Hierarchical Embedding Fusion for Retrieval-Augmented Code Generation
sigir26-047 · Full research paper · Nikita Sorokin, Ivan Sedykh, V. A. Malykh
Learned Sparse Retrieval Efficiency · 50% RAG for Domain Applications · 25% Efficient and Long-Context RAG · 25%
Abstract
Retrieval-augmented code generation commonly conditions a decoder on large retrieved snippets, which couples online cost to repository size and introduces long-context noise. We present Hierarchical Embedding Fusion (HEF), a two-stage repository representation for code completion: (i) an offline cache that compresses repository chunks into a reusable hierarchy of dense vectors using a small fuser model, and (ii) an online interface that maps a small number of retrieved vectors into learned pseudo-tokens consumed by a code generator. This replaces thousands of retrieved tokens with a fixed pseudo-token budget while retaining access to repository-level information.
Assigned reviewers
| # | Reviewer | Match | Why (closest evidence publications in the taxonomy) | |
|---|---|---|---|---|
| 1 | Shu Zhou 0002 | 57 | 82 Activation Caching for Retrieval-Augmented Generation (2026) Efficient and Long-Context RAG 49 The Retrieval Bottleneck: Scaling Laws for Reinforcement Learning in RAG (2026) Efficient and Long-Context RAG 47 Latent Retrieval Augmented Generation (2026) Efficient and Long-Context RAG |
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| 2 | Corby Rosset | 40 | 64 Optimizing Query Evaluations Using Reinforcement Learning for Web Search (2018) Efficient Retrieval and Indexing 63 Dodo: Dynamic Contextual Compression for Decoder-only LMs (2024) Learned Sparse Retrieval Efficiency 37 Augmenting Zero-Shot Dense Retrievers with Plug-in Mixture-of-Memories (2023) Retrieval-Augmented Generation › Others |
Area chair
| Area chair | Match | |
|---|---|---|
| Hongjin Qian | 51 |
Area-chair candidates (6)
| Hongjin Qian assigned | 51 | 12 papers | |
| Xiaoxi Li 0005 | 37 | 15 papers | |
| Xiaoxue Zang | 36 | 4 papers | |
| Pengyue Jia | 36 | 10 papers | |
| Jun Xu 0001 | 36 | 2 papers | |
| Chenyan Xiong | 35 | 15 papers |
Candidates from the panel ranked by match score
| # | Reviewer | Match | Load | Why | |
|---|---|---|---|---|---|
| 1 | Franco Maria Nardini | 65 | 3 | 66 Efficient Re-ranking with Cross-encoders via Early Exit (2025) Learned Sparse Retrieval Efficiency 66 Quality versus efficiency in document scoring with learning-to-rank models (2016) Learned Sparse Retrieval Efficiency |
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| 2 | Huiqiang Jiang | 64 | 3 | 66 LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Models (2023) Learned Sparse Retrieval Efficiency 66 RetrievalAttention: Accelerating Long-Context LLM Inference via Vector Retrieval (2025) Learned Sparse Retrieval Efficiency |
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| 3 | Antonio Mallia | 63 | 3 | 66 Improved Learned Sparse Retrieval with Corpus-Specific Vocabularies (2024) Learned Sparse Retrieval Efficiency 66 Learning Passage Impacts for Inverted Indexes (2021) Learned Sparse Retrieval Efficiency |
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| 4 | Shu Zhou 0002 assigned | 57 | 3 | 82 Activation Caching for Retrieval-Augmented Generation (2026) Efficient and Long-Context RAG 49 The Retrieval Bottleneck: Scaling Laws for Reinforcement Learning in RAG (2026) Efficient and Long-Context RAG |
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| 5 | Sebastian Bruch 0001 | 56 | 3 | 66 Efficient Inverted Indexes for Approximate Retrieval over Learned Sparse Representations (2024) Learned Sparse Retrieval Efficiency 66 ReNeuIR at SIGIR 2023: The Second Workshop on Reaching Efficiency in Neural Information Retrieval (2023) Learned Sparse Retrieval Efficiency |
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| 6 | Peitian Zhang | 55 | 3 | 55 Hybrid Inverted Index Is a Robust Accelerator for Dense Retrieval (2023) Efficient Retrieval and Indexing 53 Tackling the Length Barrier: Dynamic Context Browsing for Knowledge-Intensive Task (2025) Efficient and Long-Context RAG |
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| 7 | Xueguang Ma | 51 | 3 | 66 LACONIC: Dense-Level Effectiveness for Scalable Sparse Retrieval via a Two-Phase Training Curriculum (2026) Learned Sparse Retrieval Efficiency 66 Gosling Grows Up: Retrieval with Learned Dense and Sparse Representations Using Anserini (2025) Learned Sparse Retrieval Efficiency |
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| 9 | Xinyu Ma 0001 | 46 | 3 | 82 Probe-and-Fetch: Dynamic KV Cache Pruning for Accelerated Long-Context Inference in Web-Scale AI Search (2026) Efficient and Long-Context RAG 45 Replication and Exploration of Generative Retrieval over Dynamic Corpora (2025) Generative Retrieval |
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| 10 | Sheng-Chieh Lin | 46 | 3 | 67 One Blade for One Purpose: Advancing Math Information Retrieval using Hybrid Search (2023) Learned Sparse Retrieval Efficiency 66 Pyserini: A Python Toolkit for Reproducible Information Retrieval Research with Sparse and Dense Representations (2021) Learned Sparse Retrieval Efficiency |
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| 11 | Jingtao Zhan | 46 | 3 | 65 Joint Optimization of Multi-vector Representation with Product Quantization (2022) Learned Sparse Retrieval Efficiency 51 Dynamic and Parametric Retrieval-Augmented Generation (2025) Multi-Hop and Iterative Retrieval Reasoning |
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| 12 | Xiao Wang 0043 | 45 | 3 | 66 Reproducibility, Replicability, and Insights into Dense Multi-Representation Retrieval Models: from ColBERT to Col (2023) Learned Sparse Retrieval Efficiency 65 An Inspection of the Reproducibility and Replicability of TCT-ColBERT (2022) Learned Sparse Retrieval Efficiency |
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| 13 | Jurek Leonhardt | 45 | 3 | 66 Efficient Neural Ranking Using Forward Indexes and Lightweight Encoders (2024) Learned Sparse Retrieval Efficiency 66 Efficient Neural Ranking using Forward Indexes (2022) Learned Sparse Retrieval Efficiency |
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| 14 | Yuchen Li 0006 | 42 | 3 | 82 Probe-and-Fetch: Dynamic KV Cache Pruning for Accelerated Long-Context Inference in Web-Scale AI Search (2026) Efficient and Long-Context RAG 37 When Search Engine Services Meet Large Language Models: Visions and Challenges (2024) Retrieval-Augmented Generation › Others |
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| 15 | Jing Liu 0022 | 41 | 3 | 47 BEE-RAG: Balanced Entropy Engineering for Retrieval-Augmented Generation (2026) Efficient and Long-Context RAG 39 Dense Text Retrieval Based on Pretrained Language Models: A Survey (2024) Dense Bi-Encoder Training and Representation Learning |
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| 16 | Daiting Shi | 41 | 3 | 66 Pre-trained Language Model-based Retrieval and Ranking for Web Search (2023) Learned Sparse Retrieval Efficiency 65 Pre-trained Language Model based Ranking in Baidu Search (2021) Learned Sparse Retrieval Efficiency |
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| 17 | Di Wu 0054 | 41 | 3 | 66 Repoformer: Selective Retrieval for Repository-Level Code Completion (2024) Efficient and Long-Context RAG 39 LongMemEval: Benchmarking Chat Assistants on Long-Term Interactive Memory (2025) Conversational Search and Retrieval |
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| 18 | Shengyao Zhuang | 41 | 3 | 66 Layer-wise Token Compression for Efficient Document Reranking (2026) Learned Sparse Retrieval Efficiency 66 LACONIC: Dense-Level Effectiveness for Scalable Sparse Retrieval via a Two-Phase Training Curriculum (2026) Learned Sparse Retrieval Efficiency |
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| 19 | Corby Rosset assigned | 40 | 3 | 64 Optimizing Query Evaluations Using Reinforcement Learning for Web Search (2018) Efficient Retrieval and Indexing 63 Dodo: Dynamic Contextual Compression for Decoder-only LMs (2024) Learned Sparse Retrieval Efficiency |
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| 20 | Jialong Wu 0007 | 40 | 3 | 66 SCOPE: Optimizing Key-Value Cache Compression in Long-context Generation (2025) Learned Sparse Retrieval Efficiency 37 PROPER: A Progressive Learning Framework for Personalized Large Language Models with Group-Level Adaptation (2025) Efficiency and Deployment |
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| 21 | Jinheon Baek | 38 | 3 | 87 Efficient Long Context Language Model Retrieval with Compression (2025) Learned Sparse Retrieval Efficiency 45 Knowledge-Augmented Reasoning Distillation for Small Language Models in Knowledge-Intensive Tasks (2023) Retrieval-Augmented and Open-Domain QA |
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| 22 | Ruqing Zhang 0001 | 38 | 3 | 49 CorpusBrain++: A Continual Generative Pre-Training Framework for Knowledge-Intensive Language Tasks (2026) Generative Retrieval 42 PROP: Pre-training with Representative Words Prediction for Ad-hoc Retrieval (2021) Sparse and Dense Retrieval Encoders |
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| 23 | Yujia Zhou 0002 | 38 | 3 | 47 Parametric Retrieval Augmented Generation (2025) Efficient and Long-Context RAG 35 Enhancing Generative Retrieval with Reinforcement Learning from Relevance Feedback (2023) Recommendation with Search and Ranking |
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| 24 | Venktesh V | 37 | 3 | 66 Breaking the Lens of the Telescope: Online Relevance Estimation over Large Retrieval Sets (2025) Learned Sparse Retrieval Efficiency 37 The Surprising Effectiveness of Rankers trained on Expanded Queries (2024) Evidence Selection and Context Refinement |
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| 26 | Yupeng Hou | 37 | 3 | 52 CoRAL: Collaborative Retrieval-Augmented Large Language Models Improve Long-tail Recommendation (2024) RAG for Domain Applications 38 Large Language Models are Zero-Shot Rankers for Recommender Systems (2024) Efficiency and Deployment |
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| 27 | Negar Arabzadeh | 37 | 3 | 53 Predicting Efficiency/Effectiveness Trade-offs for Dense vs. Sparse Retrieval Strategy Selection (2021) Efficient Retrieval and Indexing 39 Learning Query-Space Document Representations for High-Recall Retrieval (2023) Dense Bi-Encoder Training and Representation Learning |
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| 28 | Amir Ingber | 37 | 3 | 66 SDR: Efficient Neural Re-ranking using Succinct Document Representation (2022) Learned Sparse Retrieval Efficiency 65 Bridging Dense and Sparse Maximum Inner Product Search (2024) Approximate Nearest Neighbor Search |
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| 29 | Keping Bi | 36 | 3 | 44 A Multi-Granularity-Aware Aspect Learning Model for Multi-Aspect Dense Retrieval (2024) Sparse and Dense Retrieval Encoders 44 Pre-training with Aspect-Content Text Mutual Prediction for Multi-Aspect Dense Retrieval (2023) Sparse and Dense Retrieval Encoders |
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| 31 | Mariano Barone | 36 | 3 | 43 Combating Biomedical Misinformation through Multi-modal Claim Detection and Evidence-based Verification (2025) RAG for Domain Applications 41 Combining Evidence and Reasoning for Biomedical Fact-Checking (2025) Automated Fact Checking and Claim Verification |
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| 33 | Han Li 0005 | 36 | 3 | 39 Retrieval Augmented Generation with Collaborative Filtering for Personalized Text Generation (2025) Personalized and Conversational RAG 37 LEARN: Knowledge Adaptation from Large Language Model to Recommendation for Practical Industrial Application (2025) Efficiency and Deployment |
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| 35 | Yingyi Zhang 0001 | 36 | 3 | 66 Compress-then-Rank: Faster and Better Listwise Reranking with Large Language Models via Ranking-Aware Passage Compression (2026) Learned Sparse Retrieval Efficiency 38 Personalize Before Retrieve: LLM-based Personalized Query Expansion for User-Centric Retrieval (2026) Personalized and Conversational RAG |