Balanced Co-Clustering of Users and Items for Embedding Table Compression in Recommender Systems
sigir26-204 · Full research paper · Rongfeng Jiang, Renchi Yang, Di Wu
Embedding Compression and Quantizati · 100%
Abstract
Recommender systems have advanced markedly over the past decade by transforming each user/item into a dense embedding vector with deep learning models. At industrial scale, embedding tables constituted by such vectors of all users/items demand a vast amount of parameters and impose heavy compute and memory overhead during training and inference, hindering model deployment under resource constraints. Existing solutions towards embedding compression either suffer from severely compromised recommendation accuracy or incur considerable computational costs.
Assigned reviewers
| # | Reviewer | Match | Why (closest evidence publications in the taxonomy) | |
|---|---|---|---|---|
| 1 | Hung Vinh Tran | 47 | 66 A Thorough Performance Benchmarking on Lightweight Embedding-based Recommender Systems (2025) Recommendation Systems and Evaluation 63 On-device Content-based Recommendation with Single-shot Embedding Pruning: A Cooperative Game Perspective (2025) Content-Based Transferable Recommendation 35 Efficient Content-based Recommendation Model Training via Noise-aware Coreset Selection (2026) Content-Based Transferable Recommendation |
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| 2 | Xurong Liang | 40 | 71 Learning Compact Compositional Embeddings via Regularized Pruning for Recommendation (2023) Efficient and Lightweight Graph Collaborative Filtering 47 Lightweight Embeddings with Graph Rewiring for Collaborative Filtering (2025) Graph-based User and Item Representation Learning 47 Lightweight Embeddings for Graph Collaborative Filtering (2024) Graph-based User and Item Representation Learning |
Area chair
| Area chair | Match | |
|---|---|---|
| Yankai Chen 0001 | 33 |
Area-chair candidates (5)
| Yankai Chen 0001 assigned | 33 | 6 papers | |
| Maolin Wang 0001 | 33 | 15 papers | |
| Xiaoyi Zeng | 32 | 11 papers | |
| Kun Gai COI: co-author | 31 | 5 papers | |
| Ge Li 0001 | 30 | 4 papers |
Candidates from the panel ranked by match score
| # | Reviewer | Match | Load | Why | |
|---|---|---|---|---|---|
| 1 | Hung Vinh Tran assigned | 47 | 3 | 66 A Thorough Performance Benchmarking on Lightweight Embedding-based Recommender Systems (2025) Recommendation Systems and Evaluation 63 On-device Content-based Recommendation with Single-shot Embedding Pruning: A Cooperative Game Perspective (2025) Content-Based Transferable Recommendation |
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| 2 | Zheng Zhang 0006 COI: co-author | 40 | 3 | 40 Flexible Discrete Multi-view Hashing with Collective Latent Feature Learning (2020) Cross-Modal Hashing and Quantization 40 From Sparse to Dense: Semantic Graph Evolutionary Hashing for Unsupervised Cross-Modal Retrieval (2022) Cross-Modal Hashing and Quantization |
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| 3 | Xurong Liang assigned | 40 | 3 | 71 Learning Compact Compositional Embeddings via Regularized Pruning for Recommendation (2023) Efficient and Lightweight Graph Collaborative Filtering 47 Lightweight Embeddings with Graph Rewiring for Collaborative Filtering (2025) Graph-based User and Item Representation Learning |
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| 4 | Hao Deng 0011 | 38 | 3 | 64 CSMF: Cascaded Selective Mask Fine-Tuning for Multi-Objective Embedding-Based Retrieval (2025) Multi-Task and Multi-Objective Optimization 38 ESANS: Effective and Semantic-Aware Negative Sampling for Large-Scale Retrieval Systems (2025) Multimodal Denoising and Robustness |
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| 5 | Fengling Li 0001 | 37 | 3 | 50 EffiPOI: A Product Quantization Framework Based on Knowledge Distillation for Efficient POI Recommendations (2026) Efficient and Long-Sequence Sequential Recommendation 40 Unified stable and generalizable online hashing for cross-modal retrieval (2026) Cross-Modal Hashing and Quantization |
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| 6 | Antonio Mallia | 37 | 3 | 42 Learning Passage Impacts for Inverted Indexes (2021) Learned Sparse Retrieval Efficiency 42 Improved Learned Sparse Retrieval with Corpus-Specific Vocabularies (2024) Learned Sparse Retrieval Efficiency |
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| 7 | Franco Maria Nardini | 37 | 3 | 41 ReNeuIR: Reaching Efficiency in Neural Information Retrieval (2022) Learned Sparse Retrieval Efficiency 41 ReNeuIR at SIGIR 2023: The Second Workshop on Reaching Efficiency in Neural Information Retrieval (2023) Learned Sparse Retrieval Efficiency |
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| 8 | Meiyu Liang | 35 | 3 | 40 Deep Unsupervised Momentum Contrastive Hashing for Cross-modal Retrieval (2023) Cross-Modal Hashing and Quantization 40 A Multi-View Double Alignment Hashing Network with Weighted Contrastive Learning (2024) Cross-Modal Hashing and Quantization |
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| 9 | Sebastian Bruch 0001 | 35 | 3 | 41 Efficient Inverted Indexes for Approximate Retrieval over Learned Sparse Representations (2024) Learned Sparse Retrieval Efficiency 41 ReNeuIR: Reaching Efficiency in Neural Information Retrieval (2022) Learned Sparse Retrieval Efficiency |
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| 10 | Huiqiang Jiang | 34 | 3 | 41 RetroInfer: A Vector Storage Engine for Scalable Long-Context LLM Inference (2026) Learned Sparse Retrieval Efficiency 41 LeanK: Learnable K Cache Channel Pruning for Efficient Decoding (2025) Learned Sparse Retrieval Efficiency |
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| 11 | Xueguang Ma | 34 | 3 | 42 LACONIC: Dense-Level Effectiveness for Scalable Sparse Retrieval via a Two-Phase Training Curriculum (2026) Learned Sparse Retrieval Efficiency 39 SLIM: Sparsified Late Interaction for Multi-Vector Retrieval with Inverted Indexes (2023) Learned Sparse Retrieval Efficiency |
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| 12 | Jin Chen 0008 | 34 | 3 | 55 Automated Sparse and Low-Rank Shallow Autoencoders for Recommendation (2025) Efficient and Lightweight Graph Collaborative Filtering 55 AutoS2AE: Automate to Regularize Sparse Shallow Autoencoders for Recommendation (2023) Efficient and Lightweight Graph Collaborative Filtering |
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| 13 | Gyuseok Lee | 34 | 3 | 43 Continual Collaborative Distillation for Recommender System (2024) Efficient and Lightweight Graph Collaborative Filtering 31 Capturing User Interests from Data Streams for Continual Sequential Recommendation (2026) Efficient Sequential Recommendation Architectures |
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| 14 | Jingtao Zhan | 34 | 3 | 40 Scaling Laws For Dense Retrieval (2024) Sparse and Dense Retrieval Encoders 39 Joint Optimization of Multi-vector Representation with Product Quantization (2022) Learned Sparse Retrieval Efficiency |
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| 15 | Xiao Wang 0043 | 34 | 3 | 38 Reproducibility, Replicability, and Insights into Dense Multi-Representation Retrieval Models: from ColBERT to Col (2023) Learned Sparse Retrieval Efficiency 38 An Inspection of the Reproducibility and Replicability of TCT-ColBERT (2022) Learned Sparse Retrieval Efficiency |
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| 16 | Jieming Zhu | 33 | 3 | 50 TayFCS: Towards Light Feature Combination Selection for Deep Recommender Systems (2025) CTR and Conversion Rate Prediction 37 Cross-Batch Negative Sampling for Training Two-Tower Recommenders (2021) Negative Sampling and Loss Functions |
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| 18 | Peitian Zhang | 33 | 3 | 40 C-Pack: Packed Resources For General Chinese Embeddings (2024) Text Embedding and Representation Learning 39 Hybrid Inverted Index Is a Robust Accelerator for Dense Retrieval (2023) Efficient Retrieval and Indexing |
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| 20 | Ruqing Zhang 0001 | 33 | 3 | 40 A Contrastive Pre-training Approach to Discriminative Autoencoder for Dense Retrieval (2022) Dense Bi-Encoder Training and Representation Learning 40 Pre-train a Discriminative Text Encoder for Dense Retrieval via Contrastive Span Prediction (2022) Dense Bi-Encoder Training and Representation Learning |
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| 21 | Qijiong Liu | 33 | 3 | 44 Condensing Pre-Augmented Recommendation Data via Lightweight Policy Gradient Estimation (Extended Abstract) (2025) Efficient Training and Data Optimization 44 Condensing Pre-Augmented Recommendation Data via Lightweight Policy Gradient Estimation (2025) Efficient Training and Data Optimization |
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| 23 | Sheng-Chieh Lin | 32 | 3 | 40 Efficiently Teaching an Effective Dense Retriever with Balanced Topic Aware Sampling (2021) Approximate Nearest Neighbor Search 40 A Dense Representation Framework for Lexical and Semantic Matching (2023) Dense Bi-Encoder Training and Representation Learning |
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| 24 | Junwei Pan COI: co-author | 32 | 3 | 100 On the Embedding Collapse when Scaling up Recommendation Models (2024) Embedding Compression and Quantization 31 Incremental Learning for LLM-based Tokenization and Recommendation (2025) Item Tokenization and Semantic IDs |
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| 25 | Jie Jiang 0015 | 32 | 3 | 72 On the Embedding Collapse when Scaling up Recommendation Models (2024) Embedding Compression and Quantization 47 Long-Sequence Recommendation Models Need Decoupled Embeddings (2025) CTR and Conversion Rate Prediction |
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| 26 | Noveen Sachdeva | 32 | 3 | 69 ECLARE: Extreme Classification with Label Graph Correlations (2021) Graph Neural Network Architectures for CF 43 Infinite Recommendation Networks: A Data-Centric Approach (2022) Efficient and Lightweight Graph Collaborative Filtering |
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| 27 | Xinyu Ma 0001 | 32 | 3 | 40 Probe-and-Fetch: Dynamic KV Cache Pruning for Accelerated Long-Context Inference in Web-Scale AI Search (2026) Efficient and Long-Context RAG 40 A Contrastive Pre-training Approach to Discriminative Autoencoder for Dense Retrieval (2022) Sparse and Dense Retrieval Encoders |
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| 28 | Jinpeng Wang 0002 | 31 | 3 | 40 Webly Supervised Deep Attentive Quantization (2021) Cross-Modal Hashing and Quantization 40 Hugs Bring Double Benefits: Unsupervised Cross-Modal Hashing with Multi-granularity Aligned Transformers (2024) Cross-Modal Hashing and Quantization |
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| 30 | Yupeng Hou | 31 | 3 | 36 Towards Large Generative Recommendation: A Tokenization Perspective (2025) Item Tokenization and Semantic IDs 35 Adapting Large Language Models by Integrating Collaborative Semantics for Recommendation (2024) Collaborative-Semantic Representation Alignment |
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| 31 | Han Li 0005 | 31 | 3 | 71 Learning Tree-based Deep Model for Recommender Systems (2018) Efficient and Lightweight Graph Collaborative Filtering 36 Comprehensive List Generation for Multi-Generator Reranking (2025) Recommendation with Search and Ranking |
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| 32 | Amir Ingber | 31 | 3 | 41 SDR: Efficient Neural Re-ranking using Succinct Document Representation (2022) Learned Sparse Retrieval Efficiency 40 Bridging Dense and Sparse Maximum Inner Product Search (2024) Approximate Nearest Neighbor Search |
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| 33 | Lichan Hong | 30 | 3 | 44 Bridging the Gap: Unpacking the Hidden Challenges in Knowledge Distillation for Online Ranking Systems (2024) Efficient Training and Data Optimization 36 Better Generalization with Semantic IDs: A Case Study in Ranking for Recommendations (2024) Item Tokenization and Semantic IDs |
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| 34 | Jurek Leonhardt | 30 | 3 | 38 Efficient Neural Ranking Using Forward Indexes and Lightweight Encoders (2024) Learned Sparse Retrieval Efficiency 38 Efficient Neural Ranking using Forward Indexes (2022) Learned Sparse Retrieval Efficiency |