AI Models Learn to Think Better, Video Tech Gets Smarter, and Language Models Speed Up

AI Papers Podcast

Today's stories explore how artificial intelligence is evolving to become more thoughtful and efficient, with breakthroughs in how AI systems reason, process video, and generate content. From models that can 'deliberate' before making decisions to dramatic speedups in image generation, these advances signal a shift toward AI that's not just faster, but potentially more reliable and useful in real-world applications. Links to all the papers we discussed: RobustFT: Robust Supervised Fine-tuning for Large Language Models under Noisy Response, B-STaR: Monitoring and Balancing Exploration and Exploitation in Self-Taught Reasoners, Distilled Decoding 1: One-step Sampling of Image Auto-regressive Models with Flow Matching, Diving into Self-Evolving Training for Multimodal Reasoning, Deliberation in Latent Space via Differentiable Cache Augmentation, Large Motion Video Autoencoding with Cross-modal Video VAE