Awesome NeurIPS 2023 Info

Caption: Wordcloud of all NeurIPS 2023 titles

Welcome to the hub for all things NeurIPS 2023! We scraped the data for all 3500+ NeurIPS projects and dove into the depths of Hugging Face, GitHub, LinkedIn, and Arxiv to pick out the most interesting content.

In this repo, you will find:

Data Analysis: detailed analysis of the titles and abstracts from NeurIPS 2023 accepted papers
Awesome Projects: synthesized collection of 40 NeurIPS 2023 papers you won't want to miss
Conference Schedule: comprehensive listing of all NeurIPS 2023 projects (title, authors, abstract) organized by poster session and sorted alphabetically

Data Analysis

The raw data is included in this repo. If you have ideas for other interesting analyses, feel free to create an issue or submit a PR!

For now, insights are organized into the following categories:

Authors
Titles
Abstracts

For the data analysis itself, check out the Jupyter Notebook!

Authors

Most prolific authors

The top 10 authors with the most papers at NeurIPS 2023 are:

Bo Li: 15 papers
Ludwig Schmidt: 14 papers
Bo Han: 13 papers
Mihaela van der Schaar: 13 papers
Hao Wang: 12 papers
Dacheng Tao: 11 papers
Bernhard Schölkopf: 11 papers
Masashi Sugiyama: 11 papers
Andreas Krause: 11 papers
Tongliang Liu: 11 papers

Number of unique authors

There were 13,012 unique authors at NeurIPS 2023, up from 9913 at NeurIPS 2022.

This continues the exponential explosion of unique authors over the past decade.

Number of authors per paper

The average number of authors per paper was 4.98, up from 4.66 at NeurIPS 2022.
Additionally, there were a handful of single-author papers, in contrast to NeurIPS 2022, where the minimum number of authors was 2.
The paper with the most authors was ClimSim: A large multi-scale dataset for hybrid physics-ML climate emulation

Titles

Title Length

The average title length was 8.72 words, up from 8.48 at NeurIPS 2022. This continues an ongoing trend of title lengthening:

Prevalence of Acronyms

22% of titles introduced an acronym, up from 18% at NeurIPS 2022.

LaTeX in Titles

1.3% of titles contained LaTeX, whereas none of the titles at NeurIPS 2022 contained LaTeX.

Abstracts

Abstract Length

The longest abstract was from [Re] On the Reproducibility of FairCal: Fairness Calibration for Face Verification, which has 373 words.
The shortest abstract was from Improved Convergence in High Probability of Clipped Gradient Methods with Heavy Tailed Noise, which has 29 words.

GitHub Reigns Supreme

Out of the 3581 abstracts, 675 explicitly mention GitHub, including a link to their code, models, or data.
Only 79 abstracts include a URL that is not GitHub.

Modalities, Models, and Tasks

Using a CLIP model, we zero-shot classified/predicted the modality of focus for each paper based on its abstract. The categories were ["vision", "text", "audio", "tabular", "time series", "multimodal"].

By far the biggest category was multimodal, with a count of 1296. However, the CLIP model's inclination towards "multimodal" may be somewhat biased by trying to partially fit other modalities — the words multi-modal and multimodal only show up in 156 abstracts, and phrases like vision-language and text-to-image only appear a handful of times across the dataset.

Themes occurring frequently include:

"benchmark": 730
("generation", "generate"): 681
("efficient", "efficiency"): 963
"agent": 280
("llm", "large language model"): 238

Cool NeurIPS Projects

Title	Paper	Code	Project Page	Hugging Face
An Inverse Scaling Law for CLIP Training
Augmenting Language Models with Long-Term Memory
Chameleon: Plug-and-Play Compositional Reasoning with Large Language Models			Project
Cheap and Quick: Efficient Vision-Language Instruction Tuning for Large Language Models			Project
DataComp: In search of the next generation of multimodal datasets			Project
Direct Preference Optimization: Your Language Model is Secretly a Reward Model
DreamSim: Learning New Dimensions of Human Visual Similarity using Synthetic Data			Project
Fine-Tuning Language Models with Just Forward Passes
Generating Images with Multimodal Language Models			Project
Holistic Evaluation of Text-To-Image Models			Project
HuggingGPT: Solving AI Tasks with ChatGPT and its Friends in Hugging Face
ImageReward: Learning and Evaluating Human Preferences for Text-to-Image Generation
InstructBLIP: Towards General-purpose Vision-Language Models with Instruction Tuning
Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena
LAMM: Multi-Modal Large Language Models and Applications as AI Agents			Project
LIMA: Less Is More for Alignment
LLM-Pruner: On the Structural Pruning of Large Language Models
LightZero: A Unified Benchmark for Monte Carlo Tree Search in General Sequential Decision Scenario
MVDiffusion: Enabling Holistic Multi-view Image Generation with Correspondence-Aware Diffusion			Project
MagicBrush: A Manually Annotated Dataset for Instruction-Guided Image Editing			Project
Mathematical Capabilities of ChatGPT			Project
Michelangelo: Conditional 3D Shape Generation based on Shape-Image-Text Aligned Latent Representation			Project
Motion-X: A Large-scale 3D Expressive Whole-body Human Motion Dataset			Project
MotionGPT: Human Motion as Foreign Language			Project
OBELICS: An Open Web-Scale Filtered Dataset of Interleaved Image-Text Documents
Photoswap: Personalized Subject Swapping in Images			Project
Pick-a-Pic: An Open Dataset of User Preferences for Text-to-Image Generation
QLoRA: Efficient Finetuning of Quantized LLMs
Reflexion: Language Agents with Verbal Reinforcement Learning
ResShift: Efficient Diffusion Model for Image Super-resolution by Residual Shifting			Project
Segment Anything in 3D with NeRFs			Project
Segment Anything in High Quality
Segment Everything Everywhere All at Once
Self-Refine: Iterative Refinement with Self-Feedback			Project
Simple and Controllable Music Generation
Squeeze, Recover and Relabel : Dataset Condensation at ImageNet Scale From A New Perspective
The RefinedWeb Dataset for Falcon LLM: Outperforming Curated Corpora with Web Data, and Web Data Only
Toolformer: Language Models Can Teach Themselves to Use Tools
Unlimiformer: Long-Range Transformers with Unlimited Length Input
Visual Instruction Tuning			Project