[Paper] LEAD: Minimizing Learner-Expert Asymmetry in End-to-End Driving
Simulators can generate virtually unlimited driving data, yet imitation learning policies in simulation still struggle to achieve robust closed-loop performance...
Simulators can generate virtually unlimited driving data, yet imitation learning policies in simulation still struggle to achieve robust closed-loop performance...
We study the problem of learning a low-degree spherical polynomial of degree ell_0 = Θ(1) ge 1 defined on the unit sphere in RR^d by training an over-parameteri...
Teachers' emotional states are critical in educational scenarios, profoundly impacting teaching efficacy, student engagement, and learning achievements. However...
How to participate - 📌 Follow the 21 Days of Building a Small Language Model series - 📌 If you’ve learned anything from it so far - 📌 Create a post sharing...
Maintaining large-scale, multilingual codebases hinges on accurately localizing issues, which requires mapping natural-language error descriptions to the releva...
We propose a Vision-Language Simulation Model (VLSM) that unifies visual and textual understanding to synthesize executable FlexScript from layout sketches and ...
Service-based architecture (SBA) has gained attention in industry and academia as a means to modernize legacy systems. It refers to a design style that enables ...
Federated learning (FL) supports privacy-preserving, decentralized machine learning (ML) model training by keeping data on client devices. However, non-independ...
The Transformation Input: “Great news! Your flight to Paris is confirmed.” Output: audio waveform !TTShttps://media2.dev.to/dynamic/image/width=800%2Cheight=%2...
PyTorch vs. TensorFlow – Which Is Right for Your Workflow? Source: PyTorch vs. TensorFlow Enterprise Guidehttps://www.netcomlearning.com/blog/pytorch-vs-tensor...
Recent progress in Large Language Models (LLMs) has substantially advanced the automation of software engineering (SE) tasks, enabling complex activities such a...
The memory of contemporary Large Language Models is bound by a physical paradox: as they learn, they fill up. The linear accumulation (O(N)) of Key-Value states...