Avoiding Explainability Pitfalls in AI Language Learning
Explore how AI language tools can mislead learners and discover strategies to improve feedback accuracy and support in language learning systems.
ImproBR: Enhance Bug Reports with Advanced LLMs
Improve bug report quality using ImproBR, an LLM-powered tool that boosts reproducibility and clarity for faster software debugging.
Reward-Lens: Interpretability Library for AI Reward Models
Discover Reward-Lens, an open-source library for mechanistic interpretability of AI reward models, enhancing transparency in reinforcement learning.
AMMA: Low-Latency Memory-Centric Architecture for 1M Context
Discover AMMA, a multi-chiplet memory-centric architecture delivering 15.5X lower latency and 6.9X energy savings for 1M context attention in LLM serving.
MomentumGNN: Graph Neural Nets for Deformable Objects
Discover MomentumGNN, a graph neural network that conserves momentum for accurate deformable object simulations in graphics, robotics, and medical fields.