Papers Generative Question Answering
“Generative Question Answering” 태그가 달린 논문 48편 · 필터 해제
BenHalluEval: A Multi-Task Hallucination Evaluation Framework for Large Language Models on Bengali
Despite Bengali being the sixth most spoken language in the world, no prior work has systematically evaluated hallucination in large language models (LLMs) for Bengali. We introduce BenHalluEval, a fine-grained hallucina…
Generative Question AnsweringGenerative Active Testing: Efficient LLM Evaluation via Proxy Task Adaptation
With the widespread adoption of pre-trained Large Language Models (LLM), there exists a high demand for task-specific test sets to benchmark their performance in domains such as healthcare and biomedicine. However, the c…
Generative Question AnsweringAraHalluEval: A Fine-grained Hallucination Evaluation Framework for Arabic LLMs
Recently, extensive research on the hallucination of the large language models (LLMs) has mainly focused on the English language. Despite the growing number of multilingual and Arabic-specific LLMs, evaluating LLMs' hall…
Generative Question AnsweringBeyond Profile: From Surface-Level Facts to Deep Persona Simulation in LLMs
Previous approaches to persona simulation large language models (LLMs) have typically relied on learning basic biographical information, or using limited role-play dialogue datasets to capture a character's responses. Ho…
Generative Question AnsweringMultiple-choiceQuestion AnsweringStyle TransferEvidenceMap: Learning Evidence Analysis to Unleash the Power of Small Language Models for Biomedical Question Answering
When addressing professional questions in the biomedical domain, humans typically acquire multiple pieces of information as evidence and engage in multifaceted evidence analysis to provide high-quality answers. Current L…
Answer GenerationGenerative Question AnsweringLanguage ModelingLanguage Modelling+2Evidence-Enhanced Triplet Generation Framework for Hallucination Alleviation in Generative Question Answering
To address the hallucination in generative question answering (GQA) where the answer can not be derived from the document, we propose a novel evidence-enhanced triplet generation framework, EATQA, encouraging the model t…
Generative Question AnsweringHallucinationQuestion AnsweringTripletTowards a Generative Approach for Emotion Detection and Reasoning
Large language models (LLMs) have demonstrated impressive performance in mathematical and commonsense reasoning tasks using chain-of-thought (CoT) prompting techniques. But can they perform emotional reasoning by concate…
Emotion RecognitionGenerative Question AnsweringNatural Language InferenceQuestion AnsweringANAH: Analytical Annotation of Hallucinations in Large Language Models
Reducing the `$\textit{hallucination}$' problem of Large Language Models (LLMs) is crucial for their wide applications. A comprehensive and fine-grained measurement of the hallucination is the first key step for the gove…
Generative Question AnsweringHallucinationQuestion AnsweringSentenceChatSOS: Vector Database Augmented Generative Question Answering Assistant in Safety Engineering
With the rapid advancement of natural language processing technologies, generative artificial intelligence techniques, represented by large language models (LLMs), are gaining increasing prominence and demonstrating sign…
Generative Question AnsweringInformation RetrievalQuestion AnsweringRetrievalMitigating LLM Hallucinations via Conformal Abstention
We develop a principled procedure for determining when a large language model (LLM) should abstain from responding (e.g., by saying "I don't know") in a general domain, instead of resorting to possibly "hallucinating" a …
Conformal PredictionGenerative Question AnsweringHallucinationLanguage Modelling+4Reshaping Free-Text Radiology Notes Into Structured Reports With Generative Transformers
BACKGROUND: Radiology reports are typically written in a free-text format, making clinical information difficult to extract and use. Recently the adoption of structured reporting (SR) has been recommended by various medi…
Generative Question AnsweringInformation RetrievalLanguage ModellingLarge Language Model+1Two-stage Generative Question Answering on Temporal Knowledge Graph Using Large Language Models
Temporal knowledge graph question answering (TKGQA) poses a significant challenge task, due to the temporal constraints hidden in questions and the answers sought from dynamic structured knowledge. Although large languag…
Answer GenerationGenerative Question AnsweringGraph Neural NetworkGraph Question Answering+1Does the Generator Mind its Contexts? An Analysis of Generative Model Faithfulness under Context Transfer
The present study introduces the knowledge-augmented generator, which is specifically designed to produce information that remains grounded in contextual knowledge, regardless of alterations in the context. Previous rese…
Generative Question AnsweringHallucinationMachine TranslationQuestion AnsweringVerif.ai: Towards an Open-Source Scientific Generative Question-Answering System with Referenced and Verifiable Answers
In this paper, we present the current progress of the project Verif.ai, an open-source scientific generative question-answering system with referenced and verified answers. The components of the system are (1) an informa…
Generative Question AnsweringInformation RetrievalMisinformationQuestion Answering+1A Search for Prompts: Generating Structured Answers from Contracts
In many legal processes being able to action on the concrete implication of a legal question can be valuable to automating human review or signalling certain conditions (e.g., alerts around automatic renewal). To support…
Generative Question AnsweringIn-Context LearningQuestion AnsweringTraining Generative Question-Answering on Synthetic Data Obtained from an Instruct-tuned Model
This paper presents a simple and cost-effective method for synthesizing data to train question-answering systems. For training, fine-tuning GPT models is a common practice in resource-rich languages like English, however…
Generative Question AnsweringQuestion AnsweringSequence-to-Sequence Spanish Pre-trained Language Models
In recent years, significant advancements in pre-trained language models have driven the creation of numerous non-English language variants, with a particular emphasis on encoder-only and decoder-only architectures. Whil…
DecoderGenerative Question AnsweringNatural Language UnderstandingQuestion Answering+1Retrieving Supporting Evidence for Generative Question Answering
Current large language models (LLMs) can exhibit near-human levels of performance on many natural language-based tasks, including open-domain question answering. Unfortunately, at this time, they also convincingly halluc…
Generative Question AnsweringOpen-Domain Question AnsweringQuestion AnsweringRetrievalBenchmarks for Pirá 2.0, a Reading Comprehension Dataset about the Ocean, the Brazilian Coast, and Climate Change
Pir\'a is a reading comprehension dataset focused on the ocean, the Brazilian coast, and climate change, built from a collection of scientific abstracts and reports on these topics. This dataset represents a versatile la…
Generative Question AnsweringInformation RetrievalMachine Reading ComprehensionMultiple-choice+2Prompt Generate Train (PGT): Few-shot Domain Adaption of Retrieval Augmented Generation Models for Open Book Question-Answering
We propose a framework - Prompt, Generate, Train (PGT) - to efficiently develop a generative question-answering model for open-book question-answering over a proprietary collection of text documents. The framework adapts…
Domain AdaptationGenerative Question AnsweringQuestion AnsweringRAG+3