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Visual Question Answering
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/wskbest/mfc-bench
공식 코드MFC-Bench: Benchmarking Multimodal Fact-Checking with Large Vision-Language Models
https://github.com/wuhy68/p-adapter
공식 코드p-Laplacian Adaptation for Generative Pre-trained Vision-Language Models
https://github.com/wujunjie1998/tri-he
공식 코드Unified Triplet-Level Hallucination Evaluation for Large Vision-Language Models
https://github.com/wutaiqiang/moslora
공식 코드https://github.com/wyk-nku/distinguishing-vqa
공식 코드https://github.com/wzzheng/doe
공식 코드Doe-1: Closed-Loop Autonomous Driving with Large World Model
https://github.com/x-plug/mplug-halowl
공식 코드Hallucination Augmented Contrastive Learning for Multimodal Large Language Model
https://github.com/x-plug/mplug-owl
공식 코드mPLUG-Owl2: Revolutionizing Multi-modal Large Language Model with Modality Collaboration
https://github.com/x2fd/lvis-instruct4v
공식 코드To See is to Believe: Prompting GPT-4V for Better Visual Instruction Tuning
https://github.com/xdao85/vnhsge
공식 코드VNHSGE: VietNamese High School Graduation Examination Dataset for Large Language Models
https://github.com/xiandaguo/drive-mllm
공식 코드https://github.com/xiaoduoailab/xmodelvlm
공식 코드Xmodel-VLM: A Simple Baseline for Multimodal Vision Language Model
https://github.com/xiaohao-xu/ambiguity-in-space
공식 코드Towards Ambiguity-Free Spatial Foundation Model: Rethinking and Decoupling Depth Ambiguity
https://github.com/xiaojino/RUArt
공식 코드RUArt: A Novel Text-Centered Solution for Text-Based Visual Question Answering
https://github.com/xiaoman-zhang/PMC-VQA
공식 코드PMC-VQA: Visual Instruction Tuning for Medical Visual Question Answering
https://github.com/xiaowu0162/visualize-then-retrieve
공식 코드https://github.com/xijun-cs/vila
공식 코드ViLA: Efficient Video-Language Alignment for Video Question Answering
https://github.com/xing0047/cca-llava
공식 코드Mitigating Object Hallucination via Concentric Causal Attention
https://github.com/xingruiwang/3d-aware-vqa
공식 코드3D-Aware Visual Question Answering about Parts, Poses and Occlusions
https://github.com/xingruiwang/spatial457
공식 코드Spatial457: A Diagnostic Benchmark for 6D Spatial Reasoning of Large Multimodal Models
https://github.com/xli04/cvqa
공식 코드MM-Prompt: Cross-Modal Prompt Tuning for Continual Visual Question Answering
https://github.com/xuliu-cyber/rsunivlm
공식 코드https://github.com/y-d-wang/rsadapter
공식 코드RSAdapter: Adapting Multimodal Models for Remote Sensing Visual Question Answering
https://github.com/yangliu9208/cmcir
공식 코드Cross-Modal Causal Relational Reasoning for Event-Level Visual Question Answering
https://github.com/yangyue5114/DME
공식 코드Dynamic Multimodal Evaluation with Flexible Complexity by Vision-Language Bootstrapping
https://github.com/yanx27/clevr3d
공식 코드Comprehensive Visual Question Answering on Point Clouds through Compositional Scene Manipulation
https://github.com/yanxinzju/CSS-VQA
공식 코드Counterfactual Samples Synthesizing for Robust Visual Question Answering
https://github.com/yashkant/concat-vqa
공식 코드https://github.com/yashkant/sam-textvqa
공식 코드https://github.com/yehli/xmodaler
공식 코드X-modaler: A Versatile and High-performance Codebase for Cross-modal Analytics
https://github.com/yellow-binary-tree/pfram
공식 코드Understanding Multimodal Hallucination with Parameter-Free Representation Alignment
https://github.com/yfyuan01/ravenea
공식 코드RAVENEA: A Benchmark for Multimodal Retrieval-Augmented Visual Culture Understanding
https://github.com/yhzhu99/medagentboard
공식 코드https://github.com/yihedeng9/stic
공식 코드Enhancing Large Vision Language Models with Self-Training on Image Comprehension
https://github.com/yikai-wang/asuka-misato
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.