New Research Insights: Advancing Reliable & Explainable AI Agents in 2025 5 influential studies reshaping #AIAgents & #ExplainableAI. 🔗 Read the complete analysis: na2.hubs.ly/y0JsL_0 #AI #AIResearch #AIAgents
@arya_ai1
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Interpretability-Aware Pruning for Efficient Medical Image Analysis
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🚨 New Research Published! Interpretability-Aware Pruning for Efficient Medical Image Analysis is now live on arXiv. 🔬 Compress deep models using attribution methods without losing accuracy or trust. 📄 Read here: arxiv.org/abs/2507.08330 🎧 Podcast: aryaxai.com/research-papers/…
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XAI Evals: Comparing AI Explainability Methods Framework
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Missed our webinar on Evaluating AI Explainability? We compare SHAP, LIME, GradCAM, Integrated Gradients & DL-Backtrace across real ML & DL models using XAI Evals — our open-source evaluation framework. ▶️ Watch now: piped.video/watch?v=E8l1Ucpc… 🔗 GitHub: github.com/AryaXAI/xai_evals
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Live Deep Dive into SHAP, LIME, Grad-CAM and xai_evals
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🚨 We’re LIVE! Join us for a deep dive into SHAP, LIME, Grad-CAM & DL-Backtrace. Introducing xai_evals — the open-source benchmark for explainability methods. 🔴 Tune in here: hubs.la/Q03wsDFp0 #XAI #AIExplainability
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XAI Methods Evaluation Session and xai_evals Framework Launch
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🔴 Just 2 Hours to Go! Join our closed-door session on evaluating XAI methods like SHAP, LIME, Grad-CAM & AryaXAI’s DL-Backtrace. Introducing xai_evals — an open-source framework to quantify & benchmark explainability tools. 🔗hubs.la/Q03wqGTZ0 #AIExplainability #XAI
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Join xai_evals Session: Evaluate Your Model Explanations Tomorrow
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🔔 1 Day to Go! Can you trust your model explanations? Join us for a closed-door session on xai_evals, AryaXAI’s open-source framework to evaluate SHAP, LIME, Grad-CAM & more using quantifiable metrics. 📅 July 9th 🔗 hubs.ly/Q03w9Lw10 #XAI #ML #AI #ResponsibleAI
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Live Webinar on XAI Methods Evaluation with xai_evals July 9
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Just a Few Days to go for our live webinar: "Beyond Explainability: Evaluating XAI Methods with Confidence using xai_evals" 📅 Wednesday, July 9th 🕑11:00 AM EDT | 4:00 PM BST | 8:30 pm IST 🔗hubs.la/Q03vMvnV0 #XAI #ExplainableAI #ResponsibleAI
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Evaluating Post-hoc Explanations: Benchmarking XAI Methods for Governance
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Learn: ✅ Why post-hoc explanations often fall short without evaluation ✅ How to benchmark SHAP, LIME, DLBacktrace, & more across data modalities ✅ Integrating xai_evals into governance, audit & compliance workflows 💬 Stay for a live Q&A with Pratinav
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xai_evals Webinar: Evaluating AI Explanations Framework July 3rd
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Join our webinar on xai_evals — a framework to evaluate AI explanations using metrics like faithfulness & monotonicity. 📅 Thursday, 3rd July 🕒 4:00 PM BST 🔗 Register here: hubs.la/Q03sC89s0 📄 : hubs.la/Q03sC6tv0 #XAI #ExplainableAI #MachineLearning #AIWebinar
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xai_evals Framework: Evaluating XAI Methods with Actionable Metrics
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Join us to explore xai_evals — a framework to evaluate SHAP, LIME, Grad-CAM & more with actionable #XAI metrics. 📅 Thursday, 3rd July 🔗 hubs.la/Q03s8-0m0 📄 Paper: hubs.la/Q03s93Yh0 🎙️ Pratinav Seth, Research Scientist at AryaXAI #AIExplainability #RAI #MLAudit