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Found 7 papers, 5 papers with code
How to Configure Good In-Context Sequence for Visual Question Answering
Inspired by the success of Large Language Models in dealing with new tasks via In-Context Learning (ICL) in NLP, researchers have also developed Large Vision-Language Models (LVLMs) with ICL capabilities.
Learning Part Segmentation from Synthetic Animals
We then benchmark Syn-to-Real animal part segmentation from SAP to PartImageNet, namely SynRealPart, with existing semantic segmentation domain adaptation methods and further improve them as our second contribution.
Animal3D: A Comprehensive Dataset of 3D Animal Pose and Shape
Animal3D consists of 3379 images collected from 40 mammal species, high-quality annotations of 26 keypoints, and importantly the pose and shape parameters of the SMAL model.
Ranked #1 on
Animal Pose Estimation
on Animal3D
Enhancing Language Representation with Constructional Information for Natural Language Understanding
We adopt usage-based construction grammar as the basis of our work, which is highly compatible with statistical models such as PLMs.
Transforming Visual Scene Graphs to Image Captions
In TSG, we apply multi-head attention (MHA) to design the Graph Neural Network (GNN) for embedding scene graphs.
FCGEC: Fine-Grained Corpus for Chinese Grammatical Error Correction
Grammatical Error Correction (GEC) has been broadly applied in automatic correction and proofreading system recently.
Ranked #1 on
Grammatical Error Correction
on FCGEC
Learn from Structural Scope: Improving Aspect-Level Sentiment Analysis with Hybrid Graph Convolutional Networks
Aspect-level sentiment analysis aims to determine the sentiment polarity towards a specific target in a sentence.
Ranked #1 on
Aspect-Based Sentiment Analysis (ABSA)
on Rest16
