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Small LLMs: Pruning vs. Training from Scratch
score 4
机构: Princeton;关键词(1): pruning
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DRIVE: Distributional and Retrieval-Augmented Bidding with Value Evaluation
score 4
关键词(2): real-time, retrieval-augmented;顶会接收: ICML
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OdysSim: Building Foundation Models for Human Behavior Simulation
score 4
机构: CMU;关键词(2): distillation, post-training
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From Prompts to Responses: Dual-Sided Data Leakage and Defense in Split Large Language Models
score 4
关键词(2): deployment, fine-tuning;顶会接收: ICML
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SkillAudit: Ground-Truth-Free Skill Evolution via Paired Trajectory Auditing
score 4
机构: Huawei;关键词(2): deployment, edge
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HarnessX: A Composable, Adaptive, and Evolvable Agent Harness Foundry
score 4
入选 HF Daily Papers;关键词(1): scaling
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One Layer's Trash is Another Layer's Treasure: Adaptive Layer-wise Visual Token Selection in LVLMs
score 4
关键词(5): lightweight, compression, pruning, deployment, vision-language;顶会接收: CVPR
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ForceForget: Reinforcement Concept Removal for Enhancing Safety in Text-to-Image Models
score 4
关键词(1): text-to-image;顶会接收: ICML
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Hy-Embodied-0.5-VLA: From Vision-Language-Action Models to a Real-World Robot Learning Stack
score 4
入选 HF Daily Papers;关键词(6): deployment, fine-tuning, post-training, pre-training, vision-language
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Fodor and Pylyshyn's Systematicity Challenge Still Stands
score 3
机构: MIT