Knowledge Augmentation for Language Models

Follow this topic Ask about this topic

Momentum

11 papers in the last four weeks, up 120% on the four weeks before. 0.1% of all new papers.

Jul 13Week of Sep 28

Latest papers 111

All topics

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

Jul 22, 2026, cs.CLJ/K move · Enter open · S save

Notes to Self: Can LLMs Benefit from Experiential Abstractions?

Chang Liu, Xinyu Li, Artur Dubrawski

Auton Lab, Carnegie Mellon University

Knowledge Augmentation for Language Models LLM Reasoning

Open paper AskPDF arXiv

Humans distill experience into reusable abstractions, e.g., strategies and cautionary reminders, and apply them to gradually solve problems more effectively. We study whether Large Language Models (LLMs) can similarly benefit from such experiential abstractions. From LLMs' solution traces on the MATH training set, a stronger teacher or the LLMs themselves extract natural-language abstractions into a retrievable library. We explore two usage modes: (1) inference-time retrieval and (2) reinforcement learning (RL) with abstraction-augmented training prompts. Experiential abstractions improve LLM performance on mathematical and logical reasoning benchmarks. Self-extracted abstractions match teacher-extracted ones, and our abstraction usage framework can transfer to other datasets and models. These findings suggest LLMs can extract and apply experiential abstractions much as humans leverage distilled experience.

Momentum

Related topics

Latest papers 111