Questions tagged [natural-language-understanding]
For questions related to natural language understanding (NLU), which is a subtopic of natural language processing (NLP) that deals with machine reading comprehension. Natural-language understanding is considered a hard problem.
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How does ChatGPT cope with multiple negations
I tried to challenge ChatGPT with answering questions on prompts with multiple negations.
Q2: Paul didn't believe that Peter was right when he said that he didn't believe that Gil had betrayed him. ...
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What would be the best approach to resume longer texts in one word?
I am trying to create a model capable of resuming longer texts (my dataset has up to 140 words for each instance) in a single word (or multiple separate words). The idea is to synthetize positive or ...
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How does GPT-based language model like ChatGPT determine the n-th letter of a word?
I understand that GPT models process input text by converting words into tokens and then embedding vectors and do not process them letter by letter. Given this approach, I am curious to know how a ...
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What puts the "chat" in a system like ChatGPT?
So I read Wolfram's What Is ChatGPT Doing … and Why Does It Work? but it left one really big question in my mind. His summary [if it could be called that!] really emphasizes that the core model is ...
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Derive contextual meaning from response data
I have a website, which has a questionnaire defined, for showing to users.
And for each, entry, we have the option for the questionnaire response to be filled.
I am unable to find any tool that can ...
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Is the "Chinese room" an explanation of how ChatGPT works?
Sorry if this question makes no sense. I'm a software developer but know very little about AI.
Quite a while ago, I read about the Chinese room, and the person inside who has had a lot of training/...
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What is the "state of the art" in (at least partially) symbolic/logic-based chat bots/AI assistants?
ChatGPT has had a lot of buzz around it recently, and for good reason. It has shown some amazing capabilities in responding to new information, as well as in generalizing new information that has been ...
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Given a document and a set of keywords. I want to calculate how well each keyword describes the document
The question is in the title, but here is an example:
Context: "I often go swimming in the ocean"
Keywords: "water", "bird", ...
The keyword water + context should output ...
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Does chatGPT learn or remember from (public) user input? Will it 'fess up to it? I could not get it to reveal [closed]
It started with a question inspired by this video:
New Research Suggests to Put AI to Sleep
https://youtu.be/0yuQlbCkTJ0
She says: "In this video I discuss a new research paper which suggest a ...
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How is ChatGPT maintaining context?
It has been suggested in the answer to this earlier question that it is just remembering a certain amount of recent information. The reference used is this post by OpenAI which says that ChatGPT ...
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How to perform domain adaptation if there are only unlabelled data in both source and target domains
Recently I am reading literature regarding domain adaption. However, most of the works consider scenarios when there are some labelled data in the source domain. So I wonder if there is any ...
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How does ChatGPT respond to novel prompts and commands?
So I understand how a language model could scan a large data set like the internet and produce text that mimicked the statistical properties of the input data, eg completing a sentence like "eggs ...
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How does ChatGPT know math?
ChatGPT is a language model. As far as I know and If I'm not wrong, it gets text as tokens and word embeddings. So, how can it do math? For example, I asked:
ME: Which one is bigger 5 or 9.
ChatGPT: ...
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How does ChatGPT retain the context of previous questions?
One of the innovations with OpenAI's ChatGPT is how natural it is for users to interact with it.
What is the technical enabler for ChatGPT to maintain the context of previous questions in its answers? ...
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How to develop an Entity linking system able to detect custom entities?
I am trying to build an entity linking system that links entities found in a text to entities on Wikipedia. If no Wikipedia page seems to match this entity, the systems will assume to have found a new ...
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Are custom tokens better than punctuation pseudo-tokens for LLMs?
I've seen two approaches for introducing custom tokens for transfer learning with large language models like Bert or GPT3. Some approaches introduce new tokens into the vocabulary and learn embeddings ...
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What is the role of self loop in Hidden Markov Models(HMM)?
What actually does the self-loop (within the single hidden state ) in the Hidden Markov model helpful for?
I learn that one of the use cases concerning Natural language Understanding is that it helps ...
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How do I preload a conversational AI assistant like GPT-3 with complex relational data to draw on?
I'm exploring options to build a virtual assistant type of product.
Creating good dialog is mostly solved with GPT-3 or even DialoGPT.
My main question is how do I add larger amounts of relational ...
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How do I use A.I. to analyse & score news articles?
I'm working on a project that would benefit from using A.I. or machine learning to analyse news feeds from a variety of websites and grade each article between 0 and 10. We would manually grade ...
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How might AI analyze abusive discussion using natural language grammar?
Opening thoughts
This does not only apply to SE comments, but the idea in general.
This is not a Question for Linguistics.SE; those Questions might come later, after AI analysis. Example Linguistics ...
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Among N documents, how to summarize the most unique content in each document?
I now have $N$ documents, which share common content and they have special unique content.
Say I have $3$ legal documents related to the same person. Document $A$ is about land law, document $B$ is ...
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Is there something like person-specific sentiment analysis?
Sentiment analysis, as we know, measures "Cake sucks" as say -0.4, and "Cake is great" as 0.7.
What I'm looking for is something a bit different like so:
Given input text data ...
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How to measure the similarity the pronunciation of two words?
I would like to know how I could measure the pronunciation of two words. These two words are quite similar and differ only in one vowel.
I know there is, e.g., the Hamming distance or the Levenshtein ...
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What is the best way to generate German paraphrases?
What is the best method to generate German paraphrases? The state-of-the-art are seq2seq transformer models, like T5, but they only work for English sentences. I found the multilingual MT5 model, but ...
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Text matching: fuzzy names matching with learning
I'm new to AI/ML and I want to research and learn about techniques that could help me to solve this complex task. Any hint would be appreciated.
Let me explain it with an example:
Let's look at two ...
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Can unsupervised models learn something from cat vocalizations?
I love cats, and over the years have noticed that they have recurrent patterns of vocalizations. For example, upon seeing a bird, a cat may start chittering, but the same cat would never chitter at ...
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Extracting values from text based on keywords
I am trying to read a PDF file and put it in Python string and trying to fetch information based on keywords. The text here is completely irregular.
Example of text
Blockquote
Ram has taken an ...
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How would one disambiguate between two meanings of the same word in a sentence?
The boy lifted the bat and hit the ball.
In the above sentence, the noun "bat" means the wooden stick. It does not mean bat, the flying mammal, which is also a noun. Using NLP libraries to ...
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Is there any neural network model that can perform multiple NLP steps at once?
I realize most NLP algorithms have multiple steps. (e.g. OCR/speech rec > syntax > semantics > response logic > semantic output > natural language output)
Is there any NN model that can ...
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What dataset might Elon Musk's Dall-E have used?
Dall-E, it can generate many imaginative images from the description, even some peculiar images, how did they actually create this kind of dataset to train this AI , because there is not much of that ...
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How to extract parameters from a text using AI/NLP
lets say I have three texts:
"make a heading that says hello word"
"make a heading of hello world"
"create heading consist of hello world"
How can I fetch those groups ...
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What is MNLI-(m/mm)?
I came across the term MNLI-(m/mm) in Table 1 of the paper BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. I know what MNLI stands for, i.e. Multi-Genre Natural ...
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Are there any meaningful books entirely written by an artificial intelligence?
Are there any meaningful books entirely written by an artificial intelligence? I mean something with meaning, unlike random words or empty books.
Something that can be charactersed as fiction ...
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Is there a complement to GPT/2/3 that can be trained using supervised learning methods?
This is a bit of a soft question, not sure if it's on topic, please let me know how I can improve it if it doesn't meet the criteria for the site.
GPT models are unsupervised in nature and are (from ...
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Is it possible to classify the subject of a conversation?
I would like to classify the subject of a conversation. I could classify each messages of the conversation, but I will loose some imformation because of related messages.
I also need to do it ...
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How could facts be distinguished from opinions?
As a software engineer, I am searching for an existing solution or, if none exists, willing to create one that will be able to process texts (e.g. news from online media) to extract/paraphrase dry ...
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Can in principle GPT language models learn physics?
Does anyone know of research involving the GPT models to learn not only regular texts, but also learn from physics books with the equations written in latex format?
My intuition is that the model ...
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How homographs is an NLP task can be treated?
A homograph - is a word that shares the same written form as another word but has a different meaning.
They can be even different parts of speech. For example:
close(verb) - close(adverb)
lead(verb)...
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How to predict the "word" based on the meaning in a document?
What I mean to say is
For example, if I give the meaning of Apple from the dictionary as input to the program, it should give output as Apple.
Or I say My day to day job involves monitoring and ...
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How is the F1 score calculated in a question-answering system?
I have an NLP model for answer-extraction. So, basically, I have a paragraph and a question as input, and my model extracts the span of the paragraph that corresponds to the answer to the question.
I ...
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Can text-independent writer identification be done without multi-sentence training datasets for each writer?
I am trying to learn more about text-independent writer identification and was hoping for some advice.
I have a folder with 100k images, each of them with a different handwritten sentence. All of the ...
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When to use NLP, NLG and NLU in conversation agents?
I had read some blogs (like 1, 2 or 3) about what the difference between all three of them is. I am trying to build an open domain conversation agent using natural language AI. That agent can do ...
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How can I make ELIZA more realistic?
I’ve coded a simple ELIZA chatbot for a high school coding competition. The chatbot is part of an app that’s designed to help its user cope with depression, anxiety, and similar mental health ...
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Designing a chatbot personal project with zero coding experience, using an existing platform
My girlfriend has a masters degree in linguistics and would like to create an AI chatbot personal project to show potential employers her linguistics skills since she is struggling to find a job.
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How well can NLP techniques recognize connotations in natural languages?
What is the state of the art with respect to recognizing connotations in natural languages?
For instance:
Trump is a better president than Obama. [Praising]
Trump is the worst president ...
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How would you build an AI to output the primary concept of a paragraph?
My thinking is you input a paragraph, or sentence, and the program can boil it down to the primary concept(s).
Example:
Input:
Sure, it would be nice if morality was simply a navigation toward ...
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What are the challenges faced by using NLP to convert mathematical texts into formal logic?
From what I've figured
(a) converting mathematical theorems and proofs from English to formal logic is a straightforward job for mathematicians with sufficient background, except that it takes time.
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What are the current research trends in recognizing narrative similarity?
I am currently working on a term paper on the topic of Narrative Similarity, based on Loizos Michael's work "Similarity of Narratives". I am trying to find the latest trends within this field of study ...
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What are the current big challenges in natural language processing and understanding?
I'm doing a paper for a class on the topic of big problems that are still prevalent in AI, specifically in the area of natural language processing and understanding. From what I understand, the areas:
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Can a computer identify the philosophical concept on which a given story is based?
Say you have to enter a story to a computer. Now, the computer has to identify the philosophical concept on which the story is based, say:
Was it a "self-fulfilling prophecy"?
Was it an ...
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