Trending Research
SmoothQuant: Accurate and Efficient Post-Training Quantization for Large Language Models
BlinkDL/RWKV-LM
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We propose SmoothQuant, a training-free, accuracy-preserving, and general-purpose post-training quantization (PTQ) solution to enable 8-bit weight, 8-bit activation (W8A8) quantization for LLMs that can be implemented efficiently.
RAVE: A variational autoencoder for fast and high-quality neural audio synthesis
By leveraging a multi-band decomposition of the raw waveform, we show that our model is the first able to generate 48kHz audio signals, while simultaneously running 20 times faster than real-time on a standard laptop CPU.
ExaRanker: Explanation-Augmented Neural Ranker
Recent work has shown that inducing a large language model (LLM) to generate explanations prior to outputting an answer is an effective strategy to improve performance on a wide range of reasoning tasks.
Synthcity: facilitating innovative use cases of synthetic data in different data modalities
Synthcity is an open-source software package for innovative use cases of synthetic data in ML fairness, privacy and augmentation across diverse tabular data modalities, including static data, regular and irregular time series, data with censoring, multi-source data, composite data, and more.
GLIGEN: Open-Set Grounded Text-to-Image Generation
Large-scale text-to-image diffusion models have made amazing advances.
Ranked #1 on
Text-to-Image Generation
on COCO
Multiview Compressive Coding for 3D Reconstruction
We introduce a simple framework that operates on 3D points of single objects or whole scenes coupled with category-agnostic large-scale training from diverse RGB-D videos.
Tune-A-Video: One-Shot Tuning of Image Diffusion Models for Text-to-Video Generation
To reproduce the success of text-to-image (T2I) generation, recent works in text-to-video (T2V) generation employ large-scale text-video dataset for fine-tuning.
Instant Neural Graphics Primitives with a Multiresolution Hash Encoding
nerfstudio-project/nerfstudio
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Neural graphics primitives, parameterized by fully connected neural networks, can be costly to train and evaluate.
SensorX2car: Sensors-to-car calibration for autonomous driving in road scenarios
To this end, we present SensorX2car, a calibration toolbox for the online calibration of sensor-to-car coordinate systems in road scenes.
CodeGen: An Open Large Language Model for Code with Multi-Turn Program Synthesis
To democratize this, we train and release a family of large language models up to 16. 1B parameters, called CODEGEN, on natural language and programming language data, and open source the training library JAXFORMER.
Ranked #1 on
Program Synthesis
on HumanEval
