave...
arXiv:2604.00027v1 Announce Type: new Abstract: Large-scale EHR prediction across institutions is hindered by substantial heterogeneity in schemas and code systems....
In this tutorial, we build a complete end-to-end pipeline using NVIDIA Model Optimizer to train, prune, and fine-tune a deep...










