Official repository of paper "GraFIQs: Face Image Quality Assessment Using Gradient Magnitudes"
The official implementation of the paper "ViTNT-FIQA: Training-Free Face Image Quality Assessment with Vision Transformers", accepted at WACV2026 Workshops.
The official implementation of the paper "ATTN-FIQA: Interpretable Attention-based Face Image Quality Assessment with Vision Transformers", accepted at FG2026.
Designed and evaluated a retrieval-augmented generation (RAG) pipeline on the FiQA financial QA dataset, benchmarking multiple retrieval strategies (sparse + dense) using MRR and Precision@K to optimize answer relevance and retrieval quality.
💎AlphaCrunch: LangGraph-powered Finance AI Agent Conversational analyst using QLoRA-fine-tuned Mistral-7B + RAG over S&P 500 10-Ks . Multi-turn memory, Gradio UI.
Hybrid Semantic Search and Neural Reranking for Financial Question Answering
The official implementation of the paper "EX-FIQA: Leveraging Intermediate Early eXit Representations from Vision Transformers for Face Image Quality Assessment", accepted at FG2026.
Fine-tuning bge-small for FiQA-2018 financial retrieval on an 8 GB laptop GPU: in-batch vs BM25 vs filtered dense hard negatives, with bootstrap CIs
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