相关论文: Web-STAR: Towards a Visual Web-Based IDE for a Sto…
We present STAR: a novel system aimed at solving the complex issue of "p-hacking" and false discoveries in scientific studies. STAR provides a concrete way for ensuring the application of false discovery control procedures in hypothesis…
The present study proposes LitStoryTeller, an interactive system for visually exploring the semantic structure of a scientific article. We demonstrate how LitStoryTeller could be used to answer some of the most fundamental research…
This paper develops a Reasoning about Actions and Change framework integrated with Default Reasoning, suitable as a Knowledge Representation and Reasoning framework for Story Comprehension. The proposed framework, which is guided strongly…
Answering complex visual questions like `Which red furniture can be used for sitting?' requires multi-step reasoning, including object recognition, attribute filtering, and relational understanding. Recent work improves interpretability in…
Table retrieval is the task of retrieving the most relevant tables from large-scale corpora given natural language queries. However, structural and semantic discrepancies between unstructured text and structured tables make embedding…
Explainable AI (XAI) can greatly enhance user trust and satisfaction in AI-assisted decision-making processes. Recent findings suggest that a single explainer may not meet the diverse needs of multiple users in an AI system; indeed, even…
The online communities available on the Web have shown to be significantly interactive and capable of collectively solving difficult tasks. Nevertheless, it is still a challenge to decide how a task should be dispatched through the network…
GrayStar is a stellar atmospheric and spectral line modelling, post-processing, and visualisation code, suitable for classroom demonstrations and laboratory-style assignments, that has been developed in Java and deployed in JavaScript and…
GrayStar is a stellar atmospheric and spectral line modelling, post-processing, and visualisation code, suitable for classroom demonstrations and laboratory-style assignments, that has been developed in Java and deployed in JavaScript and…
RubyStar is a dialog system designed to create "human-like" conversation by combining different response generation strategies. RubyStar conducts a non-task-oriented conversation on general topics by using an ensemble of rule-based,…
In this paper is analyzed the prototyping of the information visualization on a Web Application for community purposes in a collaborative environment representing an evolution of the actual social networks like Facebook, Instagram, Twitter,…
Here we describe the SHARE system, a web service based framework for distributed querying and reasoning on the semantic web. The main innovations of SHARE are: (1) the extension of a SPARQL query engine to perform on-demand data retrieval…
Information extraction tasks such as event extraction require an in-depth understanding of the output structure and sub-task dependencies. They heavily rely on task-specific training data in the form of (passage, target structure) pairs to…
Multimodal large language models (MLLMs) have demonstrated remarkable potential in bridging visual and textual reasoning, yet their reliance on text-centric priors often limits their ability to disentangle semantically similar actions in…
Recently, large language models (LLMs) have shown remarkable reasoning capabilities via large-scale reinforcement learning (RL). However, leveraging the RL algorithm to empower effective multi-tool collaborative reasoning in LLMs remains an…
A new type of statistical analysis of the science and technical information (STI) in the Web context is produced. We propose a set of indicators about Web users, visualized bibliographic records, and e-commercial transactions. In addition,…
Structured spatial navigation is a core benchmark for Large Language Models (LLMs) spatial reasoning. Existing paradigms like Visualization-of-Thought (VoT) are prone to cascading errors in complex topologies. To solve this, we propose…
Time series classification is a task of paramount importance, as this kind of data often arises in safety-critical applications. However, it is typically tackled with black-box deep learning methods, making it hard for humans to understand…
Design processes involve exploration, iteration, and movement across interconnected stages such as persona creation, problem framing, solution ideation, and prototyping. However, time and resource constraints often hinder designers from…
Systems for story generation are asked to produce plausible and enjoyable stories given an input context. This task is underspecified, as a vast number of diverse stories can originate from a single input. The large output space makes it…