Results 21 to 30 of about 13,789,012 (283)
In-Context Convergence of Transformers [PDF]
International Conference on Machine Learning, 2023 Transformers have recently revolutionized many domains in modern machine learning and one salient discovery is their remarkable in-context learning capability, where models can solve an unseen task by utilizing task-specific prompts without further ...
Yu Huang, Yuan Cheng, Yingbin Liang
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Odontometric parameters in human mandibular molars for sex estimation in a forensic context
Dental Anthropology, 2021 When encountering human skeletal remains in forensic contexts, one important step in the identification process is the estimation of sex, because it reduces the number of individuals to approximately one half. The pelvis and skull are considered the most
Sofia Fernandes Franco +4 more
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PRODIGY: Enabling In-context Learning Over Graphs [PDF]
Neural Information Processing Systems, 2023 In-context learning is the ability of a pretrained model to adapt to novel and diverse downstream tasks by conditioning on prompt examples, without optimizing any parameters.
Qian Huang +6 more
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Symbol tuning improves in-context learning in language models [PDF]
Conference on Empirical Methods in Natural Language Processing, 2023 We present symbol tuning - finetuning language models on in-context input-label pairs where natural language labels (e.g.,"positive/negative sentiment") are replaced with arbitrary symbols (e.g.,"foo/bar"). Symbol tuning leverages the intuition that when
Jerry W. Wei +10 more
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Context in Systemic Functional Linguistics [PDF]
Functions of Language, 2021 No abstract available.
Tom Bartlett, Wendy L. Bowcher
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HyperAttention: Long-context Attention in Near-Linear Time [PDF]
International Conference on Learning Representations, 2023 We present an approximate attention mechanism named HyperAttention to address the computational challenges posed by the growing complexity of long contexts used in Large Language Models (LLMs).
Insu Han +5 more
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Dr.ICL: Demonstration-Retrieved In-context Learning [PDF]
Data Intelligence, 2023 In-context learning (ICL), teaching a large language model (LLM) to perform a task with few-shot demonstrations rather than adjusting the model parameters, has emerged as a strong paradigm for using LLMs.
Man Luo +7 more
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In-context Reinforcement Learning with Algorithm Distillation [PDF]
International Conference on Learning Representations, 2022 We propose Algorithm Distillation (AD), a method for distilling reinforcement learning (RL) algorithms into neural networks by modeling their training histories with a causal sequence model.
M. Laskin +13 more
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Indicators of Parent-Child Relationships in the Context of Various Socio-Demographic Parameters
Интеграция образования, 2020 Introduction. The article is dedicated to the problem of child-parent relationships (acceptance and behavior control practices by fathers). The context of modern family trends and various socio-demographic indicators of family life in the Russian ...
Artur A. Rean, Ivan A. Konovalov
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Global Context Vision Transformers [PDF]
International Conference on Machine Learning, 2022 We propose global context vision transformer (GC ViT), a novel architecture that enhances parameter and compute utilization for computer vision. Our method leverages global context self-attention modules, joint with standard local self-attention, to ...
Ali Hatamizadeh +3 more
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