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Related papers: Encoding Lexicalized Tree Adjoining Grammars with …

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Semantic theories of natural language associate meanings with utterances by providing meanings for lexical items and rules for determining the meaning of larger units given the meanings of their parts. Meanings are often assumed to combine…

cmp-lg · Computer Science 2008-02-03 Mary Dalrymple , John Lamping , Fernando Pereira , Vijay Saraswat

Accurate syntactic representations are essential for robust generalization in natural language. Recent work has found that pre-training can teach language models to rely on hierarchical syntactic features - as opposed to incorrect linear…

Computation and Language · Computer Science 2023-06-01 Aaron Mueller , Tal Linzen

This paper defines unification based ID/LP grammars based on typed feature structures as nonterminals and proposes a variant of Earley's algorithm to decide whether a given input sentence is a member of the language generated by a…

cmp-lg · Computer Science 2016-08-31 Frank Morawietz

The aim of this paper is to show how we can handle the Recognising Textual Entailment (RTE) task by using Description Logics (DLs). To do this, we propose a representation of natural language semantics in DLs inspired by existing…

Computation and Language · Computer Science 2007-10-17 Paul Bedaride

Text-attributed graphs (TAGs) have emerged as a powerful representation for modeling complex relationships across diverse domains. With the rise of large language models (LLMs), there is growing interest in leveraging their capabilities for…

Machine Learning · Computer Science 2025-07-29 Jianyuan Bo , Hao Wu , Yuan Fang

Large language models have achieved remarkable success in general language understanding tasks. However, as a family of generative methods with the objective of next token prediction, the semantic evolution with the depth of these models…

Computation and Language · Computer Science 2024-06-11 Zhu Liu , Cunliang Kong , Ying Liu , Maosong Sun

Recently, unsupervised parsing of syntactic trees has gained considerable attention. A prototypical approach to such unsupervised parsing employs reinforcement learning and auto-encoders. However, no mechanism ensures that the learnt model…

Computation and Language · Computer Science 2021-05-24 Atul Sahay , Anshul Nasery , Ayush Maheshwari , Ganesh Ramakrishnan , Rishabh Iyer

Graph-based semantic representations are valuable in natural language processing, where it is often simple and effective to represent linguistic concepts as nodes, and relations as edges between them. Several attempts has been made to find…

Formal Languages and Automata Theory · Computer Science 2021-05-10 Johanna Björklund , Frank Drewes , Anna Jonsson

Dictionaries are often developed using tools that save to Extensible Markup Language (XML)-based standards. These standards often allow high-level repeating elements to represent lexical entries, and utilize descendants of these repeating…

Computation and Language · Computer Science 2016-02-18 Paul Rodrigues , David Zajic , David Doermann , Michael Bloodgood , Peng Ye

We consider tensor grammars, which are an example of \commutative" grammars, based on the classical (rather than intuitionistic) linear logic. They can be seen as a surface representation of abstract categorial grammars ACG in the sense…

Logic · Mathematics 2021-11-22 Sergey Slavnov

Hierarchical knowledge structures are ubiquitous across real-world domains and play a vital role in organizing information from coarse to fine semantic levels. While such structures have been widely used in taxonomy systems, biomedical…

Machine Learning · Computer Science 2026-03-10 Yunhui Liu , Yongchao Liu , Yinfeng Chen , Chuntao Hong , Tao Zheng , Tieke He

Domain adaptation in natural language generation (NLG) remains challenging because of the high complexity of input semantics across domains and limited data of a target domain. This is particularly the case for dialogue systems, where we…

Computation and Language · Computer Science 2019-10-16 Bo-Hsiang Tseng , Paweł Budzianowski , Yen-Chen Wu , Milica Gašić

What counts as evidence for syntactic structure? In traditional generative grammar, systematic contrasts in grammaticality such as subject-auxiliary inversion and the licensing of parasitic gaps are taken as evidence for an internal,…

Computation and Language · Computer Science 2025-12-12 Lars G. B. Johnsen

Recent progress in large language models has renewed interest in how multi-step reasoning is represented internally. While prior work often treats reasoning as a linear chain, many reasoning problems are more naturally modeled as directed…

Computation and Language · Computer Science 2026-04-07 Tianjun Zhong , Linyang He , Nima Mesgarani

Hierarchical text classification (HTC) is a challenging subtask of multi-label classification as the labels form a complex hierarchical structure. Existing dual-encoder methods in HTC achieve weak performance gains with huge memory…

Computation and Language · Computer Science 2023-06-12 He Zhu , Chong Zhang , Junjie Huang , Junran Wu , Ke Xu

The integration of Large Language Models (LLMs) with Graph Neural Networks (GNNs) has recently been explored to enhance the capabilities of Text Attribute Graphs (TAGs). Most existing methods feed textual descriptions of the graph structure…

Computation and Language · Computer Science 2025-04-03 Zhaoxing Li , Xiaoming Zhang , Haifeng Zhang , Chengxiang Liu

In real-world scenarios, texts in a graph are often linked by multiple semantic relations (e.g., papers in an academic graph are referenced by other publications, written by the same author, or published in the same venue), where text…

Computation and Language · Computer Science 2024-07-16 Bowen Jin , Wentao Zhang , Yu Zhang , Yu Meng , Han Zhao , Jiawei Han

We here explore a ``fully'' lexicalized Tree-Adjoining Grammar for discourse that takes the basic elements of a (monologic) discourse to be not simply clauses, but larger structures that are anchored on variously realized discourse cues.…

cmp-lg · Computer Science 2007-05-23 Bonnie Lynn Webber , Aravind K. Joshi

The task of translating between programming languages differs from the challenge of translating natural languages in that programming languages are designed with a far more rigid set of structural and grammatical rules. Previous work has…

Machine Learning · Computer Science 2018-07-06 Mehdi Drissi , Olivia Watkins , Aditya Khant , Vivaswat Ojha , Pedro Sandoval , Rakia Segev , Eric Weiner , Robert Keller

The adaptation of pretrained language models to solve supervised tasks has become a baseline in NLP, and many recent works have focused on studying how linguistic information is encoded in the pretrained sentence representations. Among…

Computation and Language · Computer Science 2021-02-11 Laura Pérez-Mayos , Roberto Carlini , Miguel Ballesteros , Leo Wanner
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