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← Core AI
Artificial Intelligence
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Foundation Models
4845 directly classified papers
Papers per year
2002: 1
2006: 1
2007: 1
2008: 1
2010: 1
2012: 2
2013: 1
2014: 1
2015: 2
2016: 7
2017: 15
2018: 49
2019: 69
2020: 123
2021: 204
2022: 243
2023: 579
2024: 1365
2025: 1819
2026: 361
Papers
TeamShakespeare at SemEval-2023 Task 6: Understand Legal Documents with Contextualized Large Language Models
SEMEVAL 2023
Fusing Pre-Trained Language Models With Multimodal Prompts Through Reinforcement Learning
CVPR 2023
Understanding and Improving Visual Prompting: A Label-Mapping Perspective
CVPR 2023
Exploring the Use of Foundation Models for Named Entity Recognition and Lemmatization Tasks in Slavic Languages
EACL 2023
Finspector: A Human-Centered Visual Inspection Tool for Exploring and Comparing Biases among Foundation Models
ACL 2023
A Discerning Several Thousand Judgments: GPT-3 Rates the Article + Adjective + Numeral + Noun Construction
EACL 2023
Trompt: Towards a Better Deep Neural Network for Tabular Data
ICML 2023
On the Power of Foundation Models
ICML 2023
Enhancing Activity Prediction Models in Drug Discovery with the Ability to Understand Human Language
ICML 2023
Efficient Approximations of Complete Interatomic Potentials for Crystal Property Prediction
ICML 2023
Variational Open-Domain Question Answering
ICML 2023
GNOT: A General Neural Operator Transformer for Operator Learning
ICML 2023
KDEformer: Accelerating Transformers via Kernel Density Estimation
ICML 2023
A Study on Transformer Configuration and Training Objective
ICML 2023
$\pi$-Tuning: Transferring Multimodal Foundation Models with Optimal Multi-task Interpolation
ICML 2023
What Can Human Sketches Do for Object Detection?
CVPR 2023
Transformers Learn In-Context by Gradient Descent
ICML 2023
Learning Neural PDE Solvers with Parameter-Guided Channel Attention
ICML 2023
Whose Opinions Do Language Models Reflect?
ICML 2023
Training Deep Surrogate Models with Large Scale Online Learning
ICML 2023
FusionRetro: Molecule Representation Fusion via In-Context Learning for Retrosynthetic Planning
ICML 2023
Transformers as Algorithms: Generalization and Stability in In-context Learning
ICML 2023
Ewald-based Long-Range Message Passing for Molecular Graphs
ICML 2023
Looped Transformers as Programmable Computers
ICML 2023
Generalizing Neural Wave Functions
ICML 2023
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