"in-context learning" Papers
190 papers found • Page 4 of 4
Conference
How do Transformers Perform In-Context Autoregressive Learning ?
Michael Sander, Raja Giryes, Taiji Suzuki et al.
How Transformers Learn Causal Structure with Gradient Descent
Eshaan Nichani, Alex Damian, Jason Lee
In-context Convergence of Transformers
Yu Huang, Yuan Cheng, Yingbin LIANG
In-Context Decision Transformer: Reinforcement Learning via Hierarchical Chain-of-Thought
sili huang, Jifeng Hu, Hechang Chen et al.
In-Context Freeze-Thaw Bayesian Optimization for Hyperparameter Optimization
Herilalaina Rakotoarison, Steven Adriaensen, Neeratyoy Mallik et al.
In-Context Language Learning: Architectures and Algorithms
Ekin Akyürek, Bailin Wang, Yoon Kim et al.
In-Context Learning Agents Are Asymmetric Belief Updaters
Johannes A. Schubert, Akshay Kumar Jagadish, Marcel Binz et al.
In-context Learning on Function Classes Unveiled for Transformers
Zhijie Wang, Bo Jiang, Shuai Li
In-Context Matting
He Guo, Zixuan Ye, Zhiguo Cao et al.
In-Context Principle Learning from Mistakes
Tianjun Zhang, Aman Madaan, Luyu Gao et al.
In-Context Unlearning: Language Models as Few-Shot Unlearners
Martin Pawelczyk, Seth Neel, Himabindu Lakkaraju
In-context Vectors: Making In Context Learning More Effective and Controllable Through Latent Space Steering
Sheng Liu, Haotian Ye, Lei Xing et al.
InstructGIE: Towards Generalizable Image Editing
Zichong Meng, Changdi Yang, Jun Liu et al.
Is In-Context Learning in Large Language Models Bayesian? A Martingale Perspective
Fabian Falck, Ziyu Wang, Christopher Holmes
Language Agent Tree Search Unifies Reasoning, Acting, and Planning in Language Models
Andy Zhou, Kai Yan, Michal Shlapentokh-Rothman et al.
Large Language Models Can Automatically Engineer Features for Few-Shot Tabular Learning
Sungwon Han, Jinsung Yoon, Sercan Arik et al.
Learning Cognitive Maps from Transformer Representations for Efficient Planning in Partially Observed Environments
Antoine Dedieu, Wolfgang Lehrach, Guangyao Zhou et al.
Mastering Robot Manipulation with Multimodal Prompts through Pretraining and Multi-task Fine-tuning
Jiachen Li, Qiaozi Gao, Michael Johnston et al.
Meta-Reinforcement Learning Robust to Distributional Shift Via Performing Lifelong In-Context Learning
TengYe Xu, Zihao Li, Qinyuan Ren
Narrowing the Gap between Supervised and Unsupervised Sentence Representation Learning with Large Language Model
Mingxin Li, Richong Zhang, Zhijie Nie et al.
One Prompt is not Enough: Automated Construction of a Mixture-of-Expert Prompts
Ruochen Wang, Sohyun An, Minhao Cheng et al.
PALM: Predicting Actions through Language Models
Sanghwan Kim, Daoji Huang, Yongqin Xian et al.
PICLe: Eliciting Diverse Behaviors from Large Language Models with Persona In-Context Learning
Hyeong Kyu Choi, Sharon Li
Position: Do pretrained Transformers Learn In-Context by Gradient Descent?
Lingfeng Shen, Aayush Mishra, Daniel Khashabi
Position: Understanding LLMs Requires More Than Statistical Generalization
Patrik Reizinger, Szilvia Ujváry, Anna Mészáros et al.
Position: Video as the New Language for Real-World Decision Making
Sherry Yang, Jacob C Walker, Jack Parker-Holder et al.
Reason for Future, Act for Now: A Principled Architecture for Autonomous LLM Agents
Zhihan Liu, Hao Hu, Shenao Zhang et al.
Relational Programming with Foundational Models
Ziyang Li, Jiani Huang, Jason Liu et al.
Rethinking and Improving Visual Prompt Selection for In-Context Learning Segmentation Framework
Wei Suo, Lanqing Lai, Mengyang Sun et al.
RoboMP$^2$: A Robotic Multimodal Perception-Planning Framework with Multimodal Large Language Models
Qi Lv, Hao Li, Xiang Deng et al.
Skill Set Optimization: Reinforcing Language Model Behavior via Transferable Skills
Kolby Nottingham, Bodhisattwa Prasad Majumder, Bhavana Dalvi et al.
Subgoal-based Demonstration Learning for Formal Theorem Proving
Xueliang Zhao, Wenda Li, Lingpeng Kong
Trainable Transformer in Transformer
Abhishek Panigrahi, Sadhika Malladi, Mengzhou Xia et al.
Transformers Implement Functional Gradient Descent to Learn Non-Linear Functions In Context
Xiang Cheng, Yuxin Chen, Suvrit Sra
Transformers Learn Nonlinear Features In Context: Nonconvex Mean-field Dynamics on the Attention Landscape
Juno Kim, Taiji Suzuki
Two-stage LLM Fine-tuning with Less Specialization and More Generalization
Yihan Wang, Si Si, Daliang Li et al.
Tyche: Stochastic In-Context Learning for Medical Image Segmentation
Marianne Rakic, Hallee Wong, Jose Javier Gonzalez Ortiz et al.
Unifying Image Processing as Visual Prompting Question Answering
Yihao Liu, Xiangyu Chen, Xianzheng Ma et al.
What needs to go right for an induction head? A mechanistic study of in-context learning circuits and their formation
Aaditya Singh, Ted Moskovitz, Feilx Hill et al.
Why Larger Language Models Do In-context Learning Differently?
Zhenmei Shi, Junyi Wei, Zhuoyan Xu et al.