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Artificial Intelligence
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Learning Paradigms
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Transfer Learning
8,078 papers
Papers per year
2002: 2
2003: 1
2005: 3
2006: 5
2007: 12
2008: 7
2009: 7
2010: 16
2011: 15
2012: 13
2013: 35
2014: 32
2015: 40
2016: 72
2017: 149
2018: 341
2019: 619
2020: 711
2021: 992
2022: 980
2023: 1182
2024: 1282
2025: 1254
2026: 308
Papers
Transfer Learning for Latent Variable Network Models
NIPS 2024
MutaPLM: Protein Language Modeling for Mutation Explanation and Engineering
NIPS 2024
Free Lunch in Pathology Foundation Model: Task-specific Model Adaptation with Concept-Guided Feature Enhancement
NIPS 2024
Reference Trustable Decoding: A Training-Free Augmentation Paradigm for Large Language Models
NIPS 2024
Dissecting the Failure of Invariant Learning on Graphs
NIPS 2024
V-PETL Bench: A Unified Visual Parameter-Efficient Transfer Learning Benchmark
NIPS 2024
Lumen: Unleashing Versatile Vision-Centric Capabilities of Large Multimodal Models
NIPS 2024
Probabilistic Federated Prompt-Tuning with Non-IID and Imbalanced Data
NIPS 2024
TuneTables: Context Optimization for Scalable Prior-Data Fitted Networks
NIPS 2024
Hybrid Generative AI for De Novo Design of Co-Crystals with Enhanced Tabletability
NIPS 2024
CultureLLM: Incorporating Cultural Differences into Large Language Models
NIPS 2024
Personalized Adapter for Large Meteorology Model on Devices: Towards Weather Foundation Models
NIPS 2024
A Closer Look at the CLS Token for Cross-Domain Few-Shot Learning
NIPS 2024
Reprogramming Pretrained Target-Specific Diffusion Models for Dual-Target Drug Design
NIPS 2024
Causal Imitation for Markov Decision Processes: a Partial Identification Approach
NIPS 2024
Replay-and-Forget-Free Graph Class-Incremental Learning: A Task Profiling and Prompting Approach
NIPS 2024
Model-Based Transfer Learning for Contextual Reinforcement Learning
NIPS 2024
A Theoretical Understanding of Self-Correction through In-context Alignment
NIPS 2024
Imitating Language via Scalable Inverse Reinforcement Learning
NIPS 2024
Personalized Federated Learning with Mixture of Models for Adaptive Prediction and Model Fine-Tuning
NIPS 2024
Homology Consistency Constrained Efficient Tuning for Vision-Language Models
NIPS 2024
Derandomizing Multi-Distribution Learning
NIPS 2024
Pre-training Differentially Private Models with Limited Public Data
NIPS 2024
Grokking of Implicit Reasoning in Transformers: A Mechanistic Journey to the Edge of Generalization
NIPS 2024
MMLONGBENCH-DOC: Benchmarking Long-context Document Understanding with Visualizations
NIPS 2024
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