诺亚盘古大模型研发背后的真正的心酸与黑暗的故事。

EasyR1: An Efficient, Scalable, Multi-Modality RL Training Framework based on veRL

[ICCV 2025] Official code of "ORION: A Holistic End-to-End Autonomous Driving Framework by Vision-Language Instructed Action Generation"

The official implementation of [Quality over Quantity: Boosting Data Efficiency Through Ensembled Multimodal Data Curation] in AAAI2025.

Closed-loop evaluation for end-to-end VLM autonomous driving agent

OpenEMMA, a permissively licensed open source "reproduction" of Waymo’s EMMA model.

HE-Drive: Human-Like End-to-End Driving with Vision Language Models

Unified Efficient Fine-Tuning of 100+ LLMs & VLMs (ACL 2024)

[CVPR 2024] LMDrive: Closed-Loop End-to-End Driving with Large Language Models

LLaMA-Omni is a low-latency and high-quality end-to-end speech interaction model built upon Llama-3.1-8B-Instruct, aiming to achieve speech capabilities at the GPT-4o level.

[ACL 2024 (Findings)] ICC: Quantifying Image Caption Concreteness for Multimodal Dataset Curation

This is an official pytorch implementation of TCA-Net: Triplet Concatenated-Attentional Network for Multimodal Engagement Estimation.

[NeurIPS 2024] MoVA: Adapting Mixture of Vision Experts to Multimodal Context

A Framework of Small-scale Large Multimodal Models

Scenario Understanding with Visual-Question-Answering Base on Visual Instruction Tuning (LLaVA) built towards GPT-4V level capabilities and beyond.

This research project has constructed a two-stage clustering-based retrieval framework, as well as a deep learning-based retrieval algorithm using the CLIP model, which demonstrates zero-shot abili…

LAVIS - A One-stop Library for Language-Vision Intelligence

最完整的AI算法面试题目仓库，1000道，25个类目

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This research presents probabilistic machine learning methods to optimize basic image ranking models. And make it suitable for visual navigation and exploration tasks in the real complex world.

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