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Found 14 papers, 9 papers with code
Re-examining the Role of Schema Linking in Text-to-SQL
By providing a schema linking corpus based on the Spider text-to-SQL dataset, we systematically study the role of schema linking.
Preview-based Category Contrastive Learning for Knowledge Distillation
It first distills the structural knowledge of both instance-level feature correspondence and the relation between instance features and category centers in a contrastive learning fashion, which can explicitly optimize the category representation and explore the distinct correlation between representations of instances and categories, contributing to discriminative category centers and better classification results.
Social Debiasing for Fair Multi-modal LLMs
Multi-modal Large Language Models (MLLMs) have advanced significantly, offering powerful vision-language understanding capabilities.
SHE-Net: Syntax-Hierarchy-Enhanced Text-Video Retrieval
In particular, text-video retrieval, which aims to find the top matching videos given text descriptions from a vast video corpus, is an essential function, the primary challenge of which is to bridge the modality gap.
SNP-S3: Shared Network Pre-training and Significant Semantic Strengthening for Various Video-Text Tasks
By employing one shared BERT-type network to refine textual and cross-modal features simultaneously, SNP is lightweight and could support various downstream applications.
Knowledge-enhanced Multi-perspective Video Representation Learning for Scene Recognition
With the explosive growth of video data in real-world applications, a comprehensive representation of videos becomes increasingly important.
RTQ: Rethinking Video-language Understanding Based on Image-text Model
Recent advancements in video-language understanding have been established on the foundation of image-text models, resulting in promising outcomes due to the shared knowledge between images and videos.
Ranked #9 on
Video Retrieval
on MSR-VTT-1kA
EVE: Efficient zero-shot text-based Video Editing with Depth Map Guidance and Temporal Consistency Constraints
Compared with images, we conjecture that videos necessitate more constraints to preserve the temporal consistency during editing.
Temporal Sentence Grounding in Streaming Videos
The goal of TSGSV is to evaluate the relevance between a video stream and a given sentence query.
Micro-video Tagging via Jointly Modeling Social Influence and Tag Relation
Existing methods mostly focus on analyzing video content, neglecting users' social influence and tag relation.
CHMATCH: Contrastive Hierarchical Matching and Robust Adaptive Threshold Boosted Semi-Supervised Learning
In the meantime, we make full use of the structured information in the hierarchical labels to learn an accurate affinity graph for contrastive learning.
CNVid-3.5M: Build, Filter, and Pre-Train the Large-Scale Public Chinese Video-Text Dataset
Though there are certain methods studying the Chinese video-text pre-training, they pre-train their models on private datasets whose videos and text are unavailable.
Stacked Hybrid-Attention and Group Collaborative Learning for Unbiased Scene Graph Generation
Scene Graph Generation, which generally follows a regular encoder-decoder pipeline, aims to first encode the visual contents within the given image and then parse them into a compact summary graph.
Ranked #1 on
Unbiased Scene Graph Generation
on Visual Genome
(mR@20 metric)
Explicit Interaction Model towards Text Classification
To address this problem, we introduce the interaction mechanism to incorporate word-level matching signals into the text classification task.
Ranked #4 on
Text Classification
on Yahoo! Answers
