# NeurIPS

> Source: https://aiwiki.ai/wiki/neurips
> Updated: 2026-06-20
> Categories: Artificial Intelligence, Machine Learning
> From AI Wiki (https://aiwiki.ai), a free encyclopedia of artificial intelligence. Quote with attribution.

**NeurIPS** (the Conference on Neural Information Processing Systems) is the largest and one of the most prestigious academic conferences in [artificial intelligence](/wiki/artificial_intelligence) and [machine learning](/wiki/machine_learning), drawing more than 21,000 paper submissions and well over 15,000 attendees per year. Held annually in December, it is, along with [ICLR](/wiki/iclr) and [ICML](/wiki/icml), "one of the three primary conferences of high impact in machine learning and artificial intelligence research" [11]. NeurIPS covers topics spanning machine learning, computational neuroscience, statistics, optimization, computer vision, [natural language processing](/wiki/natural_language_processing), and [reinforcement learning](/wiki/reinforcement_learning), and it is the venue where landmark systems such as AlexNet (2012), generative adversarial networks (2014), and the [Transformer](/wiki/transformer) (2017) were first published [1].

The conference was originally known as NIPS (Neural Information Processing Systems) from its founding in 1987 until 2018, when it was renamed to NeurIPS following community concerns about the original acronym.

## What is NeurIPS?

NeurIPS is a peer-reviewed, week-long scientific conference held each December that serves as the leading global forum for new research in machine learning and neural computation. Its 2025 edition (the 39th) received 21,575 valid main-track submissions and accepted 5,290 papers, a 24.52% acceptance rate [12]. Participation spans academia and industry in roughly equal measure, making NeurIPS a primary bridge between fundamental AI research and applied systems built by labs such as [Google](/wiki/google) DeepMind, [Meta](/wiki/meta) AI, [Microsoft](/wiki/microsoft) Research, and [OpenAI](/wiki/openai).

## History

### Founding

The conference traces its origins to 1986, when the idea for an annual meeting on neural information processing was proposed at the Snowbird Meeting on Neural Networks for Computing, organized by the California Institute of Technology and Bell Laboratories. The first NIPS conference was held in 1987 in Denver, Colorado, sponsored by the IEEE Information Theory Group. Ed Posner of Caltech served as the founding general chairman [2].

In its early years, NIPS was a relatively small gathering focused on the intersection of neuroscience and computation. The conference grew steadily through the 1990s and 2000s as neural network research experienced its ups and downs. The deep learning revolution that began around 2012 transformed NeurIPS into a massive event, with attendance growing from approximately 2,000 in 2012 to over 16,000 by 2024.

### When and why did NIPS change its name to NeurIPS?

The conference operated under the acronym NIPS for over three decades. In March 2018, a letter to the board signed by professors and students at Johns Hopkins University and other institutions called for a name change, arguing that the acronym had become "vulnerable to sexual puns" and risked a hostile environment [3]. After collecting community input and running an online poll that produced no clear consensus, the board initially announced in October 2018 that it would keep the name. The decision reversed within weeks following a #ProtestNIPS campaign and Change.org petition organized in part by NVIDIA director of machine learning research Anima Anandkumar [13].

On November 16, 2018, the board announced the new acronym, NeurIPS, and the official website moved from nips.cc to neurips.cc [13]. In its statement the board explained that the new name had not been imposed but had emerged from the community itself: "The name NeurIPS has sprung up organically as an alternative acronym, and we're delighted to see it being adopted." [13]

## Notable Papers

NeurIPS has served as the venue for many of the most influential papers in the history of machine learning and artificial intelligence. The following table highlights landmark papers presented at the conference:

| Year | Paper | Authors | Significance |
|---|---|---|---|
| 1987 | "Learning representations by back-propagating errors" (related work presented) | Rumelhart, Hinton, Williams | Early NeurIPS helped popularize [backpropagation](/wiki/backpropagation), which became the foundation of neural network training |
| 2001 | "Latent Dirichlet Allocation" | Blei, Ng, Jordan | Foundational topic modeling method that shaped probabilistic machine learning for a decade |
| 2012 | "ImageNet Classification with Deep Convolutional Neural Networks" ([AlexNet](/wiki/alexnet)) | Krizhevsky, Sutskever, Hinton | Launched the [deep learning](/wiki/deep_learning) revolution by winning ImageNet with a CNN, reducing error by a dramatic margin |
| 2014 | "Generative Adversarial Nets" | Goodfellow, Pouget-Abadie, Mirza, Xu, Warde-Farley, Ozair, Courville, Bengio | Introduced [GANs](/wiki/generative_adversarial_network), one of the most influential generative model frameworks |
| 2014 | "Sequence to Sequence Learning with Neural Networks" | Sutskever, Vinyals, Le | Established the encoder-decoder paradigm for neural machine translation |
| 2015 | "Deep Reinforcement Learning with Double Q-Learning" | van Hasselt, Guez, Silver | Advanced deep RL by addressing overestimation bias in Q-learning |
| 2017 | "Attention Is All You Need" | Vaswani, Shazeer, Parmar, Uszkoreit, Jones, Gomez, Kaiser, Polosukhin | Introduced the [Transformer](/wiki/transformer) architecture, the foundation of virtually all modern [LLMs](/wiki/large_language_model); cited more than 250,000 times as of 2026, placing it among the ten most-cited papers of the 21st century [4][14] |
| 2020 | "Language Models are Few-Shot Learners" ([GPT-3](/wiki/gpt-3)) | Brown, Mann, Ryder, Subbiah, et al. | Demonstrated that scaling language models enables few-shot learning across many tasks |
| 2022 | "FlashAttention: Fast and Memory-Efficient Exact Attention with IO-Awareness" | Dao, Fu, Ermon, Rudra, Re | Introduced IO-aware attention computation that dramatically reduced memory usage and improved speed for transformer training and inference [5] |
| 2023 | "Direct Preference Optimization: Your Language Model is Secretly a Reward Model" ([DPO](/wiki/dpo)) | Rafailov, Sharma, Mitchell, Manning, Ermon, Finn | Simplified [RLHF](/wiki/rlhf) alignment by eliminating the need for a separate reward model [6] |
| 2024 | "Visual Autoregressive Modeling: Scalable Image Generation via Next-Scale Prediction" | Various | Best Paper at NeurIPS 2024; advanced autoregressive image generation |

## Conference Format

NeurIPS follows a multi-track format spanning approximately one week, typically in early to mid-December. The conference structure includes several components:

### Main Conference (3 days)

The core of NeurIPS consists of:

- **Oral presentations**: The top approximately 1% of accepted papers are selected for oral presentation, where authors give talks to the full conference audience. At NeurIPS 2025, 61 papers received oral designation out of over 5,200 accepted papers.
- **Spotlight presentations**: The next tier (roughly the top 10% of accepted papers) receive spotlight status, consisting of shorter talks. NeurIPS 2025 designated 327 spotlight papers.
- **Poster sessions**: All accepted papers are presented in large poster halls, where authors discuss their work one-on-one with attendees. This is where much of the substantive technical discussion happens.
- **Invited talks**: Prominent researchers deliver keynote-style presentations on broad topics.

### Workshops (2 days)

The days following the main conference feature dozens of parallel workshops on specialized topics. Workshops are smaller, more interactive venues that often focus on emerging areas. They have their own submission and review processes, and many important research directions first coalesce at NeurIPS workshops before becoming mainstream.

### Tutorials (1 day)

The day before the main conference features tutorials: half-day or full-day instructional sessions led by experts on specific topics. These are designed to bring attendees up to speed on active research areas.

### Competitions and Challenges

NeurIPS hosts a series of competitions where participants tackle specific problems, often with standardized benchmarks and evaluation criteria. Notable competition tracks have included:

- The NeurIPS Large Language Model Efficiency Challenge
- Machine Learning for Science competitions
- Reinforcement learning challenges (e.g., MineRL, NetHack)

### Expo

An industry expo runs alongside the conference, where companies present their AI research, products, and job opportunities. Major technology companies, AI startups, and research labs maintain booths and host presentations. The expo has grown substantially as industry investment in AI has increased.

## Acceptance Rates and Scale

NeurIPS has experienced dramatic growth in submissions over the past decade, reflecting the explosion of interest in machine learning research:

| Year | Submissions | Accepted | Acceptance Rate | Attendees |
|---|---|---|---|---|
| 2015 | 1,838 | 403 | 21.9% | ~3,800 |
| 2017 | 3,240 | 678 | 20.9% | ~8,000 |
| 2019 | 6,743 | 1,428 | 21.2% | ~13,000 |
| 2021 | 9,122 | 2,344 | 25.7% | ~21,000 (virtual) |
| 2022 | 10,411 | 2,672 | 25.7% | ~10,000 |
| 2023 | 12,343 | 3,218 | 26.1% | ~16,000 |
| 2024 | 15,671 | ~4,000 | 25.8% | ~16,000 |
| 2025 | 21,575 | 5,290 | 24.5% | ~18,000 |

The acceptance rate has remained remarkably stable at approximately 24% to 26% despite the explosive growth in submissions [7]. The main-track total roughly doubled in five years, climbing from 9,467 submissions in 2020 to 21,575 in 2025 [12]. This stability suggests that the program committee has expanded capacity proportionally rather than becoming more selective: the 2025 review process alone drew on 20,518 reviewers, 1,663 area chairs, and 199 senior area chairs [12]. NeurIPS 2025 saw a 61% increase in submissions over 2024, the largest year-over-year jump in the conference's history. As the 2025 program committee chairs put it, "NeurIPS has grown at an unprecedented pace in recent years, fundamentally reshaping how the conference operates." [12]

## Location History

NeurIPS has been held at various locations, predominantly in North America:

| Year | Location | Notes |
|---|---|---|
| 1987 | Denver, Colorado, USA | Inaugural conference |
| 2015 | Montreal, Canada | |
| 2016 | Barcelona, Spain | One of the few non-North American venues |
| 2017 | Long Beach, California, USA | |
| 2018 | Montreal, Canada | First year under the NeurIPS name |
| 2019 | Vancouver, British Columbia, Canada | |
| 2020 | Virtual | Due to COVID-19 pandemic |
| 2021 | Virtual | Due to COVID-19 pandemic |
| 2022 | New Orleans, Louisiana, USA | Return to in-person |
| 2023 | New Orleans, Louisiana, USA | |
| 2024 | Vancouver, British Columbia, Canada | |
| 2025 | San Diego, California, USA (primary) + Mexico City (secondary site) | First year with a dual-location format [8] |

The 2025 introduction of a secondary conference site in Mexico City was a notable experiment aimed at improving accessibility and reducing the environmental impact of travel for Latin American researchers. The two sites ran on overlapping dates, with the San Diego program held December 2 to 7 and the Mexico City program November 30 to December 5 [8].

## Review Process

NeurIPS uses a double-blind peer review process. [Papers](/wiki/papers) are reviewed by members of the program committee, which in recent years has included over 20,000 reviewers [12]. Each paper typically receives 3 to 4 reviews, followed by author rebuttals and a discussion period among reviewers.

The conference has been at the forefront of experimenting with review process improvements:

- **Consistency experiments**: NeurIPS 2014 ran a famous experiment where approximately 10% of submissions were reviewed by two independent committees. The results revealed that the two committees agreed on only about 50% to 60% of accept/reject decisions, highlighting the inherent noise in peer review [9].
- **Ethics review**: Starting in 2020, NeurIPS introduced mandatory broader impact statements and established an ethics review process for flagged papers.
- **Reproducibility checklists**: Papers must include checklists addressing reproducibility concerns, including code availability, computational requirements, and experimental details.

The 2025 program committee chairs noted that scale itself degrades review reliability, writing that the surge in submissions "introduces effects that make the review process noisier." [12]

## NeurIPS 2025 Highlights

NeurIPS 2025, held December 2 through 7 in San Diego with a simultaneous site in Mexico City, was the largest edition of the conference to date [8].

**Scale**: The conference received 21,575 valid main-track submissions and accepted 5,290 papers, a 24.52% acceptance rate [12].

**Best Paper Awards**: Seven papers received best paper and runner-up awards, spanning areas including [diffusion model](/wiki/diffusion_model) theory, self-supervised reinforcement learning, attention mechanisms for large language models, reasoning capabilities in LLMs, online learning theory, neural [scaling laws](/wiki/scaling_laws), and benchmarking methodologies for language model diversity.

**Key themes**: Major trends reflected in the 2025 program included continued emphasis on large language and foundation models, growing interest in reproducibility and data-centric research through the expanding Datasets and [Benchmarks](/wiki/benchmarks) Track, and increased attention to the societal impacts of AI.

## Impact on AI Research

NeurIPS has played an outsized role in shaping the trajectory of AI research. Several factors contribute to its influence:

**Launching paradigm shifts.** Many of the most consequential ideas in modern AI were first presented at NeurIPS, including deep convolutional networks for image recognition (AlexNet, 2012), generative adversarial networks (2014), the Transformer architecture (2017), and scaling laws for language models. The conference serves as a launchpad where new ideas receive immediate scrutiny and attention from the global research community.

**Industry-academia bridge.** Unlike many academic conferences, NeurIPS attracts heavy participation from industry research labs. [Google](/wiki/google) DeepMind, [Meta](/wiki/meta) AI (FAIR), [Microsoft](/wiki/microsoft) Research, [OpenAI](/wiki/openai), and other organizations are major contributors. This creates a uniquely productive feedback loop between fundamental research and applied systems.

**Benchmark setting.** Many standard benchmarks and evaluation protocols in machine learning were introduced or popularized through NeurIPS papers and competitions. The Datasets and Benchmarks track, introduced in 2021, formalized the conference's commitment to rigorous evaluation methodology.

**Community formation.** NeurIPS workshops have been instrumental in forming new research subcommunities. Areas like [AI safety](/wiki/ai_safety), machine learning for climate, and AI for science were incubated in NeurIPS workshops before becoming established fields with their own dedicated venues.

## How does NeurIPS differ from ICML, ICLR, and CVPR?

NeurIPS exists within an ecosystem of top machine learning venues:

| Conference | Focus | Timing | Relationship to NeurIPS |
|---|---|---|---|
| [ICML](/wiki/icml) | Machine learning (broad) | July | Co-equal top venue; more focused on core ML methods |
| [ICLR](/wiki/iclr) | Representation learning | May | Younger conference; strong in deep learning; open review process |
| AAAI | Artificial intelligence (broad) | February | Broader AI scope; less focused on ML specifically |
| CVPR | Computer vision | June | Dominant venue for vision research |
| ACL/EMNLP | Natural language processing | Variable | Dominant venues for NLP-specific work |

NeurIPS is distinguished by its breadth (it spans the full range of machine learning rather than a single subfield), its December timing (making it the year-end checkpoint for the field), and its sheer scale: with 21,575 submissions in 2025 it is the largest of the major AI conferences [12].

## Current State

As of early 2026, NeurIPS continues to be the primary venue where many breakthrough results in AI are first reported. The conference faces ongoing challenges related to its enormous scale: managing review quality with over 21,000 submissions, ensuring fair and consistent evaluation, and maintaining community culture as the field grows [12].

The 2025 experiment with dual conference sites may signal a future trend toward more distributed conference formats, addressing both accessibility concerns and the logistical challenges of hosting over 15,000 attendees at a single venue.

With the continued explosive growth of AI research investment and the expanding number of researchers entering the field, NeurIPS is likely to remain at the center of the machine learning research community for the foreseeable future [10].

## References

1. "Conference on Neural Information Processing Systems." *Wikipedia*. https://en.wikipedia.org/wiki/Conference_on_Neural_Information_Processing_Systems
2. "The First NIPS/NeurIPS." *Caltech*. https://www.work.caltech.edu/neurips.html
3. "AI conference widely known as 'NIPS' changes its acronym due to complaints of sexism." *Nature* (2018). https://www.nature.com/articles/d41586-018-07476-w
4. Vaswani, A. et al. (2017). "[Attention Is All You Need](/wiki/attention_is_all_you_need)." *NeurIPS 2017*. https://arxiv.org/abs/1706.03762
5. Dao, T. et al. (2022). "[FlashAttention](/wiki/flash_attention): Fast and Memory-Efficient Exact [Attention](/wiki/attention) with IO-Awareness." *NeurIPS 2022*. https://arxiv.org/abs/2205.14135
6. Rafailov, R. et al. (2023). "[Direct Preference Optimization](/wiki/dpo): Your Language Model is Secretly a Reward Model." *NeurIPS 2023*. https://arxiv.org/abs/2305.18290
7. "NeurIPS 2024 Statistics." *Paper Copilot*. https://papercopilot.com/statistics/neurips-statistics/neurips-2024-statistics/
8. "NeurIPS 2025: A Guide to Key Papers, Trends & Stats." *IntuitionLabs* (2025). https://intuitionlabs.ai/articles/neurips-2025-conference-summary-trends
9. "NeurIPS Experiment on Consistency of Review." *NeurIPS Blog* (2014). https://blog.neurips.cc/
10. "2025 Conference." *NeurIPS Official Website*. https://neurips.cc/
11. "Conference on Neural Information Processing Systems." *Wikipedia*. https://en.wikipedia.org/wiki/Conference_on_Neural_Information_Processing_Systems
12. "Reflections on the 2025 Review Process from the Program Committee Chairs." *NeurIPS Blog* (September 30, 2025). https://blog.neurips.cc/2025/09/30/reflections-on-the-2025-review-process-from-the-program-committee-chairs/
13. "Name Flip-Flop: NIPS Is Now 'NeurIPS'." *Synced Review* (November 19, 2018). https://syncedreview.com/2018/11/19/name-flip-flop-nips-is-now-neurips/
14. "Attention Is All You Need." *Wikipedia*. https://en.wikipedia.org/wiki/Attention_Is_All_You_Need