Results 11 to 20 of about 4,916,142 (279)
An Overwiew of Evolution of Lexical Query Optimization Techniques [PDF]
Труды Института системного программирования РАН, 2018 The presented overview is concerned with lexical query optimization and covers papers published in the last four decades. The paper consists of five sections.
N. A. Mendkovich, S. D. Kuznetsov
doaj +5 more sources
Using experiential optimization to build lexical representations [PDF]
Psychonomic Bulletin & Review, 2018 To account for natural variability in cognitive processing, it is standard practice to optimize a model's parameters by fitting it to behavioral data. Although most language-related theories acknowledge a large role for experience in language processing, variability reflecting that knowledge is usually ignored when evaluating a model's fit to ...
Brendan T. Johns +2 more
semanticscholar +4 more sources
Reduced Resource Optimization in Male Alcoholics: N400 in a Lexical Decision Paradigm [PDF]
Alcoholism: Clinical and Experimental Research, 2010 Background: Event Related Potential (ERP) studies have highlighted some measures, notably P3 amplitude, that are associated with both state and trait deficits in alcoholism, while studies examining N400 amplitude in alcoholism are few. The present study aims to examine differences in the N400 component, an electrophysiological correlate of semantic ...
Bangalore N. Roopesh +5 more
semanticscholar +5 more sources
Unveiling the Lexical Sensitivity of LLMs: Combinatorial Optimization for Prompt Enhancement [PDF]
Proceedings of the 2024 Conference on Empirical Methods in Natural Language ProcessingLarge language models (LLMs) demonstrate exceptional instruct-following ability to complete various downstream tasks. Although this impressive ability makes LLMs flexible task solvers, their performance in solving tasks also heavily relies on instructions. In this paper, we reveal that LLMs are over-sensitive to lexical variations in task instructions,
Pengwei Zhan +4 more
semanticscholar +6 more sources
Optimizing the computational lexicalization of large grammars [PDF]
Proceedings of the 32nd annual meeting on Association for Computational Linguistics -, 1994 The computational lexicalization of a grammar is the optimization of the links between lexicalized rules and lexical items in order to improve the quality of the bottom-up filtering during parsing. This problem is NP-complete and untractable on large grammars. An approximation algorithm is presented.
Christian Jacquemin
openalex +2 more sources
An optimizing compiler for lexically scoped LISP [PDF]
ACM SIGPLAN Notices, 1982 We are developing an optimizing compiler for a dialect of the LISP language. The current target architecture is the S-I, a multiprocessing supercomputer designed at Lawrence Livermore National Laboratory. While LISP is usually thought of as a language primarily for symbolic processing and list manipulation, this compiler is also intended to compete ...
Rodney A. Brooks +2 more
+4 more sources
Generating SD-Rules in the SPECIALIST Lexical Tools - Optimization for Suffix Derivation Rule Set
International Conference on Health Informatics, 2016 Suffix derivations (SDs) are used with query expansion in concept mapping as an effective Natural Language Processing (NLP) technique to improve recall without sacrificing precision.
Chris J. Lu +3 more
openalex +2 more sources
Languages, 2022 Bilingual speakers often engage in code-switching, that is the use of lexical items and grammatical features from two languages in one sentence. Malaysia is a particularly interesting context for the study of code-switching because Malay-English code ...
Jeanine Treffers-Daller +3 more
doaj +2 more sources
Optimizing lexical fitness assessment in L2 Chinese reading texts [PDF]
PeerJ Computer ScienceBackground Vocabulary serves as the foundation for text comprehension. Therefore, texts at different proficiency levels should incorporate appropriately adapted vocabulary to support second language learners in developing their reading skills. Methods
Qiao Lin, Liu Hua
openalex +2 more sources
Authorship attribution of source code by using back propagation neural network based on particle swarm optimization. [PDF]
PLoS ONE, 2017 Authorship attribution is to identify the most likely author of a given sample among a set of candidate known authors. It can be not only applied to discover the original author of plain text, such as novels, blogs, emails, posts etc., but also used to ...
Xinyu Yang +4 more
doaj +2 more sources