15 Outstanding Research Papers from NeurIPS 2025

NeurIPS 2025, as a premier annual event in machine learning and computational neuroscience, tackles major topics like the future of AI, current research, and the most difficult challenges. While we’re not attending this year, we’re closely following the updates and today we pull together a quick, easy-to-digest roundup of a few standout papers so you can jump in without getting overwhelmed.

Here is a list of 15 papers from NeurIPS 2025, including 8 top research papers that received awards, along with 7 others that caught our attention:

1. Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks → https://neurips.cc/virtual/2025/loc/san-diego/test-of-time/128328
Test of Time Award winner. Introduces the RPN, a small convnet that predicts objectness and boxes on shared features, enabling Faster R-CNN to share computation and run around 5 fps on a GPU

2. Artificial Hivemind: The Open-Ended Homogeneity of LMs (and Beyond) → https://neurips.cc/virtual/2025/loc/san-diego/poster/121421
Releases a huge open-ended prompt dataset, showing that LLMs often fall into an “artificial hivemind” – generate surprisingly similar answers – and measuring diversity collapse

3. Optimal Mistake Bounds for Transductive Online Learning → https://neurips.cc/virtual/2025/loc/san-diego/poster/119098
Settles a 30-year-old question by showing how much unlabeled data helps in online learning – it gives a precise quadratic advantage with tight matching bounds

4. Gated Attention for LLMs: Non-linearity, Sparsity, and Attention-Sink-Free → https://neurips.cc/virtual/2025/loc/san-diego/poster/120216
Demonstrates how gating actually affects attention: a simple sigmoid gate after Scaled Dot-Product Attention (SDPA) boosts performance, stability, and long-context behavior by adding useful nonlinearity and sparse modulation

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