Trending Research
How Close is ChatGPT to Human Experts? Comparison Corpus, Evaluation, and Detection
We call the collected dataset the Human ChatGPT Comparison Corpus (HC3).
Salesforce CausalAI Library: A Fast and Scalable Framework for Causal Analysis of Time Series and Tabular Data
We introduce the Salesforce CausalAI Library, an open-source library for causal analysis using observational data.
Diffusion Models for Causal Discovery via Topological Ordering
vios-s/diffan
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Topological ordering approaches for causal discovery exploit this by performing graph discovery in two steps, first sequentially identifying nodes in reverse order of depth (topological ordering), and secondly pruning the potential relations.
Robust Speech Recognition via Large-Scale Weak Supervision
openai/whisper
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Preprint 2022
We study the capabilities of speech processing systems trained simply to predict large amounts of transcripts of audio on the internet.
Ranked #1 on
Speech Recognition
on CHiME6
LION: Latent Point Diffusion Models for 3D Shape Generation
nv-tlabs/LION
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To advance 3D DDMs and make them useful for digital artists, we require (i) high generation quality, (ii) flexibility for manipulation and applications such as conditional synthesis and shape interpolation, and (iii) the ability to output smooth surfaces or meshes.
Ranked #1 on
Point Cloud Generation
on ShapeNet
Is ChatGPT A Good Translator? A Preliminary Study
This report provides a preliminary evaluation of ChatGPT for machine translation, including translation prompt, multilingual translation, and translation robustness.
Generate rather than Retrieve: Large Language Models are Strong Context Generators
We call our method generate-then-read (GenRead), which first prompts a large language model to generate contextutal documents based on a given question, and then reads the generated documents to produce the final answer.
LAION-5B: An open large-scale dataset for training next generation image-text models
mlfoundations/open_clip
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NeurIPS 2022 Datasets and Benchmarks 2022
We show successful replication and fine-tuning of foundational models like CLIP, GLIDE and Stable Diffusion using the dataset, and discuss further experiments enabled with an openly available dataset of this scale.
KERPLE: Kernelized Relative Positional Embedding for Length Extrapolation
Relative positional embeddings (RPE) have received considerable attention since RPEs effectively model the relative distance among tokens and enable length extrapolation.
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.
