Search Results for author:
Found 21 papers, 8 papers with code
Structure-aware Sentence Encoder in Bert-Based Siamese Network
Recently, impressive performance on various natural language understanding tasks has been achieved by explicitly incorporating syntax and semantic information into pre-trained models, such as BERT and RoBERTa.
Natural Language Understanding
Semantic Textual Similarity
+4
Testing Large Language Models on Compositionality and Inference with Phrase-Level Adjective-Noun Entailment
Here, we investigate whether lexical entailment (LE, i. e. hyponymy or the is a relation between words) can be generalised in a compositional manner.
Predicate-Argument Based Bi-Encoder for Paraphrase Identification
Paraphrase identification involves identifying whether a pair of sentences express the same or similar meanings.
MuSeCLIR: A Multiple Senses and Cross-lingual Information Retrieval Dataset
This paper addresses a deficiency in existing cross-lingual information retrieval (CLIR) datasets and provides a robust evaluation of CLIR systems’ disambiguation ability.
Automated Query Generation for Evidence Collection from Web Search Engines
This process requires a fact-checker to formulate a search query based on the fact and to present it to a search engine.
Towards Structure-aware Paraphrase Identification with Phrase Alignment Using Sentence Encoders
Therefore, we here propose to combine sentence encoders with an alignment component by representing each sentence as a list of predicate-argument spans (where their span representations are derived from sentence encoders), and decomposing the sentence-level meaning comparison into the alignment between their spans for paraphrase identification tasks.
Representing Syntax and Composition with Geometric Transformations
The exploitation of syntactic graphs (SyGs) as a word's context has been shown to be beneficial for distributional semantic models (DSMs), both at the level of individual word representations and in deriving phrasal representations via composition.
Leveraging HTML in Free Text Web Named Entity Recognition
HTML tags are typically discarded in free text Named Entity Recognition from Web pages.
Data Augmentation for Hypernymy Detection
The automatic detection of hypernymy relationships represents a challenging problem in NLP.
Improving Semantic Composition with Offset Inference
Count-based distributional semantic models suffer from sparsity due to unobserved but plausible co-occurrences in any text collection.
When a Red Herring in Not a Red Herring: Using Compositional Methods to Detect Non-Compositional Phrases
Non-compositional phrases such as \textit{red herring} and weakly compositional phrases such as \textit{spelling bee} are an integral part of natural language (Sag, 2002).
One Representation per Word - Does it make Sense for Composition?
In this paper, we investigate whether an a priori disambiguation of word senses is strictly necessary or whether the meaning of a word in context can be disambiguated through composition alone.
Aligning Packed Dependency Trees: a theory of composition for distributional semantics
We present a new framework for compositional distributional semantics in which the distributional contexts of lexemes are expressed in terms of anchored packed dependency trees.
Improving Sparse Word Representations with Distributional Inference for Semantic Composition
Distributional models are derived from co-occurrences in a corpus, where only a small proportion of all possible plausible co-occurrences will be observed.
