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Found 14 papers, 9 papers with code
A Pretraining Numerical Reasoning Model for Ordinal Constrained Question Answering on Knowledge Base
Knowledge Base Question Answering (KBQA) is to answer natural language questions posed over knowledge bases (KBs).
Plan-Then-Execute: An Empirical Study of User Trust and Team Performance When Using LLM Agents As A Daily Assistant
Our findings demonstrate that LLM agents can be a double-edged sword -- (1) they can work well when a high-quality plan and necessary user involvement in execution are available, and (2) users can easily mistrust the LLM agents with plans that seem plausible.
Is Conversational XAI All You Need? Human-AI Decision Making With a Conversational XAI Assistant
In comparison to an XAI dashboard, we found that the conversational XAI interface can bring about a better understanding of the AI system among users and higher user trust.
Fine-Grained Appropriate Reliance: Human-AI Collaboration with a Multi-Step Transparent Decision Workflow for Complex Task Decomposition
Previous empirical studies have extensively analyzed the impact of factors ranging from task, system, and human behavior on user trust and appropriate reliance in the context of one-step decision making.
To Err Is AI! Debugging as an Intervention to Facilitate Appropriate Reliance on AI Systems
Inspired by existing literature on critical thinking and a critical mindset, we propose the use of debugging an AI system as an intervention to foster appropriate reliance.
Power-up! What Can Generative Models Do for Human Computation Workflows?
We identify junctures in typical crowdsourcing workflows at which the introduction of LLMs can play a beneficial role and propose means to augment existing design patterns for crowd work.
Knowing About Knowing: An Illusion of Human Competence Can Hinder Appropriate Reliance on AI Systems
This paper addresses an under-explored problem of whether the Dunning-Kruger Effect (DKE) among people can hinder their appropriate reliance on AI systems.
Complex Knowledge Base Question Answering: A Survey
Knowledge base question answering (KBQA) aims to answer a question over a knowledge base (KB).
A Survey on Complex Knowledge Base Question Answering: Methods, Challenges and Solutions
In this paper, we elaborately summarize the typical challenges and solutions for complex KBQA.
Improving Multi-hop Knowledge Base Question Answering by Learning Intermediate Supervision Signals
In our approach, the student network aims to find the correct answer to the query, while the teacher network tries to learn intermediate supervision signals for improving the reasoning capacity of the student network.
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TextBox: A Unified, Modularized, and Extensible Framework for Text Generation
In this paper, we release an open-source library, called TextBox, to provide a unified, modularized, and extensible text generation framework.
Knowledge-Enhanced Personalized Review Generation with Capsule Graph Neural Network
First, based on graph capsules, we adaptively learn aspect capsules for inferring the aspect sequence.
Mining Implicit Entity Preference from User-Item Interaction Data for Knowledge Graph Completion via Adversarial Learning
Our generator is isolated from user interaction data, and serves to improve the performance of the discriminator.
KB4Rec: A Dataset for Linking Knowledge Bases with Recommender Systems
Based on our linked dataset, we first preform some interesting qualitative analysis experiments, in which we discuss the effect of two important factors (i. e. popularity and recency) on whether a RS item can be linked to a KB entity.
