3 papers
cs.CV2026
There is No VAE: End-to-End Pixel-Space Generative Modeling via Self-Supervised Pre-training
Jiachen Lei, Keli Liu, Julius Berner +4
Pixel-space generative models are often more difficult to train and generally underperform compared to their latent-space counterparts, leaving a persistent performance and efficie…
cs.CE2026
NMRGym: A Comprehensive Benchmark for Nuclear Magnetic Resonance Based Molecular Structure Elucidation
Zheng Fang, Chen Yang, Hai-tao Yu +5
Nuclear Magnetic Resonance (NMR) spectroscopy is the cornerstone of small-molecule structure elucidation. While deep learning has demonstrated significant potential in automating s…
cs.CL2025
Know-MRI: A Knowledge Mechanisms Revealer&Interpreter for Large Language Models
Jiaxiang Liu, Boxuan Xing, Chenhao Yuan +8
As large language models (LLMs) continue to advance, there is a growing urgency to enhance the interpretability of their internal knowledge mechanisms. Consequently, many interpret…