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Found 39 papers, 12 papers with code
Using Mixed Incentives to Document Xi’an Guanzhong
This paper describes our use of mixed incentives and the citizen science portal LanguageARC to prepare, collect and quality control a large corpus of object namings for the purpose of providing speech data to document the under-represented Guanzhong dialect of Chinese spoken in the Shaanxi province in the environs of Xi’an.
Controllable GUI Exploration
During the early stages of interface design, designers need to produce multiple sketches to explore a design space.
BloomScene: Lightweight Structured 3D Gaussian Splatting for Crossmodal Scene Generation
To this end, we propose BloomScene, a lightweight structured 3D Gaussian splatting for crossmodal scene generation, which creates diverse and high-quality 3D scenes from text or image inputs.
Toward Robust Incomplete Multimodal Sentiment Analysis via Hierarchical Representation Learning
Specifically, we propose a fine-grained representation factorization module that sufficiently extracts valuable sentiment information by factorizing modality into sentiment-relevant and modality-specific representations through crossmodal translation and sentiment semantic reconstruction.
MedAide: Towards an Omni Medical Aide via Specialized LLM-based Multi-Agent Collaboration
Large Language Model (LLM)-driven interactive systems currently show potential promise in healthcare domains.
nextlocllm: next location prediction using LLMs
Experiments show that NextLocLLM outperforms existing models in next location prediction, excelling in both supervised and zero-shot settings.
DreamStruct: Understanding Slides and User Interfaces via Synthetic Data Generation
Enabling machines to understand structured visuals like slides and user interfaces is essential for making them accessible to people with disabilities.
Dark Miner: Defend against undesired generation for text-to-image diffusion models
Most existing methods focus on modifying the generation probabilities conditioned on the texts containing target concepts.
Self-supervised Learning for Geospatial AI: A Survey
The proliferation of geospatial data in urban and territorial environments has significantly facilitated the development of geospatial artificial intelligence (GeoAI) across various urban applications.
A New Dataset, Notation Software, and Representation for Computational Schenkerian Analysis
Schenkerian Analysis (SchA) is a uniquely expressive method of music analysis, combining elements of melody, harmony, counterpoint, and form to describe the hierarchical structure supporting a work of music.
UrbanLLM: Autonomous Urban Activity Planning and Management with Large Language Models
Location-based services play an critical role in improving the quality of our daily lives.
SAGDFN: A Scalable Adaptive Graph Diffusion Forecasting Network for Multivariate Time Series Forecasting
Time series forecasting is essential for our daily activities and precise modeling of the complex correlations and shared patterns among multiple time series is essential for improving forecasting performance.
CoMT: Chain-of-Medical-Thought Reduces Hallucination in Medical Report Generation
Automatic medical report generation (MRG), which possesses significant research value as it can aid radiologists in clinical diagnosis and report composition, has garnered increasing attention.
Enhancing Criminal Case Matching through Diverse Legal Factors
In this paper, we propose a two-stage framework named Diverse Legal Factor-enhanced Criminal Case Matching (DLF-CCM).
Detecting and Evaluating Medical Hallucinations in Large Vision Language Models
To bridge this gap, we introduce Med-HallMark, the first benchmark specifically designed for hallucination detection and evaluation within the medical multimodal domain.
PediatricsGPT: Large Language Models as Chinese Medical Assistants for Pediatric Applications
In the parameter-efficient secondary SFT phase, a mixture of universal-specific experts strategy is presented to resolve the competency conflict between medical generalist and pediatric expertise mastery.
Impact of Design Decisions in Scanpath Modeling
We show that even small variations of these design parameters have a noticeable impact on standard evaluation metrics such as DTW or Eyenalysis.
Efficiency in Focus: LayerNorm as a Catalyst for Fine-tuning Medical Visual Language Pre-trained Models
In the realm of Medical Visual Language Models (Med-VLMs), the quest for universal efficient fine-tuning mechanisms remains paramount, especially given researchers in interdisciplinary fields are often extremely short of training resources, yet largely unexplored.
Medical Visual Question Answering
parameter-efficient fine-tuning
+2
Graph4GUI: Graph Neural Networks for Representing Graphical User Interfaces
Present-day graphical user interfaces (GUIs) exhibit diverse arrangements of text, graphics, and interactive elements such as buttons and menus, but representations of GUIs have not kept up.
EyeFormer: Predicting Personalized Scanpaths with Transformer-Guided Reinforcement Learning
From a visual perception perspective, modern graphical user interfaces (GUIs) comprise a complex graphics-rich two-dimensional visuospatial arrangement of text, images, and interactive objects such as buttons and menus.
Can LLMs' Tuning Methods Work in Medical Multimodal Domain?
In this paper, we delve into the fine-tuning methods of LLMs and conduct extensive experiments to investigate the impact of fine-tuning methods for large models on the existing multimodal model in the medical domain from the training data level and the model structure level.
MISS: A Generative Pretraining and Finetuning Approach for Med-VQA
Medical visual question answering (VQA) is a challenging multimodal task, where Vision-Language Pre-training (VLP) models can effectively improve the generalization performance.
RS-Corrector: Correcting the Racial Stereotypes in Latent Diffusion Models
Extensive empirical evaluations demonstrate that the introduced \themodel effectively corrects the racial stereotypes of the well-trained Stable Diffusion model while leaving the original model unchanged.
Large Language Model based Long-tail Query Rewriting in Taobao Search
In the realm of e-commerce search, the significance of semantic matching cannot be overstated, as it directly impacts both user experience and company revenue.
DeltaSpace: A Semantic-aligned Feature Space for Flexible Text-guided Image Editing
Based on DeltaSpace, we propose a novel framework called DeltaEdit, which maps the CLIP visual feature differences to the latent space directions of a generative model during the training phase, and predicts the latent space directions from the CLIP textual feature differences during the inference phase.
ILuvUI: Instruction-tuned LangUage-Vision modeling of UIs from Machine Conversations
Multimodal Vision-Language Models (VLMs) enable powerful applications from their fused understanding of images and language, but many perform poorly on UI tasks due to the lack of UI training data.
AXNav: Replaying Accessibility Tests from Natural Language
Recently, Large Language Models (LLMs) have been used for a variety of tasks including automation of UIs, however to our knowledge no one has yet explored their use in controlling assistive technologies for the purposes of supporting accessibility testing.
Few-Shot Domain Adaptation for Charge Prediction on Unprofessional Descriptions
Recent works considering professional legal-linguistic style (PLLS) texts have shown promising results on the charge prediction task.
InfoStyler: Disentanglement Information Bottleneck for Artistic Style Transfer
InfoStyler formulates the disentanglement representation learning as an information compression problem by eliminating style statistics from the content image and removing the content structure from the style image.
3D-Aware Adversarial Makeup Generation for Facial Privacy Protection
The privacy and security of face data on social media are facing unprecedented challenges as it is vulnerable to unauthorized access and identification.
HiFECap: Monocular High-Fidelity and Expressive Capture of Human Performances
Furthermore, we show that HiFECap outperforms the state-of-the-art human performance capture approaches qualitatively and quantitatively while for the first time capturing all aspects of the human.
DFGC 2022: The Second DeepFake Game Competition
There is a two-party game between DeepFake creators and defenders.
ReverseORC: Reverse Engineering of Resizable User Interface Layouts with OR-Constraints
Furthermore, it can be used to detect and fix problems in legacy UIs, extend UIs with enhanced layout behaviours, and support the creation of flexible UI layouts.
Enhancing Cross-lingual Prompting with Dual Prompt Augmentation
Prompting shows promising results in few-shot scenarios.
BacHMMachine: An Interpretable and Scalable Model for Algorithmic Harmonization for Four-part Baroque Chorales
Algorithmic harmonization - the automated harmonization of a musical piece given its melodic line - is a challenging problem that has garnered much interest from both music theorists and computer scientists.
ORCSolver: An Efficient Solver for Adaptive GUI Layout with OR-Constraints
OR-constrained (ORC) graphical user interface layouts unify conventional constraint-based layouts with flow layouts, which enables the definition of flexible layouts that adapt to screens with different sizes, orientations, or aspect ratios with only a single layout specification.
ORC Layout: Adaptive GUI Layout with OR-Constraints
We propose a novel approach for constraint-based graphical user interface (GUI) layout based on OR-constraints (ORC) in standard soft/hard linear constraint systems.
Human-Computer Interaction Graphics
SDFDiff: Differentiable Rendering of Signed Distance Fields for 3D Shape Optimization
We propose SDFDiff, a novel approach for image-based shape optimization using differentiable rendering of 3D shapes represented by signed distance functions (SDFs).
Ranked #1 on
Single-View 3D Reconstruction
on ShapeNet
(using extra training data)
