Knowledge Augmentation for Language Models

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Overview

The field studies how language models can acquire and use information beyond what is already stored in their parameters, especially for changing facts, specialized domains, and multi-step tasks. Common approaches retrieve text or knowledge-graph evidence at inference time, maintain external memories, or inject knowledge through continued pretraining, supervised tuning, adapters, and synthetic data; agents may also decide when to search or use tools. Work increasingly tests not just whether evidence is available but whether models select and integrate it, using knowledge-intensive question answering, long-context, coding, medical, legal, and reasoning benchmarks. A central tension is choosing between retrieval and internalization: added context can be noisy or ignored, while weight updates can be costly and erode general abilities, so the best method depends on model scale, evidence quality, update needs, and compute.

Latest papers

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180 papers18 papers in the last four weeks, up 80% on the four weeks before. 0.1% of all new papers.

  1. Commonsense Knowledge with Negation: A Resource to Enhance Negation Understanding

    Apr 21, 2026Zijie Wang, MohammadHossein Rezaei, Farzana Rashid +1Knowledge Augmentation for Language ModelsLLM Training

    University of Arizona · University of North Carolina Asheville

  2. Enhancing Mental Health Counseling Support in Bangladesh using Culturally-Grounded Knowledge

    Apr 16, 2026Md Arid Hasan, Azhagu Meena SP, Aditya Khan +6Retrieval-Augmented GenerationMental Health Counseling

    University of Toronto, Canada · mPower Social Enterprises Ltd, Bangladesh · National Institute of Mental Health, Bangladesh +2

  3. MoshiRAG: Asynchronous Knowledge Retrieval for Full-Duplex Speech Language Models

    Apr 14, 2026Chung-Ming Chien, Manu Orsini, Eugene Kharitonov +3Speech Language ModelsFull-Duplex Spoken Dialogue Systems

    Toyota Technological Institute at Chicago, Chicago, USA · Kyutai, Paris, France · Gradium, Paris, France

  4. KoCo: Conditioning Language Model Pre-training on Knowledge Coordinates

    Apr 14, 2026Yudong Li, Jiawei Cai, Linlin ShenLanguage Model PretrainingKnowledge Augmentation for Language Models

    School of Computer Science and Software Engineering, Shenzhen University · Department of Electrical Engineering, Tsinghua University · School of Artificial Intelligence, Shenzhen University +1

  5. Structure-Grounded Knowledge Retrieval via Code Dependencies for Multi-Step Data Reasoning

    Apr 12, 2026Xinyi HuangKnowledge Augmentation for Language ModelsRetrieval-Augmented Generation

    Simon Fraser University

  6. Enhancing LLM Medical Coding with Structured External Knowledge

    Apr 9, 2026Yidong Gan, David D. Nguyen, Yang Lin +4Automated Medical CodingMedical LLMs

    Oracle Health and AI · The University of Sydney · CSIRO Data61

  7. Filling the Gaps: Selective Knowledge Augmentation for LLM Recommenders

    Apr 9, 2026Jaehyun Lee, Sanghwan Jang, SeongKu Kang +1Recommender SystemsLarge Language Model-Based Recommendation

    Pohang University of Science and Technology, Pohang, Republic of Korea · Korea University, Seoul, Republic of Korea

  8. WRAP++: Web discoveRy Amplified Pretraining

    Apr 8, 2026Jiang Zhou, Yunhao Wang, Xing Wu +2Knowledge Augmentation for Language ModelsSynthetic Data Pretraining

  9. Scientific Knowledge-driven Decoding Constraints Improving the Reliability of LLMs

    Apr 8, 2026Maotian Ma, Zheni Zeng, Zhenghao Liu +1LLM Hallucination MitigationKnowledge Augmentation for Language Models

    Nanjing University · Tsinghua University · Northeastern University

  10. MisEdu-RAG: A Misconception-Aware Dual-Hypergraph RAG for Novice Math Teachers

    Apr 5, 2026Zhihan Guo, Yuting Lu, Jionghao LinRetrieval-Augmented GenerationKnowledge Augmentation for Language Models

    The University of Hong Kong, Hong Kong SAR, China · Carnegie Mellon University, Pittsburgh PA 15213, USA · Monash University, Clayton VIC 3800, Australia

  11. Beyond the Parameters: A Technical Survey of Contextual Enrichment in Large Language Models: From In-Context Prompting to Causal Retrieval-Augmented Generation

    Apr 3, 2026Prakhar Bansal, Shivangi AgarwalKnowledge Augmentation for Language ModelsRetrieval-Augmented Generation

  12. Injecting Structured Biomedical Knowledge into Language Models: Continual Pretraining vs. GraphRAG

    Apr 3, 2026Jaafer Klila, Sondes Bannour Souihi, Rahma Boujelben +2Knowledge Augmentation for Language ModelsContinued Pretraining

    Université Paris-Saclay, CEA, List Palaiseau, France · University of Sfax Sfax, Tunisia

  13. Where Does Robustness Live? Neuron-Guided Adaptation for Retrieval-Augmented Language Models

    Apr 2, 2026Jae O Lee, Jaemin Kim, Sumyeong Ahn +1Retrieval-Augmented GenerationFine-Tuning

    1Hanyang University · 2KENTECH

  14. Autolearn: Learn by Surprise, Commit by Proof

    Apr 2, 2026Kang-Sin ChoiOnline Language Model AdaptationKnowledge Augmentation for Language Models

    Ewha Womans University

  15. Procedural Knowledge at Scale Improves Reasoning

    Apr 1, 2026Di Wu, Devendra Singh Sachan, Wen-tau Yih +1Retrieval-Augmented ReasoningLLM Reasoning

    University of California, Los Angeles · Meta FAIR

  16. To Memorize or to Retrieve: Scaling the Interaction Between Pretraining and Retrieval

    Apr 1, 2026Karan Singh, Michael Yu, Varun Gangal +4Retrieval-Augmented GenerationKnowledge Augmentation for Language Models

    Stanford University · †DegenAI Labs · Independent Researcher +3

  17. Training the Knowledge Base through Evidence Distillation and Write-Back Enrichment

    Mar 26, 2026Yuxing Lu, Xukai Zhao, Wei Wu +1Retrieval-Augmented GenerationKnowledge Augmentation for Language Models

    Peking University · Georgia Institute of Technology · Tsinghua University

  18. Grounding Arabic LLMs in the Doha Historical Dictionary: Retrieval-Augmented Understanding of Quran and Hadith

    Mar 25, 2026Somaya Eltanbouly, Samer RashwaniArabic NLPKnowledge Augmentation for Language Models

    College of Islamic Studies, Hamad bin Khalifa University, Doha, Qatar.

  19. Synthetic Mixed Training: Scaling Parametric Knowledge Acquisition Beyond RAG

    Mar 24, 2026Seungju Han, Konwoo Kim, Chanwoo Park +5Knowledge Augmentation for Language ModelsSynthetic Data Augmentation

    Stanford University · MIT · University of Washington

  20. SPA: A Simple but Tough-to-Beat Baseline for Knowledge Injection

    Mar 23, 2026Kexian Tang, Jiani Wang, Shaowen Wang +1Knowledge Augmentation for Language ModelsSynthetic Data Generation for Language Models

    Institute for Interdisciplinary Information Sciences, Tsinghua University

  21. Revisiting Quantum Code Generation: Where Should Domain Knowledge Live?

    Mar 23, 2026Oscar Novo, Oscar Bastidas-Jossa, Alberto Calvo +2LLM Code GenerationKnowledge Augmentation for Language Models

    Quantum Computing Research, QCentroid, 48001, Bilbao, Spain

  22. DomAgent: Leveraging Knowledge Graphs and Case-Based Reasoning for Domain-Specific Code Generation

    Mar 22, 2026Shuai Wang, Dhasarathy Parthasarathy, Robert Feldt +1Case-Based ReasoningCode Generation

    Chalmers University of Technology, Gothenburg, Sweden · Volvo Group, Gothenburg, Sweden

  23. Knowledge Packs: Zero-Token Knowledge Delivery via KV Cache Injection

    Mar 22, 2026Andrey PustovitKnowledge Augmentation for Language ModelsActivation Steering

    Independent Researcher

  24. KA2L: A Knowledge-Aware Active Learning Framework for LLMs

    Mar 18, 2026Haoxuan Yin, Chen Tang, Yangfan Wang +2Active LearningLLM Fine-Tuning

    Faculty of Computing, Harbin Institute of Technology, Harbin, 150001, China · Institute for Advanced Algorithms Research, Shanghai, 201306, China · National Key Laboratory of Smart Farm Technologies and Systems, Harbin, 150001, China

  25. Continually self-improving AI

    Mar 18, 2026Zitong YangLanguage Model Self-ImprovementSelf-Training for Language Models

    Department of Statistics, Stanford University

  26. Exploring different approaches to customize language models for domain-specific text-to-code generation

    Mar 17, 2026Luís Freire, Fernanda A. Andaló, Nicki Skafte DetlefsenCode GenerationLLM Code Generation

    Technical University of Denmark · The LEGO Group

  27. SIA: A Synthesize-Inject-Align Framework for Knowledge-Grounded and Secure E-commerce Search LLMs with Industrial Deployment

    Mar 17, 2026Zhouwei Zhai, Mengxiang Chen, Anmeng ZhangE-Commerce SearchKnowledge Augmentation for Language Models

    JD.com Beijing, China

  28. Information Asymmetry across Language Varieties: A Case Study on Cantonese-Mandarin and Bavarian-German QA

    Mar 16, 2026Renhao Pei, Siyao Peng, Verena Blaschke +2Multilingual QACultural Knowledge in Language Models

    MaiNLP, Center for Information and Language Processing, LMU Munich, Germany · Munich Center for Machine Learning (MCML), Germany · ELLIS Institute Finland +1

  29. Enhanced Drug-drug Interaction Prediction Using Adaptive Knowledge Integration

    Mar 13, 2026Pengfei Liu, Jun Tao, Zhixiang RenDrug-Drug Interaction PredictionKnowledge Augmentation for Language Models

    Pengcheng Laboratory, Shenzhen 518000 · School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou 510006, China

  30. Automating Skill Acquisition through Large-Scale Mining of Open-Source Agentic Repositories: A Framework for Multi-Agent Procedural Knowledge Extraction

    Mar 12, 2026Shuzhen Bi, Mengsong Wu, Hao Hao +5Mining Software RepositoriesLLM Agent Skill Learning

    Shanghai Innovation Institute · University of Science and Technology of China · East China Normal University