Search Results for author:
Found 14 papers, 9 papers with code
The Devil is in the Few Shots: Iterative Visual Knowledge Completion for Few-shot Learning
Few-shot learning aims to further enhance the transfer capability of CLIP by giving few images in each class, aka 'few shots'.
MixRED: A Mix-lingual Relation Extraction Dataset
Relation extraction is a critical task in the field of natural language processing with numerous real-world applications.
Cobra Effect in Reference-Free Image Captioning Metrics
If a certain metric has flaws, it will be exploited by the model and reflected in the generated sentences.
EFUF: Efficient Fine-grained Unlearning Framework for Mitigating Hallucinations in Multimodal Large Language Models
Multimodal large language models (MLLMs) have attracted increasing attention in the past few years, but they may still generate descriptions that include objects not present in the corresponding images, a phenomenon known as object hallucination.
SeeClick: Harnessing GUI Grounding for Advanced Visual GUI Agents
In our preliminary study, we have discovered a key challenge in developing visual GUI agents: GUI grounding -- the capacity to accurately locate screen elements based on instructions.
M2DF: Multi-grained Multi-curriculum Denoising Framework for Multimodal Aspect-based Sentiment Analysis
Therefore, in this work, we focus on whether the negative impact of noisy images can be reduced without modifying the data.
Bounding and Filling: A Fast and Flexible Framework for Image Captioning
Several models adopted a non-autoregressive manner to speed up the process.
DRIN: Dynamic Relation Interactive Network for Multimodal Entity Linking
Multimodal Entity Linking (MEL) is a task that aims to link ambiguous mentions within multimodal contexts to referential entities in a multimodal knowledge base.
Food-500 Cap: A Fine-Grained Food Caption Benchmark for Evaluating Vision-Language Models
Experiments on our proposed datasets demonstrate that popular VLMs underperform in the food domain compared with their performance in the general domain.
ADS-Cap: A Framework for Accurate and Diverse Stylized Captioning with Unpaired Stylistic Corpora
Generating visually grounded image captions with specific linguistic styles using unpaired stylistic corpora is a challenging task, especially since we expect stylized captions with a wide variety of stylistic patterns.
Beyond Generic: Enhancing Image Captioning with Real-World Knowledge using Vision-Language Pre-Training Model
Considering that Vision-Language Pre-Training (VLP) models master massive such knowledge from large-scale web-harvested data, it is promising to utilize the generalizability of VLP models to incorporate knowledge into image descriptions.
Probing Cross-modal Semantics Alignment Capability from the Textual Perspective
In recent years, vision and language pre-training (VLP) models have advanced the state-of-the-art results in a variety of cross-modal downstream tasks.
Music-to-Text Synaesthesia: Generating Descriptive Text from Music Recordings
In this paper, we consider a novel research problem: music-to-text synaesthesia.
Learning Representation Mapping for Relation Detection in Knowledge Base Question Answering
However, one critical problem is that current approaches only get high accuracy for questions whose relations have been seen in the training data.
