Trending Research
Granite Code Models: A Family of Open Foundation Models for Code Intelligence
Increasingly, code LLMs are being integrated into software development environments to improve the productivity of human programmers, and LLM-based agents are beginning to show promise for handling complex tasks autonomously.
EfficientTrain++: Generalized Curriculum Learning for Efficient Visual Backbone Training
These patterns, when observed through frequency and spatial domains, incorporate lower-frequency components, and the natural image contents without distortion or data augmentation.
SceneTracker: Long-term Scene Flow Estimation Network
Considering the complementarity of scene flow estimation in the spatial domain's focusing capability and 3D object tracking in the temporal domain's coherence, this study aims to address a comprehensive new task that can simultaneously capture fine-grained and long-term 3D motion in an online manner: long-term scene flow estimation (LSFE).
VILA: On Pre-training for Visual Language Models
efficient-large-model/vila
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Visual language models (VLMs) rapidly progressed with the recent success of large language models.
Ranked #24 on
Visual Question Answering
on MM-Vet
InstantMesh: Efficient 3D Mesh Generation from a Single Image with Sparse-view Large Reconstruction Models
We present InstantMesh, a feed-forward framework for instant 3D mesh generation from a single image, featuring state-of-the-art generation quality and significant training scalability.
WavCraft: Audio Editing and Generation with Large Language Models
We introduce WavCraft, a collective system that leverages large language models (LLMs) to connect diverse task-specific models for audio content creation and editing.
Xmodel-VLM: A Simple Baseline for Multimodal Vision Language Model
We introduce Xmodel-VLM, a cutting-edge multimodal vision language model.
Vidur: A Large-Scale Simulation Framework For LLM Inference
Vidur models the performance of LLM operators using a combination of experimental profiling and predictive modeling, and evaluates the end-to-end inference performance for different workloads by estimating several metrics of interest such as latency and throughput.
PHUDGE: Phi-3 as Scalable Judge
In this paper cum technical report, we present PHUDGE A fine tuned Phi3 model that achieved SOTA results in 4 tasks as Feedback Test, Feedback OOD, MT Human, Preference Test surpassing each and every existing model in latency and throughput.
Improving Diffusion Models for Virtual Try-on
yisol/IDM-VTON
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Finally, we present a customization method using a pair of person-garment images, which significantly improves fidelity and authenticity.
Ranked #1 on
Virtual Try-on
on VITON-HD
