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[Up-to-date] Large Language Model Agent: A Survey on Methodology, Applications and Challenges
Cache-Augmented Generation: A Simple, Efficient Alternative to RAG
EasyR1: An Efficient, Scalable, Multi-Modality RL Training Framework based on veRL
📚Modern CUDA Learn Notes: 200+ Tensor/CUDA Cores Kernels🎉, HGEMM, FA2 via MMA and CuTe, 98~100% TFLOPS of cuBLAS/FA2.
Official Pytorch Implementation of "OwLore: Outlier-weighed Layerwise Sampled Low-Rank Projection for Memory-Efficient LLM Fine-tuning" by Pengxiang Li, Lu Yin, Xiaowei Gao, Shiwei Liu
Official implementation of paper "VLA-Cache: Towards Efficient Vision-Language-Action Model via Adaptive Token Caching in Robotic Manipulation"
6
Updated Mar 24, 2025
"PhD-Level AI Agents: Fully-Automated Scientific Discovery with Our AI-Researcher Powered by LLMs"
[NeurIPS 2024] NAVSIM: Data-Driven Non-Reactive Autonomous Vehicle Simulation and Benchmarking
Latest Advances on Vison-Language-Action Models.
AlignCLIP: Improving Cross-Modal Alignment in CLIP (ICLR 2025)
OpenEMMA, a permissively licensed open source "reproduction" of Waymo’s EMMA model.
Zero-Shot Detection via Vision and Language Knowledge Distillation
【EMNLP 2024🔥】Video-LLaVA: Learning United Visual Representation by Alignment Before Projection
[CVPR 2025 Highlight] Truncated Diffusion Model for Real-Time End-to-End Autonomous Driving
AMD 0.9B efficient text to video diffusion model
Recent Advances on MLLM's Reasoning Ability
24
Updated Apr 7, 2025
A framework for few-shot evaluation of language models.
[NeurIPS '18] "Can We Gain More from Orthogonality Regularizations in Training Deep CNNs?" Official Implementation.
Preventing Dimensional Collapse in Self-Supervised Learning via Orthogonality Regularization
1
Updated Oct 31, 2024
Search-o1: Agentic Search-Enhanced Large Reasoning Models
Source code for models described in the paper "AudioCLIP: Extending CLIP to Image, Text and Audio" (https://arxiv.org/abs/2106.13043)
[CVPR 2025] LamRA: Large Multimodal Model as Your Advanced Retrieval Assistant
🚀 Efficient implementations of state-of-the-art linear attention models in Torch and Triton
[AAAI Alignment Track 25 Poster] Stream Aligner: Efficient Sentence-Level Alignment via Distribution Induction