Tag: Prediction
All the articles with the tag "Prediction".
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Enhancing Safety Standards in Automated Systems Using Dynamic Bayesian Networks
This paper proposes a Dynamic Bayesian Network framework for autonomous vehicles that enhances safety in cut-in maneuvers by integrating lateral evidence and probabilistic safety assessments, achieving superior crash avoidance in high-speed scenarios (9.22% crash rate) compared to baseline models in the JRC-FSM simulator.
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Video Prediction Policy: A Generalist Robot Policy with Predictive Visual Representations
The Video Prediction Policy (VPP) introduces a novel generalist robot policy that leverages predictive visual representations from fine-tuned video diffusion models to learn implicit inverse dynamics, achieving significant improvements of 41.5% on the Calvin ABC→D benchmark and 31.6% in real-world dexterous manipulation tasks over state-of-the-art baselines.
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LENSLLM: Unveiling Fine-Tuning Dynamics for LLM Selection
LENSLLM introduces a Hessian-based PAC-Bayes framework and NTK-based scaling model for LLM selection, achieving up to 91.1% accuracy and 88.5% computational cost reduction by modeling fine-tuning dynamics across diverse tasks.
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COSMOS: Predictable and Cost-Effective Adaptation of LLMs
COSMOS introduces a cost-effective framework to predict performance and cost of LLM adaptation strategies like QLoRA fine-tuning and retrieval-augmented ICL, achieving high accuracy (1.09% MAE) and reducing computational costs by 92.72% across eight diverse benchmarks.
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Looped Transformers for Length Generalization
本文提出Looped Transformers方法,通过循环结构和自适应步数显著提升了Transformer在算法任务上的长度泛化能力,在多种任务中优于传统方法。