gpt - 3 - 42Papers

Home

Discover

Bookmarks

Keep Up With Latest Trending Papers. Computer Science, AI and more.Subscribe

CC BY

Artificial Intelligence

Computation and Language

GPT-3: A Survey

a survey on GPT-3

This paper provides an introductory survey to the generative principle test-based inference (gpt-3).

We survey both academic and commercial efforts applying this technology in diverse domains such as developing conversational ai chatbots, software development, creative work, domain knowledge, and business productivity.

CC BY

Computation and Language

Adding Examples to GPT-3 for Topic Classification

Improving Short Text Classification With Augmented Data Using GPT-3

This study teaches a large-scale natural language model to classify whether a question is related to data science by augmenting a small training set with additional training examples generated by the model itself.

We compare two classifiers : the classification endpoint with augmented examples, and the classification endpoint with an optimal training set chosen using a genetic algorithm.

Computation and Language

Who is GPT-3? An Exploration of Personality, Values and Demographics

Language models such as GPT-3 have caused a furore in the research community. Some studies found that GPT-3 has some creative abilities and makes mistakes that are on par with human behaviour. This pa

More...

CC BY

Machine Learning

Artificial Intelligence

Computation and Language

A Cognitive Assessment of GPT-3

Using cognitive psychology to understand GPT-3

We study the decision-making, information search, deliberation, and causal reasoning abilities of a recent large language model, using tools from cognitive psychology.

We find that much of the model s behavior is impressive : it solves vignette-based tasks similarly or better than human subjects, is able to make decent decisions from descriptions, outperforms humans in a multi-armed bandit task, and shows signatures of model-based reinforcement learning.

Added to collectionTop 100 Trending AI & Computer Science Papers

Computation and Language

Language Models are Few-Shot Learners

Recent work has demonstrated substantial gains on many NLP tasks and benchmarks by pre-training on a large corpus of text followed by fine-tuning on a specific task. While typically task-agnostic in a

More...

CC BY

Computation and Language

On the Performance of Very Large Language Models for Opinion Summarization

Zero-Shot Opinion Summarization with GPT-3

Very large language models such as gpt-3 have shown impressive performanceacross a wide variety of tasks, including text summarization.

In this paper, we show that this strong performance extends to opinion summarization.

CC BY

Information Retrieval

Computation and Language

Few-Shot Performance of GPT-3 on Biomedical Information Extraction Tasks

Thinking about GPT-3 In-Context Learning for Biomedical IE? Think Again

We present the first systematic and comprehensive study to compare the few-shot performance of the pre-trained language model (plm) gpt-3 in-context learning with fine-tuning smaller (i.e.,bert-sized) pre-trained language models on two highly representative biomedical information extraction tasks, named entity recognition and relation extraction.

Our results show that gpt-3 still significantly underperforms compared with simply fine-tuning a smaller plm using the same small training set.

CC BY

Computation and Language

Robust Prompting for Large Language Models

Prompting GPT-3 To Be Reliable

Large language models (llm) show impressive abilities via few-shot prompting.

However, existing research focuses on models'accuracy on standard benchmarks and largely ignores their reliability, which is crucial for avoiding catastrophic real-world harms.

Computation and Language

Neurons and Cognition

Large language models can segment narrative events similarly to humans

Humans perceive discrete events such as "restaurant visits" and "train rides" in their continuous experience. One important prerequisite for studying human event perception is the ability of researche

More...

CC BY

Computation and Language

Adversarial Judgments on the Article + Adjective + Numeral + Noun Construction

A Discerning Several Thousand Judgments: GPT-3 Rates the Article + Adjective + Numeral + Noun Construction

Knowledge of syntax includes knowledge of rare, idiosyncratic constructions (e.g., the article + adjective + numeral + noun construction).

Knowledge of such constructions requires knowledge of frequency biases that must be overcome in order to master such constructions.

CC BY

Software Engineering

Codex: A GPT-3 Based Model for Automatic Code Documentation Generation

Automatic Code Documentation Generation Using GPT-3

Source code documentation is an important artifact for efficient softwaredevelopment.

Manual documentation is often labouring, resource and time-intensive since manual documentation is often labouring, resource and time-intensive.

Computation and Language

Is GPT-3 a Good Data Annotator?

GPT-3 (Generative Pre-trained Transformer 3) is a large-scale autoregressive language model developed by OpenAI, which has demonstrated impressive few-shot performance on a wide range of natural langu

More...

Computation and Language

Memory-assisted prompt editing to improve GPT-3 after deployment

Large LMs such as GPT-3, while powerful, are not immune to mistakes, but are prohibitively costly to retrain. One failure mode is misinterpreting a user's instruction (e.g., GPT-3 interpreting "What w

More...

Bookmarked bySiddhesh

Machine Learning

Artificial Intelligence

Computation and Language

LoRA: Low-Rank Adaptation of Large Language Models

The dominant paradigm of natural language processing consists of large-scale pre-training on general domain data and adaptation to particular tasks or domains. As we pre-train larger models, conventio

More...

CC BY-SA

Computers and Society

Human-Computer Interaction

Artificial Intelligence

Can AI distinguish disinformation from accurate information?

AI model GPT-3 (dis)informs us better than humans

Artificial intelligence is changing the way we create and evaluate information, and this is happening during an infodemic, which has been having dramatic effects on global health.

In this paper we evaluate whether recruited individuals can distinguish disinformation from accurate information,structured in the form of tweets, and determine whether a tweet is organic or synthetic, i.e., whether it has been written by a twitter user or by the artificial intelligence model gpt-3.

Bookmarked byLuheng

Artificial Intelligence

Computation and Language

Want To Reduce Labeling Cost? GPT-3 Can Help

Data annotation is a time-consuming and labor-intensive process for many NLP tasks. Although there exist various methods to produce pseudo data labels, they are often task-specific and require a decen

More...

Human-Computer Interaction

Computation and Language

GPT-3-driven pedagogical agents for training children's curious question-asking skills

Students' ability to ask curious questions is a crucial skill that improves their learning processes. To train this skill, previous research has used a conversational agent that propose specific cues

More...

Artificial Intelligence

Computation and Language

Are Hard Examples also Harder to Explain? A Study with Human and Model-Generated Explanations

Recent work on explainable NLP has shown that few-shot prompting can enable large pretrained language models (LLMs) to generate grammatical and factual natural language explanations for data labels. I

More...

Computation and Language

What Makes Good In-Context Examples for GPT-$3$?

GPT-$3$ has attracted lots of attention due to its superior performance across a wide range of NLP tasks, especially with its powerful and versatile in-context few-shot learning ability. Despite its s

More...

Home

Discover

Bookmarks

◐ Latest Activity

◐ Recommended Follows