Results 21 to 30 of about 2,384,193 (254)

Neural Natural Language Inference Models Enhanced with External Knowledge

, 2018
Modeling natural language inference is a very challenging task. With the availability of large annotated data, it has recently become feasible to train complex models such as neural-network-based inference models, which have shown to achieve the state-of-
Chen, Qian, Inkpen, Diana, Ling, Zhen-Hua, Wei, Si, Zhu, Xiaodan   +4 more
core   +1 more source

Improving Language Modelling with Noise-contrastive estimation

, 2017
Neural language models do not scale well when the vocabulary is large. Noise-contrastive estimation (NCE) is a sampling-based method that allows for fast learning with large vocabularies.
Grzes, Marek, Liza, Farhana Ferdousi
core   +1 more source

SMART: Robust and Efficient Fine-Tuning for Pre-trained Natural Language Models through Principled Regularized Optimization

, 2020
Transfer learning has fundamentally changed the landscape of natural language processing (NLP) research. Many existing state-of-the-art models are first pre-trained on a large text corpus and then fine-tuned on downstream tasks.
Chen, Weizhu, Gao, Jianfeng, He, Pengcheng, Jiang, Haoming, Liu, Xiaodong, Zhao, Tuo   +5 more
core   +1 more source

Slim Embedding Layers for Recurrent Neural Language Models

, 2017
Recurrent neural language models are the state-of-the-art models for language modeling. When the vocabulary size is large, the space taken to store the model parameters becomes the bottleneck for the use of recurrent neural language models. In this paper,
Kulhanek, Raymond, Li, Zhongliang, Wang, Shaojun, Wu, Shuang, Zhao, Yunxin   +4 more
core   +1 more source

From Large Language Models to Large Multimodal Models: A Literature Review

Applied Sciences
With the deepening of research on Large Language Models (LLMs), significant progress has been made in recent years on the development of Large Multimodal Models (LMMs), which are gradually moving toward Artificial General Intelligence. This paper aims to
Dawei Huang, Chuan Yan, Qing Li, Xiaojiang Peng   +3 more
doaj   +1 more source

Large language models propagate race-based medicine

npj Digital Medicine, 2023
Large language models (LLMs) are being integrated into healthcare systems; but these models may recapitulate harmful, race-based medicine. The objective of this study is to assess whether four commercially available large language models (LLMs) propagate
Jesutofunmi A. Omiye, Jenna C. Lester, Simon Spichak, Veronica Rotemberg, Roxana Daneshjou   +4 more
doaj   +1 more source

Why and When Are Evidence‐Based Interventions Adopted in Paediatric Supportive Care? A Qualitative Exploration of the Determinants of Photobiomodulation Implementation

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Background Oral mucositis is a common and debilitating side effect of childhood cancer and stem cell transplant treatments. It affects the quality of life of children and young people (CYP) and places a strain on services. Photobiomodulation is recommended for oral mucositis prevention in international guidance but is poorly implemented in UK ...
Claudia Heggie, Kara A. Gray‐Burrows, Peter F. Day, Bob Phillips, Carl A. Thompson   +4 more
wiley   +1 more source

Role play with large language models

Nature, 2023
As dialogue agents become increasingly human-like in their performance, it is imperative that we develop effective ways to describe their behaviour in high-level terms without falling into the trap of anthropomorphism. In this paper, we foreground the concept of role-play.
Murray Shanahan, Kyle McDonell, Laria Reynolds   +2 more
openaire   +6 more sources

Real‐World Pediatric Blinatumomab Administration: Access to Outpatient Care Delivery and Impact of a Hospital‐Dispensed Model

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Blinatumomab has been shown to be highly effective for patients with pediatric B‐ALL and has recently become standard of care therapy. Due to its past use in the clinical trial setting, there is limited information available about real‐world administration.
Katelyn Oranges, Kelly A. Duffy, Sara McDonough, Evelyn Kurpiewski, R. Jennifer Randall, Allison Barz Leahy, Haley M. Newman, Joyce P. Lee, Stephen P. Hunger, Anne F. Reilly, David T. Teachey, Susan R. Rheingold, Daniel J. Zheng   +12 more
wiley   +1 more source

Language Without Propositions: Why Large Language Models Hallucinate

Philosophies
This paper defends the thesis that LLM hallucinations are best explained as a truth representation problem: Current models lack an internal representation of propositions as truth-bearers, so truth and falsity cannot constrain generation in the way ...
Jakub Mácha
doaj   +1 more source