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AI framework digitizes athlete profiling with VLM and RAG

By PulseAugur Editorial · [2 sources] ·

Researchers have developed a novel LLM-based framework for holistic athlete profiling, designed to overcome the limitations of traditional manual or basic computer vision assessment methods. This agentic system, orchestrated by LangGraph, integrates computer vision for kinematic tracking with Vision-Language Models for semantic reasoning, specifically aligning with the Sports Authority of India's protocols. To manage computational demands and prevent hallucinations, the framework employs a temporal chunking strategy, an LLM-as-a-Judge self-correction loop, and a dual-persistence RAG pipeline using ChromaDB for natural language querying. AI

IMPACT This framework could significantly improve the objectivity and scalability of athlete talent identification and performance analysis.

RANK_REASON The cluster contains a research paper detailing a novel AI framework.

Read on arXiv cs.MA (Multiagent) →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

AI framework digitizes athlete profiling with VLM and RAG

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The cluster contains a research paper detailing a novel AI framework.
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COVERAGE [2]

  1. arXiv cs.AI TIER_1 English(EN) · Deep Ghosal, Ishani Sen, Wazib Ansar, Amlan Chakrabarti ·

    Digitizing Coaching Intelligence: An Agentic Framework for Holistic Athlete Profiling using VLM and RAG

    arXiv:2606.28570v1 Announce Type: cross Abstract: Athlete assessment is a critical process for tracking physical progress and identifying elite talent. However, during mass recruitment drives, traditional methods rely on manual observation, which is inherently subjective and unsc…

  2. arXiv cs.MA (Multiagent) TIER_1 English(EN) · Amlan Chakrabarti ·

    Digitizing Coaching Intelligence: An Agentic Framework for Holistic Athlete Profiling using VLM and RAG

    Athlete assessment is a critical process for tracking physical progress and identifying elite talent. However, during mass recruitment drives, traditional methods rely on manual observation, which is inherently subjective and unscalable, or basic computer vision (CV) systems limi…

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