Questions tagged [question-answering]

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NLP: Checking that answers to a question are correct

Question answering is a common topic within NLP, but my problem is a little different: rather than answering a question, I have a question, an (open-ended) answer, and what I want to check is if that ...
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If Bert can handle only 512 inputs. Why you can provide such long contexts in QA Pipeline?

For example, I use Pipeline from Huggingface Transformers to use a QA model card like this. ...
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global contrast normalization implementation

I'm trying to understand figure 12.1 in Goodfellow available here. I'm not able to reproduce figure 12.1, and I'm wondering what is it I'm missing. The denominator of equation 12.3 is a constant, and ...
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How did AILabs Team get such performance in the superglue benchmark?

If we look at superglue (https://super.gluebenchmark.com/leaderboard) benchmark leaderboard, it may seem that AILabs does not perform super well. But if we look at the model card (https://super....
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How do pretrained models using SQUAD dataset work on an any other dataset?

I see in some Kaggle contests people have used models pretrained in SQUAD dataset for building QA systems for the dataset given in the contest. How does this work? How can a pretrained model in a ...
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How to generate a WH question for a given answer?

There are limited info regarding question generation compared to question answering. I have a bunch of notes and highlights gathered from books, webpages which I want to memorize and also build an ...
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Question answering bot: EM>F1, does it make sense?

I am fine-tuning a Question Answering bot starting from a pre-trained model from HuggingFace repo. The dataset I am using for the fine-tuning has a lot of empty answers. So, after the fine tuning, ...
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Scoring function for transformers (BERT etc)

While using BERT / transformers for NLP tasks, a major problem faced by us was to detect if the answer returned by model is correct or not, or what is the confidence level of the answer. The ...
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Pretrained models for Propositional logic

Are there any pretrained models which understand propositional logic? For example, the t5 model can do question-answering. Given a context such as "Alice is Bob's mother. Bob is Charlie's father&...
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Addressing polysemy in NLP tasks

Looking for modern algorithms using NN Language Model implementations addressing polysemy in NLP tasks, including text classification, question answering and topic modeling. Transfer/Zero-short ...
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learn information from text and resolve problem using transformers

Let's imagine that we have some question, like this: "x multiplied by x equals 9. What is x?" For this easy question answer is +-3. I want to make AI model answer on questions like that. To ...
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Best way to suggest answers given historical question-answer pairs

Many question-answering implementations focus on extracting information from large documents/corpora of text such as Wikipedia. I have access to a full chat log from the customer service of a large ...
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which script can be used to finetune BERT fro squad question answering in hugging face library

I have gone through lot of blogs which talk about run_squad.py script from hugging face, but I could not find it in the latest repo. So, which script has to be used ...
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How to pass input to deep learning models for Multiple choice question answering problem?

I'm currently working on a multiple-choice question answering system. The training set consists of a question, answer and 4 options and I need to predict the correct answer among 4 options. Sometimes ...
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How to process list type questions in Question Answering task [closed]

How to generate question-answer-context triplets for questions with multiple answer strings? How to measure performance for it? For a question with one single answer, we generate one question-answer-...
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Bert for QuestionAnswering input exceeds 512

I'm training Bert on question answering (in Spanish) and i have a large context, only the context exceeds 512, the total question + context is 10k, i found that longformer is bert like for long ...
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Closed Domain Question Answering which doesn't answer Questions

I've been exploring Closed Domain Question Answering Implementations which have been trained on SQuAD 2.0 dataset. Ideally, it should not answer questions which the context text corpus doesn't contain ...
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Select best answer from several existing ones for a question

After analyzing questions on a forum, a human support team has created a set of general answers, that can be used to provide basic answers on the forum. I am trying to build a system that: Selects ...
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Options to find the most similar question in a dataset of question-answer pairs?

I am building a chatbot that will only handle FAQs, but these FAQs are very specific to an organisation, so I cannot use any existing off-the-shelf solutions, or connect to question-answering APIs. I ...
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4 votes
2 answers
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Question answering (QA) vs Chatbots

Are Question answering (QA) the same as Chatbots? I can not understand the difference between them. For me it's the same thing: interact with a robot that answers questions.
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Meaningful Information retrieval and question answering for unstructured data - Is it even possible?

Hello good NLP people, I am working on a task that gradually seems not solvable for me. My data-set consists of long, messy, unstructured documents (pdfs, doc, docx, scans with tables, graphs, text, ...
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3 votes
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Answer to Question

Looking for a system which can generate answers to questions. Most systems and blogs posted on internet are on Question to answer but not on answer to question or paraphrasing or keyword to questions. ...
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1 vote
1 answer
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Measuring quality of answers from QnA systems

I am having a question answering system which is using Seq2Seq kind of architecture. Actually it is a transformer architecture. When a question is asked it gives startposition and endposition of ...
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1 answer
703 views

BERT - How Question answering is different than classification

Basically I am trying to understand how question answering works in case of BERT. Code for both classes QuestionAnswering and Classification is pasted below for reference. My understanding is: <...
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Is it possible to create a rule-based algorithm to compute the relevance score of question-answer pair?

In information retrieval or question answering system, we use TD-IDF or BM25 to compute the similarity score of question-question pair as the baseline or coarse ranking for deep learning. In ...
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