Trending Research
NExT-GPT: Any-to-Any Multimodal LLM
While recently Multimodal Large Language Models (MM-LLMs) have made exciting strides, they mostly fall prey to the limitation of only input-side multimodal understanding, without the ability to produce content in multiple modalities.
Show-1: Marrying Pixel and Latent Diffusion Models for Text-to-Video Generation
In this paper, we are the first to propose a hybrid model, dubbed as Show-1, which marries pixel-based and latent-based VDMs for text-to-video generation.
Ranked #1 on
Text-to-Video Generation
on MSR-VTT
QA-LoRA: Quantization-Aware Low-Rank Adaptation of Large Language Models
Recently years have witnessed a rapid development of large language models (LLMs).
Demonstrate-Search-Predict: Composing retrieval and language models for knowledge-intensive NLP
stanfordnlp/dspy
•
•
Retrieval-augmented in-context learning has emerged as a powerful approach for addressing knowledge-intensive tasks using frozen language models (LM) and retrieval models (RM).
FreeU: Free Lunch in Diffusion U-Net
ChenyangSi/FreeU
•
•
In this paper, we uncover the untapped potential of diffusion U-Net, which serves as a "free lunch" that substantially improves the generation quality on the fly.
What Makes Good In-Context Examples for GPT-$3$?
stanfordnlp/dsp
•
•
Inspired by the recent success of leveraging a retrieval module to augment large-scale neural network models, we propose to retrieve examples that are semantically-similar to a test sample to formulate its corresponding prompt.
ReConcile: Round-Table Conference Improves Reasoning via Consensus among Diverse LLMs
We also experiment with GPT-4 itself as one of the agents in ReConcile and demonstrate that its initial performance also improves by absolute 10. 0% through discussion and feedback from other agents.
Agents: An Open-source Framework for Autonomous Language Agents
Recent advances on large language models (LLMs) enable researchers and developers to build autonomous language agents that can automatically solve various tasks and interact with environments, humans, and other agents using natural language interfaces.
NeuRBF: A Neural Fields Representation with Adaptive Radial Basis Functions
oppo-us-research/NeuRBF
•
•
ICCV 2023
The spatial positions of their neural features are fixed on grid nodes and cannot well adapt to target signals.
Retinexformer: One-stage Retinex-based Transformer for Low-light Image Enhancement
caiyuanhao1998/retinexformer
•
•
ICCV 2023
When enhancing low-light images, many deep learning algorithms are based on the Retinex theory.
Ranked #1 on
Low-Light Image Enhancement
on LOL-v2-synthetic
