Recommendation Systems: Papers to Read

A living reading list on recommender systems — classic papers, industry blog posts, surveys, and datasets. I'll keep adding to this over time rather than starting a new post for every batch.

Part 11 - Multi-modal & Visual Recommendation

• VBPR: Visual Bayesian Personalized Ranking from Implicit Feedback - He & McAuley (2016) · visual features from CNN in MF · paper
• ACF: Attentive Collaborative Filtering with Item and Component-level Attention - Chen et al. (2017) · paper
• BM3: Bootstrapped Multi-modal Self-supervised Learning for Recommendation (2022) · modal dropout + contrastive learning · paper
• MMGCN: Multi-modal Graph Convolution Network for Personalized Recommendation (2021) · paper
• Artwork Personalization at Netflix - Netflix Tech Blog (2017) · personalized thumbnail selection via contextual bandits · blog

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Part 12 - LLMs & Generative Recommendation

• P5: Pretrain, Personalize, Prompt - Towards a Unified Paradigm for RecSys - Geng et al. (2022) · text-to-text unified LLM for all RecSys tasks · paper
• TIGER: Generative Retrieval via Semantic IDs - Rajput et al., Google (2023) · autoregressive generation of hierarchical item IDs · paper
• How to Index Item IDs for Recommendation Foundation Models (2023) · ID vs text indexing comparison · paper
• TALLRec: Align LLM with Recommendation via Instruction Tuning (2023) · LoRA two-stage tuning for LLM rec · paper
• InstructRec: Recommendation as Instruction Following (2023) · instruction-tuning for personalized rec · paper
• LLaRA: Large Language-Recommendation Assistant (2023) · hybrid prompts with collaborative + text features · paper
• RLMRec: Representation Learning with LLMs for Recommendation (2023) · LLM-generated semantic profiles augment CF · paper
• Is ChatGPT a Good Recommender? A Preliminary Study (2023) · zero-shot LLM rec evaluation · paper
• BIGRec: Grounding Language Models for Recommendation (2023) · grounding LLM outputs to real catalog items · paper
• Actions Speak Louder than Words (HSTU) - Zhai et al., Meta (2024) · generative rec at trillion-scale · paper
• A Survey on Large Language Models for Recommendation - Wu et al. (2023) · covers prompting, tuning, and agent-based rec · survey
• RecSys in the Era of Large Language Models: A Survey (2023) · survey

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Part 13 - Exploration, Bandits & Reinforcement Learning

• Contextual Bandits for Personalized News Article Recommendation (LinUCB) - Li et al., Yahoo! (2010) · paper
• Deep Bayesian Bandits Showdown - Riquelme et al. (2018) · benchmark of neural contextual bandits · paper
• Top-K Off-Policy Correction for a REINFORCE Recommender System - Chen et al., Google (2019) · policy gradient with off-policy correction at YouTube · paper
• Reinforcement Learning for Slate-based Recommender Systems (SlateQ) - Ie et al., Google (2019) · Q-learning for ordered list recommendations · paper
• RecSim: A Configurable Simulation Platform for Recommender Systems - Google (2019) · paper
• Unbiased Offline Evaluation of Contextual-Bandit-Based News Recommendation - Li et al. (2010) · replay method for offline bandit eval · paper

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Part 14 - Causal Inference & Debiasing

• Recommendations as Treatments: Debiasing Learning and Evaluation - Schnabel et al. (2016) · IPS for unbiased recommendation training · paper
• Unbiased Learning to Rank with Unbiased Propensity Estimation - Joachims et al. (2018) · position bias correction via dual learning · paper
• CausE: Towards Causal Recommendations - Bonner & Vasile (2018) · counterfactual thinking for RecSys · paper
• Deconfounded Recommendation for Alleviating Bias Amplification (2021) · causal graph + PD learning for popularity debiasing · paper
• Disentangling User Interest and Conformity for Recommendation (2021) · DICE: causal embedding separating interest from conformity · paper
• Popularity Bias in Recommender Systems - Abdollahpouri et al. (2021) · taxonomy of popularity bias types and effects · paper
• A Survey on the Fairness of Recommender Systems (2022) · bias types, debiasing methods, fairness metrics · survey

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Part 15 - Evaluation Methodology

• Evaluating Collaborative Filtering Recommender Systems - Herlocker et al. (2004) · canonical evaluation methodology paper · paper
• Are We Really Making Much Progress? A Worrying Analysis of Recent Neural Recommendation Approaches - Dacrema et al. (2019) · reproducibility crisis: simple baselines match complex models · paper
• Normalized Discounted Cumulative Gain (NDCG) for Ranking Evaluation - Järvelin & Kekäläinen (2002) · paper
• Beyond Accuracy: Evaluating Recommender Systems by Coverage and Serendipity - Ge et al. (2010) · diversity + serendipity metrics · paper
• A Closer Look at the Evaluation of Recommender Systems (2020) · sampled-based NDCG is heavily biased · paper
• Leave-One-Out vs. Temporal Split Evaluation for Sequential RecSys (2020) · critiques common evaluation flaws in sequential rec · paper
• Offline Evaluation of Recommender Systems: A Practitioner's View (2022) · paper
• Netflix Tech Blog: A/B Testing Intuition Busters - Netflix · blog
• RecBole: A Unified, Comprehensive and Efficient Recommendation Library (2020) · paper
• Reclist: Beyond-accuracy Evaluation of RecSys - Chia et al. (2022) · behavioral testing framework for rec models · paper

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Part 16 - Datasets

• MovieLens: Stable Benchmark Dataset - Harper & Konstan (2015) · 1M / 10M / 25M versions; starting point for most papers · dataset
• Amazon Product Reviews (2018) - Ni et al. (2019) · 233M reviews across 29 categories; widely used for sequential rec · dataset
• Yelp Open Dataset - local business reviews + metadata · dataset
• MIND: Microsoft News Dataset - Wu et al. (2020) · 1M users, 160K news articles, click labels · dataset
• KuaiRec: A Fully-Observed Dataset for Recommender Systems - Gao et al. (2022) · near-complete observation matrix; nearly unbiased evaluation · dataset
• KuaiRand: An Unbiased Sequential Recommendation Dataset (2022) · random exploration policy logging for unbiased eval · dataset
• Taobao User Behavior Dataset - Alibaba · 100M user behavior records · dataset
• MSD: Million Song Dataset - Bertin-Mahieux et al. (2011) · implicit listening history for music rec · dataset
• RecSys Challenge Datasets - ACM RecSys (annual) · dataset
• LastFM Dataset - HetRec 2011 · music listening history · dataset

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Part 17 - Surveys & Textbooks

• Recommender Systems Handbook (3rd ed.) - Ricci, Rokach & Shapira (2022) · comprehensive reference · book
• Practical Recommender Systems - Falk, Manning (2019) · practitioner-focused · book
• Deep Learning based Recommender System: A Survey and New Perspectives - Zhang et al. (2019) · survey
• Graph Neural Networks in Recommender Systems: A Survey - Wu et al. (2020) · survey
• Self-supervised Learning for Recommender Systems: A Survey - Yu et al. (2022) · survey
• A Survey on Knowledge Graph-Based Recommender Systems - Guo et al. (2020) · survey
• A Survey on Large Language Models for Recommendation - Wu et al. (2023) · survey
• Toward the Next Generation of Recommender Systems - Adomavicius & Tuzhilin (2005) · foundational taxonomy survey · survey
• Google ML Crash Course: Recommendation Systems · hands-on collaborative filtering, candidate generation, retrieval · website
• RecSys Podcast (recspod.com) · practitioner interviews on production rec · website

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Part 18 – 2024–2026 Frontier

Scaling Laws for RecSys (2024)

• Actions Speak Louder than Words: HSTU at Meta - Zhai et al., Meta (Feb 2024) · 1T-param sequential transducer; scales rec the way LLM scaling laws scale language · paper
• Wukong: Towards a Scaling Law for Large-Scale Recommendation - Yao et al., LinkedIn (Mar 2024) · rec models follow power laws but with different exponents than LLMs · paper
• Breaking the Length Barrier: LLMs Excel at Supervised Long-Context Recommendation (2024) · fine-tuned LLMs with very long behavior sequences beat all baselines · paper

LLM-Integrated RecSys (2024)

• Is ChatGPT a Good Recommender? A Preliminary Study (2023) · zero-shot GPT-4 still loses to fine-tuned ID models; set the 2024 research agenda · paper
• NoteLLM: A Retrievable Large Language Model for Note Recommendation - Xiaohongshu/REDNote, WWW (2024) · end-to-end LLM as retriever at production note-rec scale · paper
• HLLM: Enhancing Sequential Recommendations via Hierarchical Large Language Models (2024) · item-level LLM encodes content; user-level LLM models history · paper
• LLaRA: Aligning Large Language Models with Sequential Recommenders (2023/2024) · hybrid prompt connects LLM reasoning with ID-based sequence model · paper
• AgentCF: Collaborative Learning with Autonomous Language Agents for Recommender Systems (2024) · LLM agents simulate user-item interaction for training signal · paper
• E4SRec: Effective, Efficient, Extensible Sequential Rec with LLMs (2024) · practical LLM-for-SeqRec that's actually deployable in production · paper
• CTRL: Connect Tabular and Language Model for CTR Prediction - Yuan et al., Alibaba (2023) · bridges structured feature tables and LLM text for industrial CTR · paper

Generative Retrieval (2024)

• How to Index Item IDs for Recommendation Foundation Models (2024) · systematic study of semantic ID design for TIGER-style autoregressive rec · paper
• Generative Recommendation: Towards Next-generation Recommender Paradigm (2023/2024) · position paper framing the shift from retrieve-rank to generate · paper
• MoRec: Representation Learning with Item Text Encoders vs ID Embeddings (2022, re-evaluated 2024) · reopens the "text vs ID" debate: text encoders rival ID embeds at scale · paper

Diffusion Models for RecSys (2023–2024)

• DiffRec: Diffusion Recommender Model - Lin et al., RecSys (2023) · DDPM applied to collaborative filtering; strong on cold/sparse data · paper
• CF-Diff: Collaborative Filtering with Diffusion Models (2023) · multi-step denoising as personalization · paper

Multi-Modal RecSys (2024–2025)

• BM3: Bootstrap Latent Representations for Multi-modal Recommendation (2023/2024) · SSL multi-modal alignment without negative sampling · paper
• MMSSL: Multi-modal Self-supervised Learning for Recommendation (2023/2024) · cross-modal contrastive learning with graph structure · paper
• AlphaRec: Scalable Multimodal Recommendation with Vision-Language Models (2025) · CLIP embeddings as item representations for zero-shot rec · paper

Agentic & RAG-based RecSys (2024–2025)

• RecMind: Large Language Model Powered Agent For Recommendation (2024) · planning + memory + tool use in an LLM agent for rec · paper
• RAG for Personalized Recommendation (2024) · retrieval-augmented generation injected into rec ranking stage · paper
• AgentRec: Simulation-based Evaluation of Recommender Systems via LLM Agents (2024) · replaces offline user behavior datasets with LLM-simulated users · paper

Industry Blog Posts (2024–2026)

• Meta Generative Recommendations - HSTU Deep Dive - Meta AI (2024) · companion to the paper · blog
• How YouTube Thinks About Recommendations - YouTube (2021, updated 2024) · goals, metrics, and societal responsibility framing · blog
• Twitter's Open-Source Recommendation Algorithm - X/Twitter (2023) · full production stack: GraphJet, SimClusters, TwHIN, Heavy Ranker · blog
• Spotify's Podcast Recommendation System - Spotify Engineering (2022/2024) · two-tower + session context at audio scale · blog
• Netflix: How We Built Personalized Homepage - Netflix (2012, still relevant architecture primer) · blog
• Eugene Yan's RecSys Writing (2024) - collected practitioner deep-dives; updated regularly through 2025 · blog