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Inference in the FO(C) Modelling Language [article]

Bart Bogaerts, Joost Vennekens, Marc Denecker, Jan Van den Bussche
2014 arXiv   pre-print
Up to this point, no systems exist that perform inference on FO(C), and very little is known about properties of inference in FO(C). In this paper, we study both of the above problems.  ...  We implemented a prototype of this transformation, and thus present the first system to perform inference in FO(C). We also provide results about the complexity of reasoning in FO(C).  ...  We call this integration FO(C). 1 FO(C) fits in the FO(·) research project (Denecker 2012) , which aims at integrating expressive language constructs with a Tarskian model semantics in a unified language  ... 
arXiv:1404.6368v1 fatcat:6v3vqex3rjhqboob75sayojot4

The L+C Plant-Modelling Language [chapter]

P. Prusinkiewicz, R. Karwowski, B. Lane
2007 Functional-Structural Plant Modelling in Crop Production  
We implemented this transformation and hence, created the first system that performs inference in FO(C). We also provide results about the complexity of reasoning in FO(C).  ...  Up to this point, no systems exist that perform inference on FO(C), and very little is known about properties of inference in FO(C). In this paper, we study both of the above problems.  ...  Bogaerts et al. / Inference in the FO(C) Modelling Language 113 Definition 3 . 12 . 312 Let Δ be a causal theory in NestNF and let C be one of the C i in definition 3.5, then we call ϕ i (again, from  ... 
doi:10.1007/1-4020-6034-3_3 fatcat:wjjuqnvl45bsrbbluee6io35qe

Predicate Logic as a Modelling Language: The IDP System [article]

Broes De Cat, Bart Bogaerts, Maurice Bruynooghe, Gerda Janssens and Marc Denecker
2018 arXiv   pre-print
In this paper, we present the language and system.  ...  of inference.  ...  FO(ID,AGG,PF,T), the Formal Base Language In this section, we introduce the logic that is the basis of the IDP language.  ... 
arXiv:1401.6312v3 fatcat:fldt2evvpvbufhgz4bp47pp2em

OAG-BERT: Pre-train Heterogeneous Entity-augmented Academic Language Models [article]

Xiao Liu, Da Yin, Xingjian Zhang, Kai Su, Kan Wu, Hongxia Yang, Jie Tang
2021 arXiv   pre-print
To enrich language models with domain knowledge is crucial but difficult.  ...  Based on the world's largest public academic graph Open Academic Graph (OAG), we pre-train an academic language model, namely OAG-BERT, which integrates massive heterogeneous entities including paper,  ...  2 , ..., |C), where is the entity length and is the -th token in the entity.  ... 
arXiv:2103.02410v2 fatcat:ba6za5nfnjawvovsl6bdvcdwoi

Boolean models and infinitary first order languages

J.-P. Ressayre
1973 Annals of Mathematical Logic  
The paper develops a systematic use of boolean models in the model theory of infinitary languages. This yields a notion of (boolean) saturated model for denumerable sublanguages of Lo~ l w.  ...  The methods of saturated models are then applied; in particular results of "upward LiSwenheim-Skolem" type and results relating syntactic and semantic properties are obtained,  ...  We say that we relativize the above notions to a predicate G if we replace in their definitions the language ~ by the language ~c which contains in addition the predicate G.  ... 
doi:10.1016/0003-4843(73)90003-x fatcat:ktgilv3bhff63f7ubo2jfwa43q

Predicate logic as a modeling language: modeling and solving some machine learning and data mining problems with IDP3

MAURICE BRUYNOOGHE, HENDRIK BLOCKEEL, BART BOGAERTS, BROES DE CAT, STEF DE POOTER, JOACHIM JANSEN, ANTHONY LABARRE, JAN RAMON, MARC DENECKER, SICCO VERWER
2014 Theory and Practice of Logic Programming  
It offers its users a modeling language that is a slight extension of predicate logic and allows them to solve a wide range of search problems.  ...  These research areas have recently shown a strong interest in declarative modeling and constraint-solving as opposed to algorithmic approaches.  ...  Acknowledgements Caroline Macé and Tara Andrews introduced some of the authors to stemmatology and provided the data sets; Tara also explained the working of the procedural code.  ... 
doi:10.1017/s147106841400009x fatcat:txwnmq27w5abpjdbamvi6qmkm4

Fertility models for statistical natural language understanding

Stephen Della Pietra, Mark Epstein, Salim Roukos, Todd Ward
1997 Proceedings of the 35th annual meeting on Association for Computational Linguistics -  
The basic underlying intuition is that a single concept may be expressed in English as many disjoint clump of words. We present two fertility models which attempt to capture this phenomenon.  ...  Several recent efforts in statistical natural language understanding (NLU) have focused on generating clumps of English words from semantic meaning concepts (Miller et al., 1995; Levin and Pieraccini,  ...  The views and conclusions contained in this document should not be interpreted as representing the official policies of the U.S. Government.  ... 
doi:10.3115/976909.979639 dblp:conf/acl/PietraERW97 fatcat:2yiubeuyxfcmfidpyyfbvqwxmy

Generating Training Data with Language Models: Towards Zero-Shot Language Understanding [article]

Yu Meng, Jiaxin Huang, Yu Zhang, Jiawei Han
2022 arXiv   pre-print
Pretrained language models (PLMs) have demonstrated remarkable performance in various natural language processing tasks: Unidirectional PLMs (e.g., GPT) are well known for their superior text generation  ...  capabilities; bidirectional PLMs (e.g., BERT) have been the prominent choice for natural language understanding (NLU) tasks.  ...  ., 2020) , especially on challenging tasks like natural language inference (NLI).  ... 
arXiv:2202.04538v1 fatcat:eqlgcsotwre67pitwxqxjmru5e

Neural Random Projections for Language Modelling [article]

Davide Nunes, Luis Antunes
2018 arXiv   pre-print
In this paper, we exploit the sparsity in natural language even further by encoding each unique input word using a fixed sparse random representation.  ...  Neural network-based language models deal with data sparsity problems by mapping the large discrete space of words into a smaller continuous space of real-valued vectors.  ...  The idea of using embeddings in language modelling is explored in the early work or Bengio et al.  ... 
arXiv:1807.00930v4 fatcat:jzmciwx73jdctiwkfxzok3p3ty

On the Sentence Embeddings from Pre-trained Language Models [article]

Bohan Li and Hao Zhou and Junxian He and Mingxuan Wang and Yiming Yang and Lei Li
2020 arXiv   pre-print
However, the sentence embeddings from the pre-trained language models without fine-tuning have been found to poorly capture semantic meaning of sentences.  ...  We first reveal the theoretical connection between the masked language model pre-training objective and the semantic similarity task theoretically, and then analyze the BERT sentence embeddings empirically  ...  Acknowledgments The authors would like to thank Jiangtao Feng, Wenxian Shi, Yuxuan Song, and anonymous reviewers for their helpful comments and suggestion on this paper.  ... 
arXiv:2011.05864v1 fatcat:q7appb75a5elfnofhz6cgjmmva

QA-GNN: Reasoning with Language Models and Knowledge Graphs for Question Answering [article]

Michihiro Yasunaga, Hongyu Ren, Antoine Bosselut, Percy Liang, Jure Leskovec
2021 arXiv   pre-print
We evaluate our model on QA benchmarks in the commonsense (CommonsenseQA, OpenBookQA) and biomedical (MedQA-USMLE) domains.  ...  The problem of answering questions using knowledge from pre-trained language models (LMs) and knowledge graphs (KGs) presents two challenges: given a QA context (question and answer choice), methods need  ...  Acknowledgment We thank Rok Sosic, Weihua Hu, Jing Huang, Michele Catasta, members of the Stanford SNAP, P-Lambda and NLP groups and Project MOWGLI team, as well as our anonymous reviewers for valuable  ... 
arXiv:2104.06378v4 fatcat:qytacnflg5d2lj7blaw2ueo5x4

textTOvec: Deep Contextualized Neural Autoregressive Topic Models of Language with Distributed Compositional Prior [article]

Pankaj Gupta and Yatin Chaudhary and Florian Buettner and Hinrich Schütze
2019 arXiv   pre-print
We address two challenges of probabilistic topic modelling in order to better estimate the probability of a word in a given context, i.e., P(word|context): (1) No Language Structure in Context: Probabilistic  ...  The LSTM-LM learns a vector-space representation of each word by accounting for word order in local collocation patterns and models complex characteristics of language (e.g., syntax and semantics), while  ...  The LSTM offers history for the ith word via modeling temporal dependencies in the input sequence, c i .  ... 
arXiv:1810.03947v4 fatcat:4mobcineg5bu5c266bonq4n5xa

The Genesis of Spanish /θ/: A Revised Model

Ian Mackenzie
2022 Languages  
This article proposes a revised model of the genesis of Castilian Spanish /θ/, based on (i) precise tracking across the Late Middle Ages of the orthographical d → z change in preconsonantal coda position  ...  This effectively inverts the normally assumed chronology, according to which devoicing preceded and indeed was implicated in the genesis of /θ/.  ...  For example, prior 'kiss' would have been distinguishe articulation, the ç of beç o being voic conventional chronology is poorly associated teleological explanation fo basis.  ... 
doi:10.3390/languages7030191 fatcat:66quzzuw5jdsth3ve4gv3up3wy

The Status of Information Processing Models of Language

J. Morton
1981 Philosophical Transactions of the Royal Society of London. Biological Sciences  
An introductio n is given to the n atu re of inform ation processing models in psychology.  ...  of language and for phenom ena of m em ory for language m aterials over short time intervals.  ...  N ote th a t the fo rm at itself can n o t be falsified.  ... 
doi:10.1098/rstb.1981.0147 fatcat:e4i46usqznfvhoj23ddrn7hsqm

On Tree-Based Neural Sentence Modeling

Haoyue Shi, Hao Zhou, Jiaze Chen, Lei Li
2018 Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing  
To study the effectiveness of different tree structures, we replace the parsing trees with trivial trees (i.e., binary balanced tree, left-branching tree and right-branching tree) in the encoders.  ...  Further analysis show that tree modeling gives better results when crucial words are closer to the final representation.  ...  Acknowledgements We thank Hang Li, Yue Zhang, Lili Mou and Jiayuan Mao for their helpful comments on this work, and the anonymous reviewers for their valuable feedback.  ... 
doi:10.18653/v1/d18-1492 dblp:conf/emnlp/ShiZCL18 fatcat:a2hiqrn7szce7d4azhwu3egkyy
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