Search Results for author:
Found 13 papers, 5 papers with code
Aligning Large Language Models to a Domain-specific Graph Database
Graph Databases (Graph DB) are widely applied in various fields, including finance, social networks, and medicine.
Unsupervised Text Style Transfer via LLMs and Attention Masking with Multi-way Interactions
Among existing methods for UTST tasks, attention masking approach and Large Language Models (LLMs) are deemed as two pioneering methods.
Diffutoon: High-Resolution Editable Toon Shading via Diffusion Models
Toon shading is a type of non-photorealistic rendering task of animation.
Survey of Natural Language Processing for Education: Taxonomy, Systematic Review, and Future Trends
Natural Language Processing (NLP) aims to analyze text or speech via techniques in the computer science field.
Improving Zero-shot Visual Question Answering via Large Language Models with Reasoning Question Prompts
This results in a set of candidate answers.
FastBlend: a Powerful Model-Free Toolkit Making Video Stylization Easier
In the interpolation mode, FastBlend surpasses video interpolation and model-based video processing approaches.
Learning Knowledge-Enhanced Contextual Language Representations for Domain Natural Language Understanding
In the experiments, we evaluate KANGAROO over various knowledge-aware and general NLP tasks in both full and few-shot learning settings, outperforming various KEPLM training paradigms performance in closed-domains significantly.
Prompting Large Language Models with Chain-of-Thought for Few-Shot Knowledge Base Question Generation
Inspired by Chain-of-Thought (CoT) prompting, which is an in-context learning strategy for reasoning, we formulate KBQG task as a reasoning problem, where the generation of a complete question is splitted into a series of sub-question generation.
DualToken-ViT: Position-aware Efficient Vision Transformer with Dual Token Fusion
Position-aware global tokens also contain the position information of the image, which makes our model better for vision tasks.
DiffSynth: Latent In-Iteration Deflickering for Realistic Video Synthesis
In recent years, diffusion models have emerged as the most powerful approach in image synthesis.
Optimal Linear Subspace Search: Learning to Construct Fast and High-Quality Schedulers for Diffusion Models
In this paper, we first provide a detailed theoretical and empirical analysis of the generation process of the diffusion models based on schedulers.
Finding Global Homophily in Graph Neural Networks When Meeting Heterophily
Further, for other homophilous nodes excluded in the neighborhood, they are ignored for information aggregation.
Ranked #2 on
Node Classification
on pokec
Programming Knowledge Tracing: A Comprehensive Dataset and A New Model
More specifically, we construct a bipartite graph for programming problem embedding, and design an improved pre-training model PLCodeBERT for code embedding, as well as a double-sequence RNN model with exponential decay attention for effective feature fusion.
