Trending Research
Branch-Train-MiX: Mixing Expert LLMs into a Mixture-of-Experts LLM
Leeroo-AI/mergoo
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We investigate efficient methods for training Large Language Models (LLMs) to possess capabilities in multiple specialized domains, such as coding, math reasoning and world knowledge.
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Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models
google-deepmind/recurrentgemma
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Recurrent neural networks (RNNs) have fast inference and scale efficiently on long sequences, but they are difficult to train and hard to scale.
Cross-Attention Makes Inference Cumbersome in Text-to-Image Diffusion Models
This study explores the role of cross-attention during inference in text-conditional diffusion models.
Retrieval-Augmented Generation for AI-Generated Content: A Survey
We first classify RAG foundations according to how the retriever augments the generator, distilling the fundamental abstractions of the augmentation methodologies for various retrievers and generators.
AIOS: LLM Agent Operating System
Inspired by these challenges, this paper presents AIOS, an LLM agent operating system, which embeds large language model into operating systems (OS) as the brain of the OS, enabling an operating system "with soul" -- an important step towards AGI.
SafeGen: Mitigating Unsafe Content Generation in Text-to-Image Models
letterligo/text-agnostic-governance
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The key idea is to eliminate unsafe visual representations from the model regardless of the text input.
Matching 2D Images in 3D: Metric Relative Pose from Metric Correspondences
Usually, correspondences are 2D-to-2D and the pose we estimate is defined only up to scale.
PCToolkit: A Unified Plug-and-Play Prompt Compression Toolkit of Large Language Models
3DAgentWorld/Toolkit-for-Prompt-Compression
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Prompt compression is an innovative method for efficiently condensing input prompts while preserving essential information.
SchurVINS: Schur Complement-Based Lightweight Visual Inertial Navigation System
To this end, we propose a novel filter-based VINS framework named SchurVINS, which could guarantee both high accuracy by building a complete residual model and low computational complexity with Schur complement.
Champ: Controllable and Consistent Human Image Animation with 3D Parametric Guidance
fudan-generative-vision/champ
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In this study, we introduce a methodology for human image animation by leveraging a 3D human parametric model within a latent diffusion framework to enhance shape alignment and motion guidance in curernt human generative techniques.
