Hamsterdam Research
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The AI Assistant Is Part of the Search Journey: What New Research, “Role of Personality in Conversational Information Seeking,” Means for SEO/GEO (Hamsterdam Research)
The AI Assistant Is Part of the Search Journey: What New Research, “Role of Personality in Conversational Information Seeking,” Means for SEO/GEO (Hamsterdam Research) By Ethan Lazuk Last updated: Welcome to another edition of Hamsterdam Research! 🐹 This is where we look at recent AI research papers to learn what they’re talking about and explore…
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The Prompt Isn’t Always the Query: What Conversation Context Means for SEO and GEO (Hamsterdam Research)
The Prompt Isn’t Always the Query: What Conversation Context Means for SEO and GEO (Hamsterdam Research) By Ethan Lazuk Last updated: Welcome to another edition of Hamsterdam Research! 🐹 This is where we look at recent AI research papers to learn what they’re talking about and explore their hypothetical implications for the future of search…
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Exploring “GuidedRAG: Semantic Steering of Retrieval-Augmented Generation” and Why SEO/GEO Professionals Should Care (Hamsterdam Research)
Exploring “GuidedRAG: Semantic Steering of Retrieval-Augmented Generation” and Why SEO/GEO Professionals Should Care (Hamsterdam Research) By Ethan Lazuk Last updated: Welcome to a new edition of Hamsterdam Research! 🐹 This is where we look at recent AI research papers to learn just what the heck they’re talking about and explore their hypothetical implications for the…
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Exploring “Scalable In-context Ranking with Generative Models,” a Google Research Paper, & Why SEO/GEO Professionals Should Care (A Hamsterdam Research Post)
Exploring “Scalable In-context Ranking with Generative Models,” a Google Research Paper, & Why SEO/GEO Professionals Should Care (A Hamsterdam Research Post) By Ethan Lazuk Last updated: Welcome to a new edition of Hamsterdam Research! 🐹 If you’re new here, this is where we look at recent AI research papers to learn just what the heck…
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Summarizing “Web vs. LLMs: An Empirical Study of Learning Behaviors of CS2 Students” from an SEO’s perspective (Hamsterdam Research)
In this Hamsterdam Research post, we’ll summarize “Web vs. LLMs: An Empirical Study of Learning Behaviors of CS2 Students” from an SEO’s perspective.
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What is Pairwise Ranking Prompting and why should SEOs care?
What is Pairwise Ranking Prompting and why should SEOs care? Welcome to a new Hamsterdam Research post. 🐹 We’ll be taking a look at a paper from Google Research titled, “Large Language Models are Effective Text Rankers with Pairwise Ranking Prompting.” The paper’s authors include Zhen Qin, Rolf Jagerman, Kai Hui, Honglei Zhuang, Junru Wu,…
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What are zero-shot pointwise LLM rankers and why should SEOs care?
What are zero-shot pointwise LLM rankers and intermediate relevance labels, and why should SEOs care? Welcome to a new Hamsterdam Research post. 🐹 This time, we’ll take a look at a paper from Google Research titled, “Beyond Yes and No: Improving Zero-Shot Pointwise LLM Rankers via Scoring Fine-Grained Relevance Labels.” The paper’s authors include Honglei…
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Learning what query expansion to improve generalization of strong cross-encoder rankers means and why SEOs should care.
Learning what query expansion to improve generalization of strong cross-encoder rankers means and why SEOs should care. Welcome to a new Hamsterdam Research post. This week, we’ll take a look at a paper from Google Research titled, “Can Query Expansion Improve Generalization of Strong Cross-Encoder Rankers?“ The paper’s authors include Minghan Li, Honglei Zhuang, Kai…
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Exploring language model embeddings for Bayesian optimization & why marketers should care.
Exploring language model embeddings for Bayesian optimization & why marketers should care. Welcome to a new week of 🐹 Hamsterdam Research, where we’re looking at a Google DeepMind paper, Predicting from Strings: Language Model Embeddings for Bayesian Optimization. The paper was submitted to ArXiv on October 14th, 2024, and includes several authors, including Tung Nguyen,…
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What we as marketers can learn about originality and diversity from Diversity-Rewarded CFG Distillation via Google DeepMind.
What we as marketers can learn about originality and diversity from Diversity-Rewarded CFG Distillation via Google DeepMind. Welcome back to 🐹 Hamsterdam Research, where we’re looking at a subtopic from a Google DeepMind paper, Diversity-Rewarded CFG Distillation. Our focus will be on what originality and diversity mean in the context of the paper, and why…
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Introducing inference scaling for long-context RAG, and why marketers should care.
Introducing inference scaling for long-context RAG via Google DeepMind, and why marketers should care. Welcome back to 🐹 Hamsterdam Research, where we’re delving into a new topic from Google DeepMind: Inference Scaling for Long-Context RetrievalAugmented Generation. The paper was submitted to ArXiv on October 6th, 2024, and includes several authors, including Zhenrui Yue, Honglei Zhuang,…
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Introducing Differential Transformer, and why marketers should care.
Introducing Differential Transformer, and why marketers should care. 🐹 Hamsterdam Research is back with a new and exciting topic: Differential Transformer. You may be familiar with Transformers, the basis for ML models like GPT and BERT. A Differential Transformer (Diff Transformer) is an improved version designed to handle attention better by focusing on relevant information…
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Stumbling Upon Google Engineer Ni Lao’s Work, & Exploring What It Can Teach Us about ML, IR & NLP for SEO Insights (a Hamsterdam Research Post)
In this Hamsterdam Research post, we look at the work of Ni Lao, a Google engineer, for learnings about machine learning, information retrieval, and NLP.