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检索条件"任意字段=Conference on empirical methods in natural language processing"
15135 条 记 录,以下是271-280 订阅
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Generalized Measures of Anticipation and Responsivity in Online language processing
Generalized Measures of Anticipation and Responsivity in Onl...
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2024 conference on empirical methods in natural language processing, EMNLP 2024
作者: Giulianelli, Mario Opedal, Andreas Cotterell, Ryan ETH zürich Switzerland
We introduce a generalization of classic information-theoretic measures of predictive uncertainty in online language processing, based on the simulation of expected continuations of incremental linguistic contexts. Ou... 详细信息
来源: 评论
language Model Quality Correlates with Psychometric Predictive Power in Multiple languages
Language Model Quality Correlates with Psychometric Predicti...
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conference on empirical methods in natural language processing (EMNLP)
作者: Wilcox, Ethan Gotlieb Meister, Clara Cotterell, Ryan Pimentel, Tiago Swiss Fed Inst Technol Zurich Switzerland Univ Cambridge Cambridge England
Surprisal theory (Hale, 2001;Levy, 2008) posits that a word's reading time is proportional to its surprisal (i.e., to its negative log probability given the proceeding context). It has been empirically tested usin... 详细信息
来源: 评论
Investigating Large language Models for Complex Word Identification in Multilingual and Multidomain Setups
Investigating Large Language Models for Complex Word Identif...
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2024 conference on empirical methods in natural language processing, EMNLP 2024
作者: Smădu, Răzvan-Alexandru Ion, David-Gabriel Cercel, Dumitru-Clementin Pop, Florin Cercel, Mihaela-Claudia National University of Science and Technology POLITEHNICA Bucharest Faculty of Automatic Control and Computers Bucharest Romania National Institute for Research & Development in Informatics - ICI Bucharest Bucharest Romania Academy of Romanian Scientists Bucharest Romania Paris 1 Panthéon-Sorbonne University Paris France University of Bucharest Bucharest Romania
Complex Word Identification (CWI) is an essential step in the lexical simplification task and has recently become a task on its own. Some variations of this binary classification task have emerged, such as lexical com... 详细信息
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Parameter-efficient Tuning for Large language Model without Calculating Its Gradients
Parameter-efficient Tuning for Large Language Model without ...
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conference on empirical methods in natural language processing (EMNLP)
作者: Jin, Feihu Zhang, Jiajun Zong, Chengqing Chinese Acad Sci Inst Automat Beijing Peoples R China Univ Chinese Acad Sci Sch Artificial Intelligence Beijing Peoples R China Wuhan AI Res Wuhan Peoples R China Shanghai Artificial Intelligence Lab Shanghai Peoples R China
Fine-tuning all parameters of large language models (LLMs) requires significant computational resources and is time-consuming. Recent parameter-efficient tuning methods such as Adapter tuning, Prefix tuning, and LoRA ... 详细信息
来源: 评论
empirical Prior for Text Autoencoders
Empirical Prior for Text Autoencoders
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2024 conference on empirical methods in natural language processing, EMNLP 2024
作者: Yin, Yongjing Gao, Wenyang Wu, Haodong Yan, Jianhao Zhang, Yue Zhejiang University China School of Engineering Westlake University China Institute of Advanced Technology Westlake Institute for Advanced Study China
This paper explores the application of Variational Autoencoders (VAE) in text generation, focusing on overcoming challenges like posterior collapse and the limitations of simplistic prior distributions. We investigate... 详细信息
来源: 评论
TRANSAGENTS: Build Your Translation Company with language Agents
TRANSAGENTS: Build Your Translation Company with Language Ag...
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2024 conference on empirical methods in natural language processing, EMNLP 2024
作者: Wu, Minghao Xu, Jiahao Wang, Longyue Monash University Australia Nanyang Technological University Singapore Tencent AI Lab China
Multi-agent systems empowered by large language models (LLMs) have demonstrated remarkable capabilities in a wide range of downstream applications. In this work, we introduce TRANSAGENTS, a novel multi-agent translati... 详细信息
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KidLM: Advancing language Models for Children - Early Insights and Future Directions
KidLM: Advancing Language Models for Children - Early Insigh...
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2024 conference on empirical methods in natural language processing, EMNLP 2024
作者: Nayeem, Mir Tafseer Rafiei, Davood University of Alberta Canada
Recent studies highlight the potential of large language models in creating educational tools for children, yet significant challenges remain in maintaining key child-specific properties such as linguistic nuances, co... 详细信息
来源: 评论
Deep natural language Feature Learning for Interpretable Prediction
Deep Natural Language Feature Learning for Interpretable Pre...
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conference on empirical methods in natural language processing (EMNLP)
作者: Urrutia, Felipe Buc, Cristian Barriere, Valentin Ctr Nacl Inteligencia Artificial Macul Chile Univ Chile Dept Comp Sci Santiago Chile
We propose a general method to break down a main complex task into a set of intermediary easier sub-tasks, which are formulated in natural language as binary questions related to the final target task. Our method allo... 详细信息
来源: 评论
VerifyMatch: A Semi-Supervised Learning Paradigm for natural language Inference with Confidence-Aware MixUp
VerifyMatch: A Semi-Supervised Learning Paradigm for Natural...
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2024 conference on empirical methods in natural language processing, EMNLP 2024
作者: Park, Seo Yeon Caragea, Cornelia Korea Republic of University of Illinois Chicago United States
While natural language inference (NLI) has emerged as a prominent task for evaluating a model's capability to perform natural language understanding, creating large benchmarks for training deep learning models imp... 详细信息
来源: 评论
Conversing with databases: Practical natural language Querying
Conversing with databases: Practical Natural Language Queryi...
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2023 conference on empirical methods in natural language processing, EMNLP 2023
作者: Kochedykov, Denis Yin, Fenglin Khatravath, Sreevidya JPMorgan ML CoE
In this work, we designed, developed and released in production DataQue - a hybrid NLQ (natural language Querying) system for conversational DB querying. We address multiple practical problems that are not accounted f... 详细信息
来源: 评论