https://github.com/forjadeforest/icd-lm
공식 코드Lever LM: Configuring In-Context Sequence to Lever Large Vision Language Models
Papers with Code 아카이브
Visual Question Answering
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/forjadeforest/lever-lm
공식 코드Lever LM: Configuring In-Context Sequence to Lever Large Vision Language Models
https://github.com/forjadeforest/live-learnable-in-context-vector
공식 코드LIVE: Learnable In-Context Vector for Visual Question Answering
https://github.com/foundation-multimodal-models/world2code
공식 코드https://github.com/freedomintelligence/allava
공식 코드ALLaVA: Harnessing GPT4V-Synthesized Data for Lite Vision-Language Models
https://github.com/freedomintelligence/trim
공식 코드Less is More: A Simple yet Effective Token Reduction Method for Efficient Multi-modal LLMs
https://github.com/fualsan/datwep
공식 코드Dynamic Task and Weight Prioritization Curriculum Learning for Multimodal Imagery
https://github.com/fudannlplab/mousi
공식 코드https://github.com/fujitsuresearch/transformer_module_networks
공식 코드Transformer Module Networks for Systematic Generalization in Visual Question Answering
https://github.com/function2-llx/mmmm
공식 코드VividMed: Vision Language Model with Versatile Visual Grounding for Medicine
https://github.com/furkanbiten/object-bias
공식 코드Let there be a clock on the beach: Reducing Object Hallucination in Image Captioning
https://github.com/gabegrand/adversarial-vqa
공식 코드Adversarial Regularization for Visual Question Answering: Strengths, Shortcomings, and Side Effects
https://github.com/garygutc/lapa_model
공식 코드LaPA: Latent Prompt Assist Model For Medical Visual Question Answering
https://github.com/garyjiajia/ofv2_icl_vqa
공식 코드How to Configure Good In-Context Sequence for Visual Question Answering
https://github.com/gautierdag/cast
공식 코드CAST: Cross-modal Alignment Similarity Test for Vision Language Models
https://github.com/gazkune/spatiallm
공식 코드https://github.com/gewu-lab/mwafm
공식 코드https://github.com/gewu-lab/pstp-net
공식 코드Progressive Spatio-temporal Perception for Audio-Visual Question Answering
https://github.com/gewu-lab/tspm
공식 코드Boosting Audio Visual Question Answering via Key Semantic-Aware Cues
https://github.com/ghazaleh-mahmoodi/lxmert_compression
공식 코드https://github.com/gicheonkang/DAN-VisDial
공식 코드Dual Attention Networks for Visual Reference Resolution in Visual Dialog
https://github.com/glamor-usc/climb
공식 코드https://github.com/gls0425/linvt
공식 코드LinVT: Empower Your Image-level Large Language Model to Understand Videos
https://github.com/gmparg/ICLP2018
공식 코드A Trajectory Calculus for Qualitative Spatial Reasoning Using Answer Set Programming
https://github.com/gmum/3d-point-clouds-autocomplete
공식 코드https://github.com/gogoduan/got-r1
공식 코드GoT-R1: Unleashing Reasoning Capability of MLLM for Visual Generation with Reinforcement Learning
https://github.com/google-research-datasets/conceptual-12m
공식 코드Conceptual 12M: Pushing Web-Scale Image-Text Pre-Training To Recognize Long-Tail Visual Concepts
https://github.com/google-research-datasets/maverics
공식 코드https://github.com/google-research-datasets/maxm
공식 코드https://github.com/google-research/big_vision
공식 코드https://github.com/google-research/google-research
공식 코드Encyclopedic VQA: Visual questions about detailed properties of fine-grained categories
https://github.com/google-research/language
공식 코드Fusion of Detected Objects in Text for Visual Question Answering
https://github.com/google-research/long-range-arena
공식 코드https://github.com/google-research/scenic
공식 코드Location-Aware Self-Supervised Transformers for Semantic Segmentation
https://github.com/google-research/scenic/tree/main/scenic/projects/knowledge_visual_language
공식 코드https://github.com/google/haloquest
공식 코드HaloQuest: A Visual Hallucination Dataset for Advancing Multimodal Reasoning
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.