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Found 37 papers, 12 papers with code
CTM - A Model for Large-Scale Multi-View Tweet Topic Classification
In contrast to most prior work which only focuses on post-classification into a small number of topics (10-20), we consider the task of large-scale topic classification in the context of Twitter where the topic space is 10 times larger with potentially multiple topic associations per Tweet.
mEdIT: Multilingual Text Editing via Instruction Tuning
We introduce mEdIT, a multi-lingual extension to CoEdIT -- the recent state-of-the-art text editing models for writing assistance.
Personalized Text Generation with Fine-Grained Linguistic Control
As the text generation capabilities of large language models become increasingly prominent, recent studies have focused on controlling particular aspects of the generated text to make it more personalized.
SOCIALITE-LLAMA: An Instruction-Tuned Model for Social Scientific Tasks
Social science NLP tasks, such as emotion or humor detection, are required to capture the semantics along with the implicit pragmatics from text, often with limited amounts of training data.
Writing Assistants Should Model Social Factors of Language
Intelligent writing assistants powered by large language models (LLMs) are more popular today than ever before, but their further widespread adoption is precluded by sub-optimal performance.
NTULM: Enriching Social Media Text Representations with Non-Textual Units
We refer to these annotations as Non-Textual Units (NTUs).
CTM -- A Model for Large-Scale Multi-View Tweet Topic Classification
In contrast to most prior work which only focuses on post classification into a small number of topics ($10$-$20$), we consider the task of large-scale topic classification in the context of Twitter where the topic space is $10$ times larger with potentially multiple topic associations per Tweet.
LMSOC: An Approach for Socially Sensitive Pretraining
Although language depends heavily on the geographical, temporal, and other social contexts of the speaker, these elements have not been incorporated into modern transformer-based language models.
Learning, Computing, and Trustworthiness in Intelligent IoT Environments: Performance-Energy Tradeoffs
An Intelligent IoT Environment (iIoTe) is comprised of heterogeneous devices that can collaboratively execute semi-autonomous IoT applications, examples of which include highly automated manufacturing cells or autonomously interacting harvesting machines.
TopicBERT for Energy Efficient Document Classification
Our work thus focuses on optimizing the computational cost of fine-tuning for document classification.
DialectGram: Detecting Dialectal Variation at Multiple Geographic Resolutions
In this work, we propose a model that enables detection of dialectal variation at multiple levels of geographic resolution obviating the need for a-priori definition of the resolution level.
What Should I Ask? Using Conversationally Informative Rewards for Goal-Oriented Visual Dialog
In this work, we focus on the task of goal-oriented visual dialogue, aiming to automatically generate a series of questions about an image with a single objective.
TWEETQA: A Social Media Focused Question Answering Dataset
With social media becoming increasingly pop-ular on which lots of news and real-time eventsare reported, developing automated questionanswering systems is critical to the effective-ness of many applications that rely on real-time knowledge.
What Should I Ask? Using Conversationally Informative Rewards for Goal-oriented Visual Dialog.
In this work, we focus on the task of goal-oriented visual dialogue, aiming to automatically generate a series of questions about an image with a single objective.
MOHONE: Modeling Higher Order Network Effects in KnowledgeGraphs via Network Infused Embeddings
First, we introduce methods that learn network representations of entities in the knowledge graph capturing these varied aspects of similarity.
DOLORES: Deep Contextualized Knowledge Graph Embeddings
We introduce a new method DOLORES for learning knowledge graph embeddings that effectively captures contextual cues and dependencies among entities and relations.
Multi-view Models for Political Ideology Detection of News Articles
A news article's title, content and link structure often reveal its political ideology.
Simple Neologism Based Domain Independent Models to Predict Year of Authorship
We present domain independent models to date documents based only on neologism usage patterns.
Simple Models for Word Formation in Slang
We propose the first generative models for three types of extra-grammatical word formation phenomena abounding in slang: Blends, Clippings, and Reduplicatives.
Hate Lingo: A Target-based Linguistic Analysis of Hate Speech in Social Media
While social media empowers freedom of expression and individual voices, it also enables anti-social behavior, online harassment, cyberbullying, and hate speech.
Simple Models for Word Formation in English Slang
We propose generative models for three types of extra-grammatical word formation phenomena abounding in English slang: Blends, Clippings, and Reduplicatives.
TFW, DamnGina, Juvie, and Hotsie-Totsie: On the Linguistic and Social Aspects of Internet Slang
In this work, we use UrbanDictionary to conduct the first large-scale linguistic analysis of slang and its social aspects on the Internet to yield insights into this variety of language that is increasingly used all over the world online.
Human Centered NLP with User-Factor Adaptation
We pose the general task of user-factor adaptation {--} adapting supervised learning models to real-valued user factors inferred from a background of their language, reflecting the idea that a piece of text should be understood within the context of the user that wrote it.
On the Distribution of Lexical Features at Multiple Levels of Analysis
Natural language processing has increasingly moved from modeling documents and words toward studying the people behind the language.
Latent Human Traits in the Language of Social Media: An Open-Vocabulary Approach
Taking advantage of linguistic information available through Facebook, we study the process of inferring a new set of potential human traits based on unprompted language use.
Domain Adaptation for Named Entity Recognition in Online Media with Word Embeddings
In this paper, we propose methods to effectively adapt models learned on one domain onto other domains using distributed word representations.
Data Centroid Based Multi-Level Fuzzy Min-Max Neural Network
In this brief, an extension of MLF is proposed which defines a new boundary region, where the previously proposed methods mark decisions with less confidence and hence misclassification is more frequent.
On the Convergent Properties of Word Embedding Methods
Do word embeddings converge to learn similar things over different initializations?
Theano: A Python framework for fast computation of mathematical expressions
Since its introduction, it has been one of the most used CPU and GPU mathematical compilers - especially in the machine learning community - and has shown steady performance improvements.
Don't Walk, Skip! Online Learning of Multi-scale Network Embeddings
We present Walklets, a novel approach for learning multiscale representations of vertices in a network.
Social and Information Networks Physics and Society
Freshman or Fresher? Quantifying the Geographic Variation of Internet Language
Our analysis of British and American English over a period of 100 years reveals that semantic variation between these dialects is shrinking.
To Drop or Not to Drop: Robustness, Consistency and Differential Privacy Properties of Dropout
Moreover, using the above mentioned stability properties of dropout, we design dropout based differentially private algorithms for solving ERMs.
Statistically Significant Detection of Linguistic Change
We propose a new computational approach for tracking and detecting statistically significant linguistic shifts in the meaning and usage of words.
POLYGLOT-NER: Massive Multilingual Named Entity Recognition
We describe a system that builds Named Entity Recognition (NER) annotators for 40 major languages using Wikipedia and Freebase.
Exploring the power of GPU's for training Polyglot language models
We evaluate the performance of training the model on the GPU and present optimizations that boost the performance on the GPU. One of the key optimizations, we propose increases the performance of a function involved in calculating and updating the gradient by approximately 50 times on the GPU for sufficiently large batch sizes.
Inducing Language Networks from Continuous Space Word Representations
Recent advancements in unsupervised feature learning have developed powerful latent representations of words.
