large language models

Research on AIGC-driven Footwear Intelligent Design Methods and Applications

ObjectiveThis research is aimed at solving the problems exposed by AIGC technology in the field of footwear design, such as generation homogeneity, low process feasibility, and market demand disconnection. A dedicated AIGC generation model and an intelligent design methodology for footwear design are built, which reali...

Confidence-Aware Autonomous Knowledge Graph Evolution for Lifelong Robotic TAMP Systems

Neuro-symbolic Task and Motion Planning (TAMP) architectures anchor Large Language Model (LLM) reasoning within a Knowledge Graph (KG) K to eliminate plan-level hallucinations, but letting K evolve autonomously across missions risks contaminating it with confidently-wrong facts that both the planner and the perception...

Confidence-Aware Autonomous Knowledge Graph Evolution for Lifelong Robotic TAMP Systems

Neuro-symbolic Task and Motion Planning (TAMP) architectures anchor Large Language Model (LLM) reasoning within a Knowledge Graph (KG) K to eliminate plan-level hallucinations, but letting K evolve autonomously across missions risks contaminating it with confidently-wrong facts that both the planner and the perception...

IDEAFix: An Evaluation Framework for Creative Defixation Prompting in LLMs

Dataset Card for Dataset Name This dataset accompanies the paper: "IDEAFix: An Evaluation Framework for Creative Defixation Prompting in LLMs," submitted to NeurIPS 2026. Dataset Details Dataset Description IDEAFix is a controlled evaluation dataset for studying divergent thinking and creative idea generation in Large...

IDEAFix: An Evaluation Framework for Creative Defixation Prompting in LLMs

Dataset Card for Dataset Name This dataset accompanies the paper: "IDEAFix: An Evaluation Framework for Creative Defixation Prompting in LLMs," submitted to NeurIPS 2026. Dataset Details Dataset Description IDEAFix is a controlled evaluation dataset for studying divergent thinking and creative idea generation in Large...

Replication Package for Creating the FairMedQA Benchmark and Conducting the Related Empirical Investigation

## 👀Overview**FairMedQA** is an adversarial medical question answering dataset for benchmarking the bias of large language models (LLMs) in the medical question answering context. FairMedQA is created from the U.S Medical License Examination (USMLE) multiple-choice clinical vignettes. Each sample includes: * An origin...

Polymer informatics: A review of ai-driven structure-property modeling and material design

Polymer science is undergoing a profound paradigm shift from labor-intensive, empirical trial-and-error experimentation to AI-guided, data-driven, and predictive material design. Owing to their multiscale structural diversity (spanning atomic connectivity, chain-packing behavior, and macroscopic morphology), polymer ma...

Bibliometric Analysis and Co-word Mapping: The Field of Knowledge Graphs

Purpose: The rapid expansion of research in the field of Knowledge Graphs (KGs) over the past decade has positioned The field as a dynamic area at the intersection of computer science, artificial intelligence. Following Google’s introduction of the KG in 2012, scholars and industry stakeholders have increasingly explor...

Use of a Large Language Model to Create a Neuropsychological Data Set From the Medical Record

Toward Domain-Specific Large Language Models in Construction Engineering: A Review of Development Tools

This paper aims to systematically review the development tools for domain-specific LLM specialization in construction engineering based on general-purpose LLM specialization and offers systematic and practical insights into the development tool ecosystem for domain-specific LLM specialization in construction engineerin...

An Analysis of Object Detection in Bad Weather Conditions using Deep Learning Models

Object detection, a task, in the field of computer vision faces obstacles when dealing with weather conditions such as fog, rain, snow, and low light situations. This paper provides an overview of advancements in the realm of object detection under challenging weather conditions. It delves into groundbreaking research...

Exploring the Landscape of Cloud Robotics: A Comprehensive Review

Cloud robotics is an innovative field that leverages cloud technologies-including cloud computing (CC), cloud storage, deep learning, big data, and the Internet of Things to augment the capabilities of robotics. This integration facilitates the execution of robotic functions through a converged infrastructure and share...