Knowledge Augmentation for Language Models

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11 papers in the last four weeks, up 175% on the four weeks before. 0.1% of all new papers.

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UNREAL: Unifying Retrieval and Long-Context with a Single Model
Oct 6, 2026Edan Kinderman, Elad Hoffer, Yochai Blau +4Retrieval-Augmented Generation Knowledge Augmentation for Language Models
NVIDIA · Technion
From Papers to Mechanisms: An Evidence-Grounded Knowledge Substrate for Scientific Language Models
Oct 5, 2026Qiuhui Chen, Yibo Liu, Tao Dai +3Knowledge Augmentation for Language Models Scientific QA
School of Information Science and Engineering, East China University of Science and Technology · School of Computer Science, Shanghai Jiao Tong University · Tencent
From Knowledge Access to Source Learning: Developing Source-Specific Competence
Oct 1, 2026Lucheng Fu, Kejing Xia, Yiyang Wang +10Continual Learning for LLM Agents Knowledge Augmentation for Language Models
Georgia Institute of Technology · University of Illinois at Urbana-Champaign · University of California, Los Angeles
On the (In)effectiveness of AMR Augmentation for Large Language Models
Sep 30, 2026Hoa Quynh Nhung Nguyen, Jacopo Staiano, Michael SullivanLLM Evaluation Knowledge Augmentation for Language Models
Saarland University · University of Trento
Draft-KV: Learning Useful Latent Communication Between Language Models
Sep 28, 2026Linquan Wu, Shichang Meng, Tianxiang Jiang +7Knowledge Augmentation for Language Models Multi-LLM Collaboration
City University of Hong Kong · University of Science and Technology of China · University of Electronic Science and Technology of China +3
When Does Structured Knowledge Help Neural Theorem Proving?
Sep 28, 2026Sareh Nabi, Roland Vogl, Marzieh NabiAutomated Theorem Proving Knowledge Augmentation for Language Models
Stanford University
Context Spanning: A Communication Framework for Full-Duplex Speech Models and External LLM Backends
Sep 27, 2026Seonghyeon Go, Yongwoo Kim, Hyeonjin Cha +1Knowledge Augmentation for Language Models Spoken Dialogue Systems
Mindlogic
Semantic Abstraction for Natural Language Inference: a Methodological Framework for Discovering and Compensating Semantic Knowledge and Reasoning Gaps in Large Language Models
Sep 22, 2026David Torres-Moreno, Jorge Hermosillo-ValadezKnowledge Augmentation for Language Models Natural Language Inference
GraphSkillAA: Attribution-Guided Skill-Graph Updating with Targeted Validation and Rollback
Sep 17, 2026Ziqiao Shang, Ling-Yue Ge, Lan-Zhe GuoKnowledge Augmentation for Language Models LLM Agent Skill Learning
National Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, China · School of Intelligence Science and Technology, Nanjing University, Suzhou, China
Where Should a Document Live: Context, Representations, or Parameters?
Sep 15, 2026Nathanaël Carraz Rakotonirina, Momchil Hardalov, Gonzalo Iglesias +1Memory-Augmented Language Models Knowledge Augmentation for Language Models
Amazon AGI
PunGraph: Retrieval-Enhanced Phonetic-Semantic Graph Reasoning for Pun Understanding
Sep 15, 2026Yuchen Su, Zijian Huang, Yaotian Shi +6Figurative Language Understanding Knowledge Augmentation for Language Models
School of Computer Science, University of Auckland, New Zealand · School of Computer and Information Technology, Shanxi University · School of Electronic Engineering and Computer Science, Queen Mary University of London
Repair Before Reinforce: Context-Augmented Knowledge Graph Reasoning for Multi-Hop Question Answering
Sep 14, 2026Tharaka D. Fonseka, Niraj K. JhaMulti-Hop QA Knowledge Augmentation for Language Models
Dept. of Electrical and Computer Engineering, Princeton University
KuaiRP Series Role-playing Models Technical Report
Sep 12, 2026Yipeng Wang, Ziwei Zhang, Jiahui Zhang +2Large Language Model-Based Role-Play Simulation Knowledge Augmentation for Language Models
Kuaishou GameMind Lab
KItCAT: Knowledge Injection via Input Corruption for Auto-regressive Training
Aug 31, 2026Meghanadh Pulivarthi, Kushagra Bhushan, Vineet Kumar +5Language Model Pretraining Knowledge Augmentation for Language Models
IBM · Work done while at IBM. Currently at Amazon Books
Frozen Memory Is Not Enough: Rethinking External Memory as Extraction
Aug 17, 2026Mingyuan Li, Guangsheng Yu, Xu Wang +1Memory-Augmented Language Models Knowledge Augmentation for Language Models
ELLIS Institute Finland · University of Turku · University of Technology Sydney
LittleLearner: Language Models Under Pedagogically Controlled Knowledge Exposure
Aug 13, 2026Fanfei Li, Jana Zeller, Manuel Prada-Corral +4Language Model Pretraining Knowledge Augmentation for Language Models
ETHZ
LoKiFormer: Locality-aware Attention with Decoupled Knowledge Memory for Efficient Large Language Model Pretraining
Aug 12, 2026Qiuwu Chen, Zimo Liu, Yuchen Li +8Language Model Pretraining Memory-Augmented Language Models
AIGCode · South China University of Technology · Pazhou Laboratory
AquiLLM: An Architecture for Supporting Tacit Knowledge Capture in Research Groups
Aug 9, 2026Jack Stark, Srinath Saikrishnan, Vikram Seenivasan +3Memory-Augmented Language Models Knowledge Augmentation for Language Models
University of California, Los Angeles, Los Angeles, California, USA · Southern Oregon University, Ashland, Oregon, USA
KV-Skill: Forging Expertise in the Model's Native Language
Aug 5, 2026Zhaowei Han, Xiang Zhang, Bing Han +3Knowledge Augmentation for Language Models Parameter-Efficient Fine-Tuning
University of Michigan, Ann Arbor, MI, USA
Wnuan: Staged Post-Training for Question Answering over Proprietary Enterprise Knowledge
Aug 3, 2026Xiaofeng Shi, Xiaosong Qiu, Wenxin Ma +6Supervised Fine-Tuning Knowledge Augmentation for Language Models
Beijing Academy of Artificial Intelligence (BAAI) · Beijing District Heating Group Co., Ltd. (BDHG) · Beijing University of Posts and Telecommunications (BUPT)
RING: Retrieval-Internalized Generation for Continual Large-Scale Knowledge Injection
Aug 3, 2026Shicheng Xu, Liang Pang, Liyi Chen +7Retrieval-Augmented Generation Continual Learning for LLMs
State Key Laboratory of AI Safety, Institute of Computing Technology, CAS · University of Chinese Academy of Sciences · Xiaohongshu Inc.
The Graph Language: How Knowledge Graphs Speak to Large Language Models
Aug 2, 2026Giuseppe PirròLLM Grounding Knowledge Augmentation for Language Models
DeMaCS, University of Calabria
SkillSmith: Learning to Compose Parametric Skills and Textual Knowledge
Jul 29, 2026Lucio M. Dery, Benedict Aaron Tjandra, Siavash Samiei +4Knowledge Augmentation for Language Models Prompt Tuning
Google DeepMind
Fewer Clarifications, Better Code: Benchmarking Cross-Session Personalized Ambiguity Adaptation in Coding Assistants
Jul 29, 2026Zijian Xu, Wenshuo Zhang, Zisen Qin +4Knowledge Augmentation for Language Models Code Generation
Southeast University · The Hong Kong University of Science and Technology
Retrieval-Augmented Large Language Models as Components of Cognitive Computing architecture for Regulatory Knowledge Management
Jul 27, 2026Dariusz Nowak-NovaRetrieval-Augmented Generation Knowledge Augmentation for Language Models
1WSB University, Poland
Do Small Models Use the Law You Give Them? Context-Injected Fine-Tuning for Legal QA in Bangladesh
Jul 26, 2026Moniruzzaman Mahadi, Abrar Mohammed Tanzim Alam, Sayma Siddika Monalisa +3Multilingual Language Model Evaluation LLM Grounding
Department of Electrical and Computer Engineering, North South University Dhaka, Bangladesh · Department of Computer Science and Engineering, BRAC University Dhaka, Bangladesh
Dynamic Commonsense Coordination for Empathetic Response Generation
Jul 24, 2026Zhengyu QiKnowledge Augmentation for Language Models Emotion-Aware Dialogue Generation
Leiden Institute of Advanced Computer Science (LIACS) Leiden University, The Netherlands
Data Quality over Capacity: Internalizing Documents into LoRA Adapters for Closed-Book QA
Jul 23, 2026Joan Figuerola HurtadoKnowledge Augmentation for Language Models LLM Fine-Tuning
Independent Researcher
AdaKP: Online Adaptive Knowledge-Point Selection for Reasoning-Oriented Reinforcement Learning
Jul 23, 2026Zibin Meng, Zhenyu Zhao, Chunqiang RunKnowledge Augmentation for Language Models RL for Language Model Reasoning
The Hong Kong University of Science and Technology · University of the Chinese Academy of Sciences
Notes to Self: Can LLMs Benefit from Experiential Abstractions?
Jul 22, 2026Chang Liu, Xinyu Li, Artur DubrawskiKnowledge Augmentation for Language Models LLM Reasoning
Auton Lab, Carnegie Mellon University
Scaling Laws for Hypernetwork-Based Knowledge Injection in Large Language Models
Jul 21, 2026Nischay Dhankhar, Dos Baha, Abulhair SaparovKnowledge Augmentation for Language Models Hypernetworks
Nace AI · Purdue University
Debate-on-Graph: Reliable and Adaptive Reasoning of Large Language Model on Uncertain Knowledge Graph
Jul 19, 2026Peiji Yu, Xin Chen, Tianxing WuKnowledge Augmentation for Language Models Multi-Agent Debate
School of Computer Science and Engineering, Southeast University, Nanjing, China · Key Laboratory of New Generation Artificial Intelligence Technology and Its Interdisciplinary Applications (Southeast University), Ministry of Education, China
Smarter and Cheaper at Once: Byte-Exact KV-Cache Grafting Turns a Frozen Small Model into a Verified-Knowledge Flywheel
Jul 15, 2026Sietse SchelpeMemory-Augmented Language Models Knowledge Augmentation for Language Models
Corbenic AI
Co-LMLM: Continuous-Query Limited Memory Language Models
Jul 8, 2026Yair Feldman, Linxi Zhao, Nathan Godey +5Language Model Pretraining Memory-Augmented Language Models
Department of Computer Science Cornell University
PHITSBench: an execution-scored benchmark for AI-assisted PHITS radiation-transport input generation using natural language
Jul 8, 2026Xianglin Ji, Svetlana V. BoriskinaKnowledge Augmentation for Language Models Code Generation
Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
TF-Engram: A Train-Free Engram with SSD-Backed Memory for Large Language Models
Jul 8, 2026Yutang Ma, Kecheng Huang, Xikun Jiang +1Memory-Augmented Language Models Knowledge Augmentation for Language Models
The Chinese University of Hong Kong · Beijing Institute of Technology, Zhuhai
Evaluating SageMath-Augmented LLM Agents for Computational and Experimental Mathematics
Jul 7, 2026Pavel Snopov, German MagaiMathematical Reasoning Benchmarks Knowledge Augmentation for Language Models
School of Mathematical and Statistical Sciences, The University of Texas Rio Grande Valley, USA · Noeon Research, Tokyo, Japan.
Integrating knowledge graphs and multilingual scholarly corpora for domain-adaptive LLMs in SSH
Jul 7, 2026Adam Faci, Alessio Miaschi, Anne Combe +4Multilingual Language Models LLM Evaluation
Huma-Num, CNRS, Paris, France · CNR - Institute for Computational Linguistics “A. Zampolli” (CNR-ILC), Pisa, Italy · Inria, France +1
When Should LLMs Search? Counterfactual Supervision for Search Routing
Jul 7, 2026Minho KimKnowledge Augmentation for Language Models LLM Routing
1Sangmyung University · 2DMTLABS.
PASTA: A Paraphrasing And Self-Training Approach for Knowledge Updating in LLMs
Jun 27, 2026Takayuki Yamamoto, Daisuke KawaharaContinual Learning for LLMs Knowledge Augmentation for Language Models
Waseda University
LAMP: Lean-based Agentic framework with MCP and Proof Repair
Jun 27, 2026Santhana Srinivasan R, Maithilee PatawarKnowledge Augmentation for Language Models Lean Theorem Proving
Indian Institute of Information Technology, Design and Manufacturing, Kancheepuram
Self-Supervised Theorem Discovery in a Formal Axiomatic System
Jun 27, 2026Kazuki Ota, Takayuki Osa, Tatsuya HaradaAutomated Theorem Proving Knowledge Augmentation for Language Models
The University of Tokyo, Japan · RIKEN AIP, Japan
KARLA: Knowledge-base Augmented Retrieval for Language Models
Jun 25, 2026Francois Crespin, Fabian M. Suchanek, Nils HolzenbergerRetrieval-Augmented Generation LLM Grounding
IP Paris, LTCI · Télécom Paris · Institut Polytechnique de Paris, France
Scaling LLM Knowledge Boundaries via Distribution-Optimized Synthesis
Jun 22, 2026Songze Li, Yarong Lan, Zhongpu Bo +16Synthetic Data Pretraining Knowledge Augmentation for Language Models
Zhejiang University · ZJU-Ant Group Joint Lab of Knowledge Graph · Ant Group
ARIA: A Causal-Aware Framework for Rescuing LLM Reasoning in Trustworthy Materials Discovery
Jun 21, 2026Yi Cao, Liaoyaqi Wang, Jieneng Chen +3Knowledge Augmentation for Language Models Materials Property Prediction
SPARK: Security Knowledge Priming and Representation-Guided Knowledge Activation for LLM-based Secure Code Generation
Jun 15, 2026Xiaoyun Xu, Lichao Wu, Jona te Lintelo +2Knowledge Augmentation for Language Models LLM Security
Radboud University · University of Bristol · University of Zagreb
Retrievable Gradients: Continual Post-Training Without Cumulative Weight Drift
Jun 14, 2026Weihang Su, Jiacheng Kang, Jingyan Xu +7Retrieval-Augmented Generation Continual Learning for LLMs
Department of Computer Science and Technology, Tsinghua University
Decoupled Mixture-of-Experts for Parametric Knowledge Injection
Jun 12, 2026Baoqing Yue, Weihang Su, Qingyao Ai +5Mixture-of-Experts Language Models Knowledge Augmentation for Language Models
Department of Computer Science and Technology, Tsinghua University
Knowledge Graph Enhanced Memory-Augmented Retrieval for Long Context Modeling
Jun 12, 2026Ghadir Alselwi, Basem Suleiman, Hao Xue +4Memory-Augmented Language Models Knowledge Augmentation for Language Models
University of New South Wales, Sydney, NSW, Australia · 2Hong Kong University of Science and Technology (Guangzhou) · University of Southampton, Southampton, UK +2
External Experience Serving in Production LLM Systems: A Deployment-Oriented Study of Quality-Cost Trade-offs
Jun 10, 2026Lin Sun, Heming Zhang, Xiangzheng ZhangLLM Serving Knowledge Augmentation for Language Models
Qiyuan Tech
LLMs+Graphs: Toward Graph-Native, Synergistic AI Systems
Jun 10, 2026Arijit Khan, Longxu Sun, Xin HuangKnowledge Augmentation for Language Models LLM Reasoning with Graphs
Bowling Green State University, Ohio, USA · Hong Kong Baptist University, Hong Kong, China
Pushing the Limits of LLM Tool Calling via Experiential Knowledge Integration and Activation
Jun 9, 2026Yupu Hao, Zhuoran Jin, Huanxuan Liao +2Knowledge Augmentation for Language Models Inference-Time Scaling
1The Key Laboratory of Cognition and Decision Intelligence for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China · School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China
Where Should Knowledge Enter? A Layered Framework for Knowledge Infusion in Multimodal Iterative Generative Model
Jun 4, 2026Renjith Prasad, Chathurangi Shyalika, Anushka Pawar +2Knowledge Augmentation for Language Models
University of South Carolina · Indian AI Research Organization
I Know What You Meme, Even If it Emerged Today: Understanding Evolving Memes through Open-World Knowledge Acquisition
Jun 3, 2026Shanhong Liu, Rui Cao, Pai Chet Ng +1Retrieval-Augmented Generation Knowledge Augmentation for Language Models
Singapore University of Technology and Design · Singapore Institute of Technology
Streaming Knowledge Compilation: Proactive Materiality-Scored Pinning for Time-Evolving LLM Wikis
Jun 3, 2026Juan M. HuertaMemory-Augmented Language Models Knowledge Augmentation for Language Models
Zinnia Tech Solutions 600 Steamboat Road Greenwich, CT 06830, USA
NovelAPIBench: Diagnosing How A Code LLM Learns to Use Novel APIs
Jun 2, 2026Jinnuo Liu, Yue Peng, Jinhan Niu +1Knowledge Augmentation for Language Models LLM Fine-Tuning
NYU Shanghai
Knowledge Graph-Enhanced Zero-Shot Topic Classification: A Multi-Strategy Comparative Study
May 28, 2026Shahana Akter, Yatharth Vohra, Ankita Shukla +1Multi-Label Classification Zero-Shot Text Classification
A2I Lab, School of Computing, Wichita State University · EIS Lab, College of Engineering, University of Nevada, Reno
AIBuildAI-2: A Knowledge-Enhanced Agent for Automatically Building AI Models
May 27, 2026Ruiyi Zhang, Peijia Qin, Qi Cao +2Continual Learning for LLM Agents AI Agents for Scientific Discovery
Department of Electrical and Computer Engineering, University of California San Diego, La Jolla, CA 92093, USA · Department of Medicine, University of California San Diego, La Jolla, CA 92093, USA
Knowledge Graph-Driven Expert-Level Reasoning for Neuroscience
May 24, 2026Jake Stephen, Niraj K. JhaKnowledge Augmentation for Language Models LLM Reasoning with Graphs
Department of Electrical and Computer Engineering, Princeton University
AI-Friendly LaTeX: Using LaTeX Code as a Knowledge Source for Retrieval-Augmented Generation
May 21, 2026Tom VerhoeffRetrieval-Augmented Generation Knowledge Augmentation for Language Models
Department of Mathematics & Computer Science, Eindhoven University of Technology

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UNREAL: Unifying Retrieval and Long-Context with a Single Model

Edan Kinderman, Elad Hoffer, Yochai Blau, Brian Chmiel+3

NVIDIA · Technion

Retrieval-Augmented Generation Knowledge Augmentation for Language Models LLM Inference Acceleration Information Retrieval Long-Context Inference

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Long-context inference and Retrieval-Augmented Generation (RAG) handle evidence selection at vastly different scales, from a single long prompt to an entire corpus. We ask whether a single model-internal mechanism can select evidence across this range. We introduce UNifying REtrieval And Long-Context with a Single Model (UNREAL), a model-native evidence selection framework to span corpus retrieval and long-context inference. UNREAL encodes chunks and derives retrieval queries directly from the frozen LLM's internal representations. It adds fewer than 500K trainable parameters and leaves the backbone unchanged. On a 3B-token, 21M-chunk Wikipedia index, all four dense and hybrid UNREAL backbones outperform state-of-the-art retriever-reranker systems. The best model raises recall from 49.1% to 73.2% on HotpotQA, from 31.7% to 60.1% on 2WikiMultiHopQA, and from 8.8% to 14.4% on MuSiQue. Applied to long-context tasks, the same selection mechanism removes distractors before generation, raising NoLiMa accuracy from 1.0% to 24.83% at its maximum context length of 128K tokens, and LV-Eval's F1 score from 49.97% to 54.66% at 256K. UNREAL also reduces FLOPs and time-to-first-token relative to full-context inference from roughly 32K tokens onward, with larger gains as context grows. Together, these results establish model-internal evidence selection as a common foundation for corpus retrieval and evidence-sparse long-context inference.

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