Fact Selection
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Benchmarks
ArgSciChat
Most implemented
ArgSciChat: A Dataset for Argumentative Dialogues on Scientific Papers
Integrating Randomness in Large Language Models: A Linear Congruential Generator Approach for Generating Clinically Relevant Content
UFO: Unified Fact Obtaining for Commonsense Question Answering
Expository Text Generation: Imitate, Retrieve, Paraphrase
COVID-VTS: Fact Extraction and Verification on Short Video Platforms
Papers
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 Generation