| Predicate-Argument Based Bi-Encoder for Paraphrase Identification | 0 | 0.34 | 2022 |
| Testing Large Language Models on Compositionality and Inference with Phrase-Level Adjective-Noun Entailment. | 0 | 0.34 | 2022 |
| Towards Structure-aware Paraphrase Identification with Phrase Alignment Using Sentence Encoders. | 0 | 0.34 | 2022 |
| MuSeCLIR: A Multiple Senses and Cross-lingual Information Retrieval Dataset. | 0 | 0.34 | 2022 |
| Representing Syntax and Composition with Geometric Transformations. | 0 | 0.34 | 2021 |
| Data Augmentation for Hypernymy Detection | 0 | 0.34 | 2021 |
| Quantification under class-conditional dataset shift. | 0 | 0.34 | 2019 |
| When a Red Herring in Not a Red Herring: Using Compositional Methods to Detect Non-Compositional Phrases. | 0 | 0.34 | 2017 |
| One Representation per Word - Does it make Sense for Composition? | 1 | 0.34 | 2017 |
| Improving Semantic Composition With Offset Inference | 0 | 0.34 | 2017 |
| Aligning Packed Dependency Trees: a theory of composition for distributional semantics. | 5 | 0.40 | 2016 |
| A critique of word similarity as a method for evaluating distributional semantic models. | 0 | 0.34 | 2016 |
| Improving Sparse Word Representations with Distributional Inference for Semantic Composition. | 3 | 0.41 | 2016 |
| Learning Using Unselected Features (LUFe). | 0 | 0.34 | 2016 |
| Optimising Agile Social Media Analysis. | 0 | 0.34 | 2015 |
| Optimising Agile Social Media Analysis | 0 | 0.34 | 2015 |
| Learning To Predict Distributions Of Words Across Domains | 0 | 0.34 | 2014 |
| Distributional Composition using Higher-Order Dependency Vectors. | 5 | 0.41 | 2014 |
| Method51 for Mining Insight from Social Media Datasets. | 2 | 0.37 | 2014 |
| Learning to Distinguish Hypernyms and Co-Hyponyms. | 38 | 1.07 | 2014 |
| Language Technology for Agile Social Media Science. | 0 | 0.34 | 2013 |
| Language Technology for Agile Social Media Science | 2 | 0.42 | 2013 |
| Cross-Domain Sentiment Classification Using a Sentiment Sensitive Thesaurus | 56 | 1.67 | 2013 |
| Algebraic approaches to compositional distributional semantics | 1 | 0.41 | 2011 |
| Dependency parsing schemata and mildly non-projective dependency parsing | 14 | 0.61 | 2011 |
| Using multiple sources to construct a sentiment sensitive thesaurus for cross-domain sentiment classification | 23 | 0.83 | 2011 |
| Parsing mildly non-projective dependency structures | 16 | 0.85 | 2009 |
| Optimal reduction of rule length in linear context-free rewriting systems | 24 | 0.85 | 2009 |
| A Deductive Approach to Dependency Parsing | 9 | 0.62 | 2008 |
| Modelling control in generation | 0 | 0.34 | 2007 |
| The distributional similarity of sub-parses | 11 | 0.82 | 2005 |
| Middleware for User Controlled Environments | 1 | 0.51 | 2005 |
| Managing the Policies of Non-Technical Users in a Dynamic World | 3 | 0.45 | 2005 |
| Characterising measures of lexical distributional similarity | 122 | 5.94 | 2004 |
| A general framework for distributional similarity | 54 | 3.10 | 2003 |
| Evaluation of LTAG Parsing with Supertag Compaction | 0 | 0.34 | 2002 |
| D-tree substitution grammars | 18 | 1.38 | 2001 |
| Class-based probability estimation using a semantic hierarchy | 80 | 6.41 | 2001 |
| A class-based probabilistic approach to structural disambiguation | 4 | 0.79 | 2000 |
| Parsing with an extended domain of locality | 7 | 1.60 | 1999 |
| An Iterative Approach to Estimating Frequencies over a Semantic Hierarchy | 7 | 1.07 | 1999 |
| A Structure-Sharing Parser for Lexicalized Grammars | 0 | 0.34 | 1998 |
| Grammar Compaction and Computation Sharing in Automata-based Parsing | 4 | 0.67 | 1998 |
| The LEXSYS Project | 2 | 0.44 | 1998 |
| A structure-sharing parser for lexicalized grammars | 8 | 1.10 | 1998 |
| Encoding Frequency Information in Lexicalized Grammars | 10 | 1.63 | 1997 |
| Automaton-based Parsing for Lexicalised Grammars. | 0 | 0.34 | 1997 |
| D-Tree Grammars | 55 | 6.79 | 1995 |
| A Tractable Extension of Linear Indexed Grammars | 7 | 0.70 | 1995 |
| Using default inheritance to describe LTAG | 2 | 0.40 | 1995 |
