Text Classification

Sentiment Analysis

The computational study of people's opinions, emotions, and attitudes expressed in text.

Text Summarisation

The process of creating a concise and coherent summary of a longer text document while preserving key information.

Topic Modelling

An unsupervised technique for discovering abstract topics that occur in a collection of documents.

Abstractive Summarisation

A text summarisation approach that generates novel sentences to capture the essential meaning of a document, rather than simply extracting and rearranging existing sentences.

Aspect-Based Sentiment Analysis

A fine-grained sentiment analysis approach that identifies opinions directed at specific aspects or features of an entity, such as a product's price, quality, or design.

A two-stage retrieval process where an initial set of candidate documents is rescored by a more powerful model to improve the relevance ordering of search results.

A generative probabilistic model for discovering topics in a collection of documents.

The task of identifying all expressions in text that refer to the same real-world entity.

The subfield of NLP focused on machine reading comprehension and extracting meaning from text.

Technology that converts written text into natural-sounding spoken audio using neural networks, enabling voice interfaces, accessibility tools, and content narration.

A security vulnerability where malicious inputs manipulate a language model into ignoring its instructions or producing unintended outputs.

The syntactic analysis of a sentence to establish relationships between head words and words that modify them.

The automated production of source code from natural language specifications or partial code context, powered by large language models trained on programming repositories.