LLM Context Management

LLM: Large Language Model

This field studies how language models and agents can use conversation history, documents, tool outputs, and memory when their working context is limited or grows costly. Common approaches include truncation and summarization, relevance-based retrieval, structured or external memory, and adaptive policies that decide what to retain, restore, or discard; some systems also manage attention or KV-cache state directly. Methods are tested on tasks such as long-horizon search, coding, multi-turn question answering, and tool use. The central tension is reducing tokens, latency, and cost without losing evidence, dependencies, or safety constraints needed for later decisions, and results vary substantially by task and model.

Latest papers

251 papers37 papers in the last four weeks, up 48% on the four weeks before. 0.2% of all new papers.

Beyond LLM Wrappers: Context Engineering and the Three-Engine Architecture for Reliable Financial AI
Oct 29, 2026Pradeep Kumar GS, Ravi TanniruContext Engineering LLM Context Management
Finteract AI
Context Is a Pipeline, Not a Window: Information Attrition in LLM Agent Harnesses
Oct 26, 2026Yuvraj Sehgal, Mahsa Panahandeh, Naser Ezzati-JivanLLM Context Management LLM Agent Harnesses
Department of Computer Science Brock University St. Catharines, Ontario, Canada · School of Electrical Engineering and Computer Science University of Ottawa Ottawa, Ontario, Canada
MarkovSim: an LLM Agent Harness with Bounded Context for Long-Horizon Computational Simulation
Oct 26, 2026Yeui-Lung Lei, Wen-Bo Chen, Pan ZhangLLM Agent Harnesses Long-Horizon LLM Agents
College of Civil and Transportation Engineering, Shenzhen University, Shenzhen, 518060, China · Department of Civil and Environmental Engineering, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, China.
The Physical Cost of Context: Quality-Constrained Resource Accounting for Coding Agents
Oct 26, 2026Zhongming Yu, Yitong Ma, Hengjia Yu +4LLM Agent Efficiency LLM Context Management
University of California, San Diego · University of Massachusetts Amherst
CTXAgent - Self-Controlled Context Management of LLM Agents
Oct 25, 2026Matthias Busch, Marius Tacke, Roland C. Aydin +2LLM Context Management Context Compaction for LLM Agents
Institute for Artificial Intelligence and Simulation in Mechanics, Hamburg University of Technology, Eißendorfer Straße, 21073 Hamburg, Germany · Institute of Material Systems Modeling, Helmholtz-Zentrum Hereon, Max-Planck-Straße, 21502 Geesthacht, Germany · German Research Center for Artificial Intelligence (DFKI), Stuhlsatzenhausweg, 66123 Saarbrücken, Germany +3
Cache Engineering for Agents
Oct 20, 2026Tianyu Fu, Ruoxi Wang, Zihan Min +6KV-Cache Management Memory Management for LLM Agents
Tsinghua University · The Chinese University of Hong Kong
When the harness decides success: state that cannot be re-observed
Oct 19, 2026Raimondas LenceviciusLLM Agent Harnesses LLM Context Management
Microsoft
Editing as Language: Teaching LLM Agents a Grammar for Native Context Editing
Oct 18, 2026Yunlong Deng, Yan Li, Xing Hu +4LLM Context Management LLM Agent Training
The Chinese University of Hong Kong · Meituan LongCat Team · Nanyang Technological University +2
Bud ContextCompact 2.0: Context Compaction for Agent Success and Accuracy with Small Language Models and Constrained Context Windows
Oct 18, 2026Jithin VG, Ditto PSLLM Context Management LLM Context Compression
Bud Ecosystem
MemPrice: Online Memory Allocation via Adaptive Pricing for Long-Horizon Agents
Oct 18, 2026Yiming Zong, Shiyuan Piao, Jiashuo Jiang +1Memory Management for LLM Agents LLM Context Management
Department of Industrial Engineering & Decision Analysis, HKUST
Reasoning with Context Management and External Memory
Oct 16, 2026Man-Ling Sung, William Hartmann, Jiangying ZhouLLM Context Management Efficient Language Model Reasoning
RTX BBN Technologies, Cambridge MA, USA
When to Forget: Risk-Controlled Context Adaptation for Long-Horizon Agents
Oct 16, 2026Chenle Chen, Yangbo Wei, Zhijie Zheng +6LLM Context Management Long-Horizon Agent Tasks
University of California, Los Angeles · Shanghai Jiao Tong University · Arizona State University +1
From Long Context to Selective Memory:A Survey of Memory-Centric Compression for Large Language Models
Oct 15, 2026Chaogui GouLLM Context Management Memory-Efficient Inference
USTB
Scaling Discovery Requires Forgetting
Oct 14, 2026Shangyin Tan, Ben Zhou, Lakshya A Agrawal +8AI Agents for Scientific Discovery LLM Agent Memory
UC Berkeley · Stanford · Bespoke Labs
Pack Light, CarryOn: Building Object-Oriented Context for Long-Horizon Agents
Oct 13, 2026Yuchen Lu, Julian McAuley, Lei ZhangLLM Context Management Long-Horizon LLM Agents
University of California San Diego
Encoding Context into LLM Weights: What Makes It Context?
Oct 13, 2026Yue Wang, Qizhou Wang, Feng Liu +3LLM Context Management Test-Time Training
The University of Melbourne · RIKEN Center for Advanced Intelligence Project · The University of Tokyo +1
Hashrope: A Persistent Data Structure for Mechanisms of LLM Context Management
Oct 12, 2026Muntaser Syed, Ameerah Alsulami, Marius SilaghiLLM Context Management LLM Inference Acceleration
Florida Institute of Technology
Do Personalized LLMs Need the Whole Conversation? Matching the Full History with Only 5% of Its Text via Relevance-Filtered Context
Oct 10, 2026Erika Hayashi, Andrew ShinLLM Context Management Conversational Memory
Keio University
Curating Always-Loaded Context for LLM Agents: A Capacitated Assortment Model with Censored Feedback
Oct 7, 2026Zexuan Liu, Yuning Yang, Tiancheng ZhaoLLM Context Management LLM Agents
University of Illinois at Urbana-Champaign · Georgia Institute of Technology · Saint Louis University
Decoupling Logic from Persona: Structural Immunity of Edge LLM Agents to Context Pollution
Oct 7, 2026Masaaki Nakatsu, Reno WangLLM Inference LLM Context Management
AO, Inc. / OrbLabs AG · AO, Inc.
Agent-Controlled Forgetting for Tool-Using Agents: Reversible Context Curation in Practice
Oct 6, 2026Jan-Peter FrankeLLM Context Management Agent Memory Management
Münster, Germany
ReFold: Training-Free Reversible Inter-Turn Context Folding for Long-Horizon Agents
Oct 6, 2026Yupeng Su, Jiayi Tian, Zheng Zhang +1LLM Inference Efficiency Long-Context Language Model Inference
University of California, Santa Barbara · Intel
When Agent Context Goes Stale: Incoherence in Volatile Agent Context
Oct 4, 2026Yingying Liu, Junzhou Fang, Chenxiong QianLLM Context Management LLM Agent Reliability
The University of Hong Kong Hong Kong SAR, China
Periscope: Extending Frozen Language Models Beyond Their Context Window
Oct 2, 2026Mohamed Eltahir, Anas Obayd, Raed Rashid +5Long-Context Language Model Inference Long-Context Reasoning in Language Models
King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia · Department of Computer Science, Edge Hill University, Ormskirk, England
Decoupling Memory from Context: Structured Memory for Token-Efficient Test-Time Continual Learning
Oct 2, 2026Yehya Farhat, Michael Desmond, Anastasios KyrillidisContinual Learning for LLM Agents Continual Learning for LLMs
Rice University, Department of Computer Science Houston, TX, USA · IBM Research Yorktown Heights, NY, USA
Trained Agentic Context Management
Oct 1, 2026Bryce SandlundLong-Context Language Modeling Long-Context Reasoning in Language Models
The Persona Is Still There, but Who Is Speaking? Latent Identity Reversion in Persistent AI Agents
Oct 1, 2026David Fraile NavarroPersona Consistency Personality Modeling in Language Models
Centre for Health Informatics, Australian Institute of Health Innovation Macquarie University, Sydney, Australia
Beyond Memory: Harnessing Long-Horizon Agents with Explicit Belief States
Oct 1, 2026Yu Luo, Jiamin Jiang, Yimin Zuo +9Belief Updating in LLMs Long-Horizon LLM Agents
Nankai University · Alibaba Group · Tsinghua University
Role-aware Heuristic Episodic Attention for Conversational LLMs
Oct 1, 2026Wanyang Hong, Zhaoning Zhang, Yi Chen +5Memory-Augmented Language Models Long-Context Language Model Inference
National Key Laboratory of Parallel and Distributed Computing College of Computer Science and Technology National University of Defense Technology, Changsha, China.
Can LLMs Reason Over Long Horizons? An Empirical Evaluation of Context Strategies for Longitudinal Clinical Reasoning
Sep 30, 2026Taye Akinrele, Noorbakhsh Amiri Golilarz, Subash Neupane +2Long-Context Language Model Evaluation Clinical Reasoning
Department of Computer Science, The University of Alabama

Oct 29, 2026J/K move · Enter open · S save

Beyond LLM Wrappers: Context Engineering and the Three-Engine Architecture for Reliable Financial AI

Pradeep Kumar GS, Ravi Tanniru

Finteract AI

Context Engineering LLM Context Management LLM Reliability Financial Reasoning in Language Models Multi-Agent LLM Systems

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Financial AI systems must support decision-bearing questions involving payments, collections, cash flow, and compliance while ensuring numerical accuracy, traceability, and auditability. Large language models (LLMs) enable natural language interaction but cannot independently guarantee reproducible calculations or evidence-grounded recommendations. We present a production-grounded architecture integrating three components: a financial knowledge graph for enterprise relationships, temporal context, and provenance; a deterministic optimization engine for financial calculations and decisions; and a multi-agent LLM layer for intent interpretation, task orchestration, explanation, and claim validation. A coordination layer, termed context engineering, selects, ranks, composes, and validates query-specific context across ERP systems, tools, and tenants. Based on observations from 15 deployments over approximately 11 months, single-agent pipelines exhibited hallucination rates of about 7-9% (5-10% across query types), including invented invoices and unsupported financial claims. Graph-backed multi-agent validation reduced observed rates to below 1%, although these findings are observational rather than causal. ERP data quality and tenant-specific schemas remained major implementation challenges. Reusable mappings, graph templates, and validation policies coincided with a reduction in deployment time from roughly six to two weeks. We argue that financial context engineering extends beyond text-centric retrieval-augmented generation by requiring structured relationships, temporal validity, exact numerical evidence, access controls, and validation against source records and solver outputs. We outline research challenges in evaluation, reproducibility, privacy, context quality, and cross-tenant generalization.