Papers Fact Selection
“Fact Selection” 태그가 달린 논문 15편 · 필터 해제
PROPEX-RAG: Enhanced GraphRAG using Prompt-Driven Prompt Execution
Retrieval-Augmented Generation (RAG) has become a robust framework for enhancing Large Language Models (LLMs) with external knowledge. Recent advances in RAG have investigated graph based retrieval for intricate reasonin…
Multi-hop Question AnsweringAnswer GenerationFact SelectionIntegrating Randomness in Large Language Models: A Linear Congruential Generator Approach for Generating Clinically Relevant Content
Generating diverse, high-quality outputs from language models is crucial for applications in education and content creation. Achieving true randomness and avoiding repetition remains a significant challenge. This study u…
Fact SelectionLanguage ModelingLanguage ModellingUFO: Unified Fact Obtaining for Commonsense Question Answering
Leveraging external knowledge to enhance the reasoning ability is crucial for commonsense question answering. However, the existing knowledge bases heavily rely on manual annotation which unavoidably causes deficiency in…
Fact SelectionQuestion AnsweringRetrievalExpository Text Generation: Imitate, Retrieve, Paraphrase
Expository documents are vital resources for conveying complex information to readers. Despite their usefulness, writing expository text by hand is a challenging process that requires careful content planning, obtaining …
Fact SelectionRetrievalText GenerationCOVID-VTS: Fact Extraction and Verification on Short Video Platforms
We introduce a new benchmark, COVID-VTS, for fact-checking multi-modal information involving short-duration videos with COVID19- focused information from both the real world and machine generation. We propose, TwtrDetect…
Fact CheckingFact SelectionFact VerificationProto-Gen: An end-to-end neural generator for persona and knowledge grounded response generation
In this paper we detail the implementation of Proto-Gen, an end-to-end neural response generator capable of selecting appropriate persona and fact sentences from available options, and generating persona and fact grounde…
DecoderFact SelectionResponse GenerationKG-CRuSE: Recurrent Walks over Knowledge Graph for Explainable Conversation Reasoning using Semantic Embeddings
Knowledge-grounded dialogue systems utilise external knowledge such as knowledge graphs to generate informative and appropriate responses. A crucial challenge of such systems is to select facts from a knowledge graph per…
DecoderFact SelectionKnowledge GraphsResponse GenerationFaiRR: Faithful and Robust Deductive Reasoning over Natural Language
Transformers have been shown to be able to perform deductive reasoning on a logical rulebase containing rules and statements written in natural language. Recent works show that such models can also produce the reasoning …
Fact SelectionLogical ReasoningArgSciChat: A Dataset for Argumentative Dialogues on Scientific Papers
The applications of conversational agents for scientific disciplines (as expert domains) are understudied due to the lack of dialogue data to train such agents. While most data collection frameworks, such as Amazon Mecha…
Fact SelectionResponse GenerationFaiRR: Faithful and Robust Deductive Reasoning over Natural Language
Transformers have been shown to be able to perform deductive reasoning on a logical rulebase containing rules and statements written in natural language. Recent works show that such models can also produce the reasoning …
Fact SelectionLogical ReasoningCausalR: Causal Reasoning over Natural Language Rulebases
Transformers have been shown to perform deductive reasoning on a logical rulebase containing rules and statements written in natural language. Recent works show that such models can also produce the reasoning steps (i.e.…
Fact SelectionLogical ReasoningSimple Question Answering with Subgraph Ranking and Joint-Scoring
Knowledge graph based simple question answering (KBSQA) is a major area of research within question answering. Although only dealing with simple questions, i.e., questions that can be answered through a single knowledge …
Fact SelectionQuestion AnsweringRelationThe combination of context information to enhance simple question answering
With the rapid development of knowledge base,question answering based on knowledge base has been a hot research issue. In this paper, we focus on answering singlerelation factoid questions based on knowledge base. We bui…
Fact SelectionKnowledge Base Question AnsweringQuestion AnsweringPattern-revising Enhanced Simple Question Answering over Knowledge Bases
Question Answering over Knowledge Bases (KB-QA), which automatically answer natural language questions based on the facts contained by a knowledge base, is one of the most important natural language processing (NLP) task…
Entity LinkingFact SelectionQuestion AnsweringRetrievalSimple Question Answering by Attentive Convolutional Neural Network
This work focuses on answering single-relation factoid questions over Freebase. Each question can acquire the answer from a single fact of form (subject, predicate, object) in Freebase. This task, simple question answeri…
Entity LinkingFact SelectionQuestion Answering