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[Paper Review] Personalized marketing: Leveraging AI for culturally aware segmentation and targeting
A short application paper that bolts LIME onto K-means over Kaggle's 200-row Mall Customer dataset. The biggest discussion point is the gap between the 'culturally aware' framing in the title and what the experiment actually does.
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[Paper Review] Persistent Visual Memory: Sustaining Perception for Deep Generation in LVLMs
An autoregressive LVLM's visual attention collapses as O(t⁻¹) under growing textual history. PVM adds a parallel retrieval branch alongside each FFN to restore visual perception during deep generation.
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[Paper Review] Unlocking the power of AI in CRM: A comprehensive multidimensional exploration
A qualitative study that distills 1,055 papers down to 64, plus 24 in-depth interviews with CRM practitioners, to organize AI-powered CRM capabilities into three dimensions and eight sub-dimensions through a microfoundations-of-dynamic-capabilities lens.
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[Paper Review] The relevance of lead prioritization: a B2B lead scoring model based on machine learning
A B2B software SME's four-year CRM dataset benchmarked across 15 classifiers via PyCaret — Gradient Boosting wins (98.39% accuracy, AUC 0.9891). Lead Source / Reason for State / Lead Classification dominate feature importance.
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[Paper Review] Artificial intelligence in customer relationship management: A systematic framework for a successful integration
An interview-based 4-macro-phase, 13-step framework for integrating AI into CRM — with ethics by design and customer data centralization wired in from day one.
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[Paper Review] TurboQuant: Online Vector Quantization with Near-optimal Distortion Rate
A training-free vector quantizer that gets within ~2.7× of the information-theoretic distortion-rate bound — using just one random rotation.
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[Paper Review] LLaDA2.0-Uni: Unifying Multimodal Understanding and Generation with Diffusion Large Language Model
A single diffusion LLM that handles image understanding, generation, editing, and interleaved reasoning. Built around a SigLIP-VQ semantic tokenizer, a 16B MoE backbone, and an 8-step distilled diffusion decoder.
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[Paper Review] TradingAgents: Multi-Agents LLM Financial Trading Framework
An LLM trading framework that mirrors a real trading firm's org chart — analysts, bullish/bearish researchers, a trader, a risk team, and a fund manager — coordinated through structured reports for cross-team handoff and natural-language debate inside teams.
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[Paper Review] How to Train Your Long-Context Visual Document Model
How to train a 344K-context visual document VLM — the first large-scale, open recipe spanning CPT, SFT, LongPO and self-improvement.
