Trending Research
FreGrad: Lightweight and Fast Frequency-aware Diffusion Vocoder
The goal of this paper is to generate realistic audio with a lightweight and fast diffusion-based vocoder, named FreGrad.
Taming Stable Diffusion for Text to 360° Panorama Image Generation
Generative models, e. g., Stable Diffusion, have enabled the creation of photorealistic images from text prompts.
Prompts As Programs: A Structure-Aware Approach to Efficient Compile-Time Prompt Optimization
We show that SAMMO generalizes previous methods and improves the performance of complex prompts on (1) instruction tuning, (2) RAG pipeline tuning, and (3) prompt compression, across several different LLMs.
TFB: Towards Comprehensive and Fair Benchmarking of Time Series Forecasting Methods
Next, we employ TFB to perform a thorough evaluation of 21 Univariate Time Series Forecasting (UTSF) methods on 8, 068 univariate time series and 14 Multivariate Time Series Forecasting (MTSF) methods on 25 datasets.
AniPortrait: Audio-Driven Synthesis of Photorealistic Portrait Animation
In this study, we propose AniPortrait, a novel framework for generating high-quality animation driven by audio and a reference portrait image.
DUSt3R: Geometric 3D Vision Made Easy
naver/dust3r
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Our formulation directly provides a 3D model of the scene as well as depth information, but interestingly, we can seamlessly recover from it, pixel matches, relative and absolute camera.
emotion2vec: Self-Supervised Pre-Training for Speech Emotion Representation
alibaba-damo-academy/FunASR
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To the best of our knowledge, emotion2vec is the first universal representation model in various emotion-related tasks, filling a gap in the field.
BGE M3-Embedding: Multi-Lingual, Multi-Functionality, Multi-Granularity Text Embeddings Through Self-Knowledge Distillation
It can simultaneously perform the three common retrieval functionalities of embedding model: dense retrieval, multi-vector retrieval, and sparse retrieval, which provides a unified model foundation for real-world IR applications.
A Survey on Deep Learning for Theorem Proving
Theorem proving is a fundamental aspect of mathematics, spanning from informal reasoning in mathematical language to rigorous derivations in formal systems.
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.
