Trending Research
DoRA: Weight-Decomposed Low-Rank Adaptation
NVlabs/DoRA
•
•
By employing DoRA, we enhance both the learning capacity and training stability of LoRA while avoiding any additional inference overhead.
MemGPT: Towards LLMs as Operating Systems
Large language models (LLMs) have revolutionized AI, but are constrained by limited context windows, hindering their utility in tasks like extended conversations and document analysis.
Visual Autoregressive Modeling: Scalable Image Generation via Next-Scale Prediction
We present Visual AutoRegressive modeling (VAR), a new generation paradigm that redefines the autoregressive learning on images as coarse-to-fine "next-scale prediction" or "next-resolution prediction", diverging from the standard raster-scan "next-token prediction".
Ranked #7 on
Image Generation
on ImageNet 256x256
WavCraft: Audio Editing and Generation with Natural Language Prompts
We introduce WavCraft, a collective system that leverages large language models (LLMs) to connect diverse task-specific models for audio content creation and editing.
TensorIR: An Abstraction for Automatic Tensorized Program Optimization
mlc-ai/web-llm
•
•
Finally, we build an end-to-end framework on top of our abstraction to automatically optimize deep learning models for given tensor computation primitives.
SUQL: Conversational Search over Structured and Unstructured Data with Large Language Models
This paper presents the first conversational agent that supports the full generality of hybrid data access for large knowledge corpora, through a language we developed called SUQL (Structured and Unstructured Query Language).
Lightplane: Highly-Scalable Components for Neural 3D Fields
facebookresearch/lightplane
•
•
Contemporary 3D research, particularly in reconstruction and generation, heavily relies on 2D images for inputs or supervision.
Transcending Forgery Specificity with Latent Space Augmentation for Generalizable Deepfake Detection
Deepfake detection faces a critical generalization hurdle, with performance deteriorating when there is a mismatch between the distributions of training and testing data.
Groma: Localized Visual Tokenization for Grounding Multimodal Large Language Models
We introduce Groma, a Multimodal Large Language Model (MLLM) with grounded and fine-grained visual perception ability.
AgentScope: A Flexible yet Robust Multi-Agent Platform
With the rapid advancement of Large Language Models (LLMs), significant progress has been made in multi-agent applications.
