Posts in the AI Conference Guide series
In 2023, LLMs took over the machine-learning conference agenda. NeurIPS received more than 12,000 submissions; both Outstanding Papers addressed large models, while runner-up DPO became a practical alternative to RLHF within two years. DreamFusion opened the text-to-3D field, ICML spotlighted LLM watermarking and learning-rate adaptation, and the Mamba preprint emerged as the first serious architectural challenger to the Transformer.
2023 was the first full academic year after ChatGPT, and LLMs rewrote the NLP conference agenda. ACL's Best Papers examined humor understanding and the propagation of political bias; an EMNLP Best Paper explained in-context learning through information flow; and the HackAPrompt competition paper also won an EMNLP Best Paper award, signaling that security research had entered the mainstream. The year's largest shift was from asking how to make models more accurate to asking how we can tell when a model is misleading us.
In 2023, computer vision moved from seeing images to understanding, generating, and controlling them. Segment Anything turned segmentation into a general zero-shot capability, ControlNet made diffusion models precisely controllable, and 3D Gaussian Splatting challenged NeRF with real-time rendering. CVPR received more than 9,000 submissions and ICCV more than 8,000 as both conferences returned to in-person events.
2023 was the first year in which LLMs comprehensively rewrote the AI research agenda. DPO received a NeurIPS Outstanding Paper Runner-Up award, ReAct became an ICLR Oral, and hallucination grew from a marginal term into a major track at every conference. Meanwhile, 3D Gaussian Splatting swept through computer vision after its SIGGRAPH debut, Mamba emerged at the end of the year to challenge the Transformer attention monopoly, and publication volume for traditional NLP pipelines began a clear decline.