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← Architectures
Deep Learning
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Architectures
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Transformers
9,294 papers
Papers per year
2011: 1
2014: 2
2015: 6
2016: 17
2017: 67
2018: 156
2019: 404
2020: 769
2021: 1217
2022: 1446
2023: 1628
2024: 1574
2025: 1647
2026: 360
Papers
Pre-Trained Multi-Goal Transformers with Prompt Optimization for Efficient Online Adaptation
NIPS 2024
FilterNet: Harnessing Frequency Filters for Time Series Forecasting
NIPS 2024
Single Image Reflection Separation via Dual-Stream Interactive Transformers
NIPS 2024
START: A Generalized State Space Model with Saliency-Driven Token-Aware Transformation
NIPS 2024
MoTE: Reconciling Generalization with Specialization for Visual-Language to Video Knowledge Transfer
NIPS 2024
DreamClear: High-Capacity Real-World Image Restoration with Privacy-Safe Dataset Curation
NIPS 2024
GeoLRM: Geometry-Aware Large Reconstruction Model for High-Quality 3D Gaussian Generation
NIPS 2024
FasterDiT: Towards Faster Diffusion Transformers Training without Architecture Modification
NIPS 2024
BAM! Just Like That: Simple and Efficient Parameter Upcycling for Mixture of Experts
NIPS 2024
LISA: Layerwise Importance Sampling for Memory-Efficient Large Language Model Fine-Tuning
NIPS 2024
Enhancing Graph Transformers with Hierarchical Distance Structural Encoding
NIPS 2024
Vision-Language Models are Strong Noisy Label Detectors
NIPS 2024
Algorithmic progress in language models
NIPS 2024
Mixture of Nested Experts: Adaptive Processing of Visual Tokens
NIPS 2024
GrounDiT: Grounding Diffusion Transformers via Noisy Patch Transplantation
NIPS 2024
A Unified Framework for 3D Scene Understanding
NIPS 2024
ETO:Efficient Transformer-based Local Feature Matching by Organizing Multiple Homography Hypotheses
NIPS 2024
DI-MaskDINO: A Joint Object Detection and Instance Segmentation Model
NIPS 2024
Localizing Memorization in SSL Vision Encoders
NIPS 2024
Found in the Middle: How Language Models Use Long Contexts Better via Plug-and-Play Positional Encoding
NIPS 2024
Talking Heads: Understanding Inter-Layer Communication in Transformer Language Models
NIPS 2024
Opponent Modeling with In-context Search
NIPS 2024
On the Power of Decision Trees in Auto-Regressive Language Modeling
NIPS 2024
The Closeness of In-Context Learning and Weight Shifting for Softmax Regression
NIPS 2024
PTQ4DiT: Post-training Quantization for Diffusion Transformers
NIPS 2024
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