Questions tagged [question-answering]
For questions about the question answering discipline, which is concerned with building systems that automatically answer questions posed by humans in a natural language.
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How does an AI like ChatGPT answer a question in a subject which it may not know?
After seeing StackOverflow's banning of ChatGPT, I explored it out of curiosity. It's marvellous as it can write code by itself!
Later to check if it knows chess as well like Google-Deepmind's ...
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Can Bayesian inference be combined with knowledge-based systems?
I've been struggling with the connection between knowledge-based AI systems and Bayesian inference for a while now. While I continue to sweep through the literature, I would be happy if someone can ...
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Why does nobody use decision trees for visual question answering?
I'm starting a project that will involve computer vision, visual question answering, and explainability. I am currently choosing what type of algorithm to use for my classifier - a neural network or a ...
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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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How can I translate a natural language question to an MDX query?
I am researching Natural Language Processing (NLP) to develop an NL Question Answering system. The answering part is already done. So processing the question remains, along with the questions ...
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Which algorithm is used in the robot Sophia to understand and answers the questions?
Which algorithm is used in the robot Sophia to understand and answer the questions?
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Which parsing algorithm can I use for NLP question answering system?
I am currently working on my last project before graduating. For this project, I have to develop a Natural Language Question Answering System. Now, I have read quite some research papers regarding ...
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Is there a machine learning system that is able to understand mathematical problems given in a textual description?
Is there a machine learning system that is able to "understand" mathematical problems given in a textual description, such as
A big cat needs 4 days to catch all the mice and a small cat ...
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ChatGPT claims that it doesn't get information from anywhere, so can't say why it gave a blatantly false statement. How is that possible?
I asked ChatGPT a question, and its response included this statement:
In "The Ruling Class" film, which was released in 1972, Patrick McGoohan played the role of Bishop Lampton.
Unlike ...
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2
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Is there a service that can search for answers to general questions? [closed]
I was looking for an API service where I can ask it a general question (for example, when was Einstein born?) and retrieve an answer from the web.
Is there any available service to do that? Have ...
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How to fine tune BERT for question answering?
I wish to train two domain-specific models:
Domain 1: Constitution and related Legal Documents
Domain 2: Technical and related documents.
For Domain 1, I've access to a text-corpus with texts from ...
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What are the advantages of Machine Learning compared to traditional programming for developing a chatbot?
I am currently building a chatbot. What I have done so far is, collected possible questions/training data/files and create a model out of it using Apache OpenNLP; the model is able to predict all the ...
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2
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How to generate a dataset for question answering from books (like Facebook's bAbI)?
I wanted to train a chatbot for answering questions from books. I am trying to use Dynamic Memory Networks to do so.
How can I generate a data set, as Facebook did in the case of bAbI tasks, so that ...
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What chatbots can answer this type of simple question that only requires to keep track of the context?
I have tried with two chat-bots Cleverbot and Alan, and I got disappointing results.
me: Socrates is a man
bot: blah blah (common bot nonsense instead of an "ok")
me: Who is a man?
alan1: ...
user5977
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Why fine tuning does not work as well as RAG?
I cannot find a definite answer to this question. Suppose I want to build a QA (question answering) system on a set of personal documents. It looks that RAG (retrieval augmented generation) is the way ...
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What is the "question" when using Dynamic Memory Networks to do part-of-speech tagging and sentiment analysis?
In the paper Ask Me Anything: Dynamic Memory Networks for Natural Language Processing the authors described a Dynamic Memory Network in the context of question answering. Then, they also tested the ...
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How to generate a response while considering past questions as well?
User: What is the tallest mountain?
Agent: Everest
User: Where is it located? # Agent hears: "Where is Everest located?"
Agent: Nepal
I want to be able ...
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Can Facebook's LASER be used like BERT?
Can Facebook's LASER be fine-tuned like BERT for Question Answering tasks or Sentiment Analysis?
From my understanding, they created an embedding that allows for similar words in different languages ...
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Will structured knowledge bases continue to be used in question answering with the likes of BERT gaining popularity?
This may come across as an open and opinion-based question, I definitely want to hear expert opinions on the subject, but I am also looking for references to materials that I can read deeply.
One of ...
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Are there any approaches other than deep learning to deal with unexpected questions in a question answering system?
I'm working on a question answering bot as my graduation project. The main concept is having a text file with many sentences, and building a question answering bot which answers a user's question ...
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Filter scientific papers based on abstract information
I have a data frame that contains different numbers of columns, the important ones are:
Title Abstract
The length (number of words) varies between each row, with a ...
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How to disapprove some who says that AI is capable of irrational thought and emotions
A teacher of mine said something of about AI being self sufficient and operating on experience. They backed this statement by this example-a car programmed to avoid ramming into apple, mango and banna ...
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Why are Mistral LLMs branded as enabling RAG-QA (Retrieval-Augmented Generation for Question Answering)?
I read on https://mistral.ai/news/mistral-large/:
Mistral Small benefits from the same innovation as Mistral Large regarding RAG-enablement and function calling.
What do they mean by RAG-enablement? ...
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How does ChatGPT assign confidence level?
How does ChatGPT assign confidence level to its answer? What is the mathematical description of it?
Here is my guess. It produces many answers from auto-regression. It already has a probability ...
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Why is generative QA + RAG so popular when extractive QA models exist that can provide factual information?
If the concern with using generative models for question answering is that these models aren't always producing factual information, why is it that people are using these models with Retrieval ...
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How big the context can be using HuggingFace models?
I'm new on AI, Neural Networks, ChatBots and all this ecosystem. I'm trying to use a classical example of pre-trained models, more specifically ...
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Do Poe AI, Open AI and Claude AI have the ability to retain information from previous queries or remember previous responses?
Do Poe AI, Open AI,and Claude AI have the ability to retain information from previous queries or remember previous responses?
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Do Poe AI, Open AI, and Claude AI generate all answers from training data, including factual and logical answers or from personal information?
Do Poe AI, Open AI, and Claude AI generate all answers from training data, including factual and logical answers or from firsthand personal information?
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How does query of LLM/GPT models work?
Training of LLM aka GPT models is clear on how is trained but can't find any info how is "mapped" query to internal tokens and generates response tokens more precise inference phase which ...
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NLP: Question answer with 2 contexts
Is there a Hugging Face Transformer that takes 2 contexts as input for question answering? For example, I could have transcript of a meeting in first context and agenda of the meeting in the second ...
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In-batch negative training Improves the results
I have read Dense passage retrieval for Open Domain Question Answering, and in page 6 it talks about in-batch negative training, it states the following:
We find that using a similar
configuration (7 ...
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Is there an unsupervised learning method for determine the most common questions within a dataset?
I have a dataset consisting of questions from customers. I am curious of the n most frequent asked questions, regardless of the variation the questions might appear in.
Is there NLP methods for ...
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Is there a survey that describes the most effective approaches for an answer retrieval problem?
I have a dataset that contains pairs of a question and an answer. My problem is to train a model that can search for the right answer from the pool of my answers given the newly input question, so ...
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Dynamic text completion [closed]
I am using the get_completion function to generate response to a question. Since generating response takes a long time (~5 seconds) I would like to display the response text as it's generated (...
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