scienceqa

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Hamidreza-Talei / efficient-vlm-inference-and-lora-finetuning

Efficient Vision-Language Model inference and LoRA fine-tuning on ScienceQA, with dynamic resolution, visual-token compression, latency analysis, and accuracy–efficiency trade-offs using Qwen3.5-0.8B.

transformers pytorch lora dynamic-resolution vlm fine-tuning multimodal-learning peft multimodal huggingface model-efficiency vision-language-model qwen scienceqa qwen3 visual-tokens

Updated Aug 19, 2026
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osmajic-mihaela / vqa-paligemma

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Fine tunned PaliGemma vision-language models using the ScienceQA dataset for visual question answering.

visual-question-answering vision-language-model paligemma scienceqa

Updated Oct 23, 2024
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saeidrznr / vlm-finetuning

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Vision-Language Model fine-tuning and evaluation on ScienceQA using Qwen3.5, LoRA, and PEFT.

machine-learning computer-vision deep-learning transformers pytorch artificial-intelligence lora vlm fine-tuning multimodal huggingface large-language-models vision-language-model qwen qwen-vl multimodal-ai scienceqa

Updated Jul 15, 2026
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Veeraja-Veeraesh / Inference-Using-LLaVA-and-SteerFair

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Mitigating positional bias in LLaVA 1.5 (7B) on ScienceQA via per-head activation steering & PCA.

attention bias-mitigation huggingface-transformers scienceqa llava7b

Updated May 17, 2025
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