KI-Forschungspapiere Täglich

Qwen2.5-1M Technical Report

Baichuan-Omni-1.5 Technical Report

Towards General-Purpose Model-Free Reinforcement Learning

ARWKV: Pretrain is not what we need, an RNN-Attention-Based Language Model Born from Transformer

Emilia: A Large-Scale, Extensive, Multilingual, and Diverse Dataset for Speech Generation

iFormer: Integrating ConvNet and Transformer for Mobile Application

Parameters vs FLOPs: Scaling Laws for Optimal Sparsity for Mixture-of-Experts Language Models

CodeMonkeys: Scaling Test-Time Compute for Software Engineering

Are Vision Language Models Texture or Shape Biased and Can We Steer Them?

Mixture-of-Mamba: Enhancing Multi-Modal State-Space Models with Modality-Aware Sparsity

Visual Generation Without Guidance

OpenCharacter: Training Customizable Role-Playing LLMs with Large-Scale Synthetic Personas

Return of the Encoder: Maximizing Parameter Efficiency for SLMs

Feasible Learning