To address the issue of insufficient knowledge and the tendency to generate hallucination in
Large Language Models (LLMs), numerous studies have endeavored to integrate LLMs with …

Large language models (LLMs) often require task-relevant knowledge to augment their
internal knowledge through prompts. However, simply injecting external knowledge into …

This paper describes the results of the Knowledge Graph Question Answering (KGQA)
shared task that was co-located with the TextGraphs 2024 workshop. In this task, given a …

This paper introduces a novel late interaction mechanism for knowledge base question
answering (KBQA) systems, combining Graphormer and transformer representations. We …

Large language models (LLMs) have demonstrated remarkable capabilities across various
domains, although their susceptibility to hallucination poses significant challenges for their …

The similarity between the question and indexed documents is a crucial factor in document
retrieval for retrieval-augmented question answering. Although this is typically the only …

Large Language Models (LLMs) face challenges due to hallucination issues. Current
solutions use retrieval-augmented generation (RAG), integrating LLMs with external …

Large Language Models (LLMs) have attracted a lot of attention in various fields due to their
superior performance, aiming to train hundreds of millions or more parameters on large …

In this work, we propose an efficient answer retrieval system** EARS**: a production-ready,
factual question answering (QA) system that combines local knowledge base search with …

Structured prediction in machine learning focuses on mapping a sequence of inputs to a
sequence of outputs within a vast output space, with interconnected predictions, offering …