Benchmark Dl Model Vision Language Drawing
%2C%20enabling%20multimodal%20processing%20of%20visual%20and%20linguistic%20data.%20However%2C%20their%20performance%20has%20been%20typically%20assessed%20on%20general%20scene%20understanding%20-%20recognizing%20objects%2C%20attributes%2C%20and%20actions%20-%20rather%20than%20cultural%20comprehension.%20This%20study%20introduces%20CulturalVQA%2C%20a%20visual%20question-answering%20benchmark%20aimed%20at%20assessing%20VLM's%20geo-diverse%20cultural%20understanding.%20We%20curate%20a%20collection%20of%202%2C378%20image-question%20pairs%20with%201-5%20answers%20per%20question%20representing%20cultures%20from%2011%20countries%20across%205%20continents.%20The%20questions%20probe%20understanding%20of%20various%20facets%20of%20culture%20such%20as%20clothing%2C%20food%2C%20drinks%2C%20rituals%2C%20and%20traditions.%20Benchmarking%20VLMs%20on%20CulturalVQA%2C%20including%20GPT-4V%20and%20Gemini%2C%20reveals%20disparity%20in%20their%20level%20of%20cultural%20understanding%20across%20regions%2C%20with%20strong%20cultural%20understanding%20capabilities%20for%20North%20America%20while%20significantly%20lower%20performance%20for%20Africa.%20We%20observe%20disparity%20in%20their%20performance%20across%20cultural%20facets%20too%2C%20with%20clothing%2C%20rituals%2C%20and%20traditions%20seeing%20higher%20performances%20than%20food%20and%20drink.%20These%20disparities%20help%20us%20identify%20areas%20where%20VLMs%20lack%20cultural%20understanding%20and%20demonstrate%20the%20potential%20of%20CulturalVQA%20as%20a%20comprehensive%20evaluation%20set%20for%20gauging%20VLM%20progress%20in%20understanding%20diverse%20cultures.)
%20for%20Image%20Classification_%20Performance%20Benchmarks.png?width=1000&height=556&name=Best%20Vision%20Language%20Models%20(VLMs)%20for%20Image%20Classification_%20Performance%20Benchmarks.png)
![[논문 리뷰] SPARK: Multi-Vision Sensor Perception and Reasoning Benchmark ...](https://moonlight-paper-snapshot.s3.ap-northeast-2.amazonaws.com/arxiv/spark-multi-vision-sensor-perception-and-reasoning-benchmark-for-large-scale-vision-language-models-0.png)
![[论文审查] THRONE: An Object-based Hallucination Benchmark for the Free ...](https://moonlight-paper-snapshot.s3.ap-northeast-2.amazonaws.com/arxiv/throne-an-object-based-hallucination-benchmark-for-the-free-form-generations-of-large-vision-language-models-1.png)
![[논문 리뷰] Multi-P$^2$A: A Multi-perspective Benchmark on Privacy ...](https://moonlight-paper-snapshot.s3.ap-northeast-2.amazonaws.com/arxiv/multi-p2a-a-multi-perspective-benchmark-on-privacy-assessment-for-large-vision-language-models-1.png)
%2C%20several%20attempts%20have%20been%20made%20to%20extend%20them%20to%20the%20visual%20domain.%20From%20having%20a%20visual%20assistant%20that%20could%20guide%20us%20through%20unfamiliar%20environments%20to%20generative%20models%20that%20produce%20images%20using%20only%20a%20high-level%20text%20description%2C%20the%20vision-language%20model%20(VLM)%20applications%20will%20significantly%20impact%20our%20relationship%20with%20technology.%20However%2C%20there%20are%20many%20challenges%20that%20need%20to%20be%20addressed%20to%20improve%20the%20reliability%20of%20those%20models.%20While%20language%20is%20discrete%2C%20vision%20evolves%20in%20a%20much%20higher%20dimensional%20space%20in%20which%20concepts%20cannot%20always%20be%20easily%20discretized.%20To%20better%20understand%20the%20mechanics%20behind%20mapping%20vision%20to%20language%2C%20we%20present%20this%20introduction%20to%20VLMs%20which%20we%20hope%20will%20help%20anyone%20who%20would%20like%20to%20enter%20the%20field.%20First%2C%20we%20introduce%20what%20VLMs%20are%2C%20how%20they%20work%2C%20and%20how%20to%20train%20them.%20Then%2C%20we%20present%20and%20discuss%20approaches%20to%20evaluate%20VLMs.%20Although%20this%20work%20primarily%20focuses%20on%20mapping%20images%20to%20language%2C%20we%20also%20discuss%20extending%20VLMs%20to%20videos.)
![[논문 리뷰] PM4Bench: A Parallel Multilingual Multi-Modal Multi-task ...](https://moonlight-paper-snapshot.s3.ap-northeast-2.amazonaws.com/arxiv/pm4bench-a-parallel-multilingual-multi-modal-multi-task-benchmark-for-large-vision-language-model-1.png)
![[2305.06500] InstructBLIP: Towards General-purpose Vision-Language ...](https://ar5iv.labs.arxiv.org/html/2305.06500/assets/x2.png)
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