VRep at SemEval-2016 Task 1 and Task 2: A System for Interpretable Semantic Similarity
Code (0)
등록된 구현이 없습니다.
Tasks
Semantic SimilaritySemantic Textual SimilarityTask 2Similar Papers 제목 키워드 기반
Contrastive Learning of Semantic and Visual Representations for Text Tracking
Semantic representation is of great benefit to the video text tracking(VTT) task that requires simultaneously classifying, detecting, and tracking texts in the video. Most existing approaches tackle this task by appearan…
Contrastive LearningEvRepSL: Event-Stream Representation via Self-Supervised Learning for Event-Based Vision
Event-stream representation is the first step for many computer vision tasks using event cameras. It converts the asynchronous event-streams into a formatted structure so that conventional machine learning models can be …
Event-based visionOptical Flow EstimationSelf-Supervised LearningLLM-EvRep: Learning an LLM-Compatible Event Representation Using a Self-Supervised Framework
Recent advancements in event-based recognition have demonstrated significant promise, yet most existing approaches rely on extensive training, limiting their adaptability for efficient processing of event-driven visual c…
SVRepair: Structured Visual Reasoning for Automated Program Repair
Large language models (LLMs) have recently shown strong potential for Automated Program Repair (APR), yet most existing approaches remain unimodal and fail to leverage the rich diagnostic signals contained in visual arti…
Visual ReasoningProgram RepairPodlab at SemEval-2019 Task 3: The Importance of Being Shallow
This paper describes our linear SVM system for emotion classification from conversational dialogue, entered in SemEval2019 Task 3. We used off-the-shelf tools coupled with feature engineering and parameter tuning to crea…
ClassificationEmotion ClassificationFeature EngineeringGeneral Classification