Search Results for author:
Found 17 papers, 5 papers with code
AltCLIP: Altering the Language Encoder in CLIP for Extended Language Capabilities
In this work, we present a conceptually simple and effective method to train a strong bilingual/multilingual multimodal representation model.
SegMamba: Long-range Sequential Modeling Mamba For 3D Medical Image Segmentation
Our SegMamba, in contrast to Transformer-based methods, excels in whole volume feature modeling from a state space model standpoint, maintaining superior processing speed, even with volume features at a resolution of {$64\times 64\times 64$}.
TACO: Topics in Algorithmic COde generation dataset
Moreover, each TACO problem includes several fine-grained labels such as task topics, algorithms, programming skills, and difficulty levels, providing a more precise reference for the training and evaluation of code generation models.
Ranked #1 on
Code Generation
on TACO-Code
AltDiffusion: A Multilingual Text-to-Image Diffusion Model
Specifically, we first train a multilingual text encoder based on the knowledge distillation.
Adversarial Mixing Policy for Relaxing Locally Linear Constraints in Mixup
To address these issues, we propose the Adversarial Mixing Policy (AMP), organized in a min-max-rand formulation, to relax the Locally Linear Constraints in Mixup.
Hierarchical Context Enhanced Multi-Domain Dialogue System for Multi-domain Task Completion
Task 1 of the DSTC8-track1 challenge aims to develop an end-to-end multi-domain dialogue system to accomplish complex users' goals under tourist information desk settings.
Research on Annotation Rules and Recognition Algorithm Based on Phrase Window
At present, most Natural Language Processing technology is based on the results of Word Segmentation for Dependency Parsing, which mainly uses an end-to-end method based on supervised learning.
Research on multi-dimensional end-to-end phrase recognition algorithm based on background knowledge
The algorithm can not only introduce background knowledge, recognize all kinds of nested phrases in sentences, but also recognize the dependency between phrases.
DialogueTRM: Exploring the Intra- and Inter-Modal Emotional Behaviors in the Conversation
Emotion Recognition in Conversations (ERC) is essential for building empathetic human-machine systems.
A Diversity-Enhanced and Constraints-Relaxed Augmentation for Low-Resource Classification
Previous studies mostly use a fine-tuned Language Model (LM) to strengthen the constraints but ignore the fact that the potential of diversity could improve the effectiveness of generated data.
Self-Supervised Prime-Dual Networks for Few-Shot Image Classification
We construct a prime-dual network structure for few-shot learning which establishes a commutative relationship between the support set and the query set, as well as a new self- supervision constraint for highly effective few-shot learning.
DialogueTRM: Exploring Multi-Modal Emotional Dynamics in a Conversation
Emotion dynamics formulates principles explaining the emotional fluctuation during conversations.
PTab: Using the Pre-trained Language Model for Modeling Tabular Data
The learning of an effective contextual representation requires meaningful features and a large amount of data.
UniTabE: A Universal Pretraining Protocol for Tabular Foundation Model in Data Science
This research primarily centers on classification and regression tasks involving tabular data, and conducts rigorous experimental testing and analyses to validate the effectiveness of our methodology.
CoIE: Chain-of-Instruct Editing for Multi-Attribute Face Manipulation
Current text-to-image editing models often encounter challenges with smoothly manipulating multiple attributes using a single instruction.
CMMU: A Benchmark for Chinese Multi-modal Multi-type Question Understanding and Reasoning
Current multi-modal benchmarks for domain-specific knowledge concentrate on multiple-choice questions and are predominantly available in English, which imposes limitations on the comprehensiveness of the evaluation.
