Papers with Code 아카이브
Explanatory Visual Question Answering
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 1
- 평가표
- 1
- 보존된 평가 기록
- 5
Explanatory Visual Question Answering (EVQA) requires answering visual questions and generating multimodal explanations for the reasoning processes.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/qwenlm/qwen-vl
공식 코드Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond
https://github.com/szzexpoi/rex
공식 코드https://github.com/thudm/cogvlm
공식 코드https://github.com/2024-MindSpore-1/Code2/tree/main/model-1/cogvlm
https://github.com/AUCOHL/RTL-Repo
https://github.com/LivXue/FS-MEVQA
https://github.com/LivXue/VCIN
https://github.com/MS-P3/code5/tree/main/cogvlm
https://github.com/THUDM/CogAgent
https://github.com/brandon3964/multimodal-task-vector
Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond
https://github.com/dlvuldet/primevul
Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context
https://github.com/emrgnt-cmplxty/zero-shot-replication
https://github.com/eternityyw/tram-benchmark
https://github.com/ethz-privsec/superhuman-ai-consistency
https://github.com/ethz-spylab/superhuman-ai-consistency
https://github.com/explainableml/clevr-x
Faithful Multimodal Explanation for Visual Question Answering
https://github.com/gpt4life/alpagasus
https://github.com/lflage/openfactscore
https://github.com/shmsw25/factscore
https://github.com/unispac/visual-adversarial-examples-jailbreak-large-language-models
https://github.com/zach-zhiling-zheng/reticular_chemist
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.