interpretability 1knowledge retrieval 1language model pretraining 1open-domain question answering 1retrieval-augmented models 1
From the 1 of 2.2k papers with an AI index.
24.4k citations
- Stanford UniversityUS126 papers
- University of California, BerkeleyUS124 papers
- Massachusetts Institute of TechnologyUS123 papers
- Google DeepMind (United Kingdom)GB82 papers
- Cornell UniversityUS76 papers
- Princeton UniversityUS75 papers
- Carnegie Mellon UniversityUS73 papers
- University of TorontoCA73 papers
- California Institute of TechnologyUS63 papers
- Columbia UniversityUS61 papers
- University of California, Santa BarbaraUS58 papers
- University of Illinois Urbana-ChampaignUS56 papers
Showing 2026 · cs.LGShow all
2 papers · 2 filters
cs.LG2026
Exposure-Based Reinforcement Learning to Rank
Harrie Oosterhuis, Rolf Jagerman, Zhen Qin +1
Reinforcement learning (RL) methods for learning-to-rank (LTR) can optimize (almost) any ranking goal, e.g., from precision or discounted cumulative gain to fairness-of-exposure or…
cs.LG2026
Reducing the GPU Memory Bottleneck with Lossless Compression for ML -- Extended
Aditya K Kamath, Arvind Krishnamurthy, Marco Canini +1
Machine learning (ML) training and inference often process data sets far exceeding GPU memory capacity, forcing them to rely on PCIe for on-demand tensor transfers, causing critica…