Herdr is a new terminal multiplexer designed specifically for managing multiple AI coding agents. It provides a real terminal environment for each agent, offers at-a-glance status updates (blocked, working, done, idle), and supports persistent sessions accessible from any terminal via SSH. Built in Rust, Herdr aims to streamline the developer workflow when orchestrating numerous AI assistants.
Researchers have introduced Exformer, an Extreme-Adaptive Transformer designed to improve time series forecasting, particularly for data containing rare but critical extreme events. This new framework addresses the limitations of traditional Transformer models that often underrepresent extreme patterns by treating all time points uniformly. Exformer incorporates a novel extreme-adaptive attention mechanism to explicitly model dependencies between normal and extreme events.
Yuxinlu1 has released Gemma4-12B v2, an updated GGUF model focused on agentic coding and tool-use capabilities. This iteration significantly improves performance on technical-agentic tasks compared to its base model, making advanced AI agent functionality accessible on local hardware with minimal VRAM requirements. The model is designed for multi-step technical tasks, debugging, and code generation.
Empero AI has released Qwythos-9B-Claude-Mythos-5-1M-GGUF, a quantized version of their 9B parameter reasoning model. This model features a 1M token context window, native function calling, and multimodal image input, making it suitable for local deployment on various GGUF-compatible runtimes.
New research challenges the prevailing understanding of performance improvements in self-alignment methods for diffusion transformers. Contrary to previous assumptions, the gains from methods like Self-Flow over SRA appear to stem primarily from data augmentation along the noise dimension, rather than interactions between tokens at different noise levels. The introduction of 'Attention Separation' demonstrates that blocking such interactions can even improve performance, highlighting the role of augmentation.