Best Online LaTeX Editor, Murfy

A noteworthy announcement was recently made in the field of Natural Language Processing. Starting from March 2026, the ACL Rolling Review (ARR) will officially discontinue support for Microsoft Word templates. Any papers submitted in Word format will be automatically desk-rejected. This marks more than just a change in formatting—it signals a significant shift in research writing culture and the tools researchers choose to use.

“When the Overleaf server went down the day before the deadline, we switched to Murfy to finish – and our paper was accepted to NeurIPS.” During the final hours before submission, just a few hours of downtime can determine the fate of an entire project. Professor Sang‑hoon Lee ’s research lab at Ajou University faced exactly this kind of crisis — and in that moment adopted Murfy, discovering the true value of an AI‑based LaTeX editor. In this post, we share their real user experience of writing a NeurIPS‑accepted paper using Murfy, based on an interview with Professor Lee’s laboratory.

Text-to-video generation has seen rapid progress thanks to large-scale diffusion models. However, maintaining generation quality while significantly reducing inference time remains a persistent challenge. The paper “Foresight: Adaptive Layer Reuse for Accelerated and High-Quality Text-to-Video Generation” introduces a clever solution: reuse internal model layers adaptively during inference—without retraining. This strategy allows for faster generation (1.63× improvement) while keeping the visual fidelity intact. In this post, we’ll break down the core idea behind Foresight, how it achieves speed without sacrificing quality, and why this could reshape efficient video generation pipelines in research and industry alike.

In multi-author projects, the name of the game is agree fast, compile clean, submit without waste. For Murfy blog readers, here’s a practical comparison that highlights where Murfy outperforms Overleaf.