https://github.com/AFeng-x/Draw-and-Understand
공식 코드Draw-and-Understand: Leveraging Visual Prompts to Enable MLLMs to Comprehend What You Want
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
Draw-and-Understand: Leveraging Visual Prompts to Enable MLLMs to Comprehend What You Want
Mamba-Enhanced Text-Audio-Video Alignment Network for Emotion Recognition in Conversations
Multilevel Hierarchical Network with Multiscale Sampling for Video Question Answering
Towards Explainable Multimodal Depression Recognition for Clinical Interviews
Foundations and Recent Trends in Multimodal Mobile Agents: A Survey
Cross-Modal Implicit Relation Reasoning and Aligning for Text-to-Image Person Retrieval
Spatio-Temporal 3D Point Clouds from WiFi-CSI Data via Transformer Networks
Dialogue-based generation of self-driving simulation scenarios using Large Language Models
Recurrent Multimodal Interaction for Referring Image Segmentation
ViLT: Vision-and-Language Transformer Without Convolution or Region Supervision
MM-BigBench: Evaluating Multimodal Models on Multimodal Content Comprehension Tasks
Stream-Omni: Simultaneous Multimodal Interactions with Large Language-Vision-Speech Model
Ming-Lite-Uni: Advancements in Unified Architecture for Natural Multimodal Interaction
UniMEL: A Unified Framework for Multimodal Entity Linking with Large Language Models
LLMs Can Evolve Continually on Modality for X-Modal Reasoning
OVTR: End-to-End Open-Vocabulary Multiple Object Tracking with Transformer
CFN-ESA: A Cross-Modal Fusion Network with Emotion-Shift Awareness for Dialogue Emotion Recognition
MMoE: Enhancing Multimodal Models with Mixtures of Multimodal Interaction Experts
ChartSketcher: Reasoning with Multimodal Feedback and Reflection for Chart Understanding
Adaptive Contrastive Learning on Multimodal Transformer for Review Helpfulness Predictions
Multi-Grained Multimodal Interaction Network for Entity Linking
I2MoE: Interpretable Multimodal Interaction-aware Mixture-of-Experts
Dissecting Dissonance: Benchmarking Large Multimodal Models Against Self-Contradictory Instructions
Narrative Action Evaluation with Prompt-Guided Multimodal Interaction
TIP: Tabular-Image Pre-training for Multimodal Classification with Incomplete Data
Cooperative Sentiment Agents for Multimodal Sentiment Analysis
LOOK-M: Look-Once Optimization in KV Cache for Efficient Multimodal Long-Context Inference
Temporal Pyramid Transformer with Multimodal Interaction for Video Question Answering
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.