Trending Research
Efficient Reasoning Models: A Survey
Reasoning models have demonstrated remarkable progress in solving complex and logic-intensive tasks by generating extended Chain-of-Thoughts (CoTs) prior to arriving at a final answer.
MinerU: An Open-Source Solution for Precise Document Content Extraction
Document content analysis has been a crucial research area in computer vision.
Olympus: A Universal Task Router for Computer Vision Tasks
We introduce Olympus, a new approach that transforms Multimodal Large Language Models (MLLMs) into a unified framework capable of handling a wide array of computer vision tasks.
MetaSpatial: Reinforcing 3D Spatial Reasoning in VLMs for the Metaverse
hiyouga/easyr1
•
•
We present MetaSpatial, the first reinforcement learning (RL)-based framework designed to enhance 3D spatial reasoning in vision-language models (VLMs), enabling real-time 3D scene generation without the need for hard-coded optimizations.
InfiniteYou: Flexible Photo Recrafting While Preserving Your Identity
Achieving flexible and high-fidelity identity-preserved image generation remains formidable, particularly with advanced Diffusion Transformers (DiTs) like FLUX.
DeepResearcher: Scaling Deep Research via Reinforcement Learning in Real-world Environments
In this paper, we introduce DeepResearcher, the first comprehensive framework for end-to-end training of LLM-based deep research agents through scaling reinforcement learning (RL) in real-world environments with authentic web search interactions.
Holistic Fusion: Task- and Setup-Agnostic Robot Localization and State Estimation with Factor Graphs
Seamless operation of mobile robots in challenging environments requires low-latency local motion estimation (e. g., dynamic maneuvers) and accurate global localization (e. g., wayfinding).
Taccel: Scaling Up Vision-based Tactile Robotics via High-performance GPU Simulation
Tactile sensing is crucial for achieving human-level robotic capabilities in manipulation tasks.
TabPFN: A Transformer That Solves Small Tabular Classification Problems in a Second
automl/tabpfn
•
•
We present TabPFN, a trained Transformer that can do supervised classification for small tabular datasets in less than a second, needs no hyperparameter tuning and is competitive with state-of-the-art classification methods.
TorchFX: A modern approach to Audio DSP with PyTorch and GPU acceleration
In response, we introduce TorchFX: a GPU-accelerated Python library for DSP, specifically engineered to facilitate sophisticated audio signal processing.
