Personal AI Agents

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3 papers in the last four weeks, against 2 the four weeks before. 0.0% of all new papers.

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Who Keeps the Gains from Personal AI Assistants? Seller Adaptation and the Unassisted in a Language-Model Market Simulation
Oct 5, 2026Haonan Huang, Joey XiaoAgentic Commerce Personal AI Agents
Princeton University · New York University
Who Is Your Agent Serving? Provider-Side Indirect Prompt Injection in Proactive Agents
Oct 4, 2026Rui Wang, Chao Wang, Xinchen Wang +3AI Agent Security Indirect Prompt Injection
Hefei University of Technology · University of Science and Technology of China
Richard: Voice-First Mobile Interaction for Persistent Tasks
Sep 30, 2026Xinyang ChenSpoken Dialogue Systems Conversational Agents
Emergi-PersonaOS: A Persona Agent Operating System for Situational Adaptation and Controllable Evolution
Sep 23, 2026Haoluan Fu, Keni Chen, Xinyu Jia +3Persona Consistency Persona-Conditioned Generation
Emergi Lab of Qianzhen Digital Tech, China · Hangzhou Dianzi University, China
Efficient Test-Time Adaptation through Human-AI Interaction
Sep 3, 2026Zora Zhiruo Wang, Apurva Gandhi, Rulin Shao +22Test-Time Adaptation Rubric-Based Evaluation
Carnegie Mellon University · University of Washington · Handshake AI +3
VibeLifeBench: Can Your Life Agent Be Proactive and Persistent in a Living World?
Aug 11, 2026Xiaohongshu IncLong-Horizon Agent Evaluation AI Agent Benchmarks
Xiaohongshu Dots Studio · Evolvent AI
Homebot: A Personal AI Agent for Conversational Home Assistance and Automation
Aug 3, 2026Shengyuan Ye, Yixin Zhang, Han Liang +3Tool-Augmented Language Model Agents Tool-Using Agents
Power Dispatching and Controlling Center, Guangdong Power Grid Co., Ltd., Guangzhou, China · School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou, China · Department of Information Engineering, The Chinese University of Hong Kong, Hong Kong SAR, China
Code Is the Body: Agent-Owned Software Bodies for Recursive Evolution and Descent
Jul 30, 2026Roy Zhao, Zhenyu ZhaoAI Agent Governance Human-AI Co-Creation
Paul G. Allen School of Computer Science & Engineering, University of Washington · 1Paul G. Allen School of Computer Science & Engineering, University of Washington · Independent Researcher +1
PAUSE: A User-Centric Benchmark for Personal AI Assistants in Unified Service Environments
Jul 29, 2026Haoyu Chen, Xirui Shi, Yuyao Wang +2Long-Horizon Agent Evaluation AI Agent Benchmarks
Electrical and Computer Engineering
Setoka: A Benchmark for Hierarchical User Understanding in Personalized Agents over Heterogeneous Data
Jul 29, 2026Lingyang Zeng, Guangze Chen, Kaichen Yu +9Personality Modeling in Language Models Memory Agent Benchmarks
East China Normal University · The Chinese University of Hong Kong
HiMe: Real-Time Self-Hosted Personal Agent Platform for Health Insights with Wearable Devices
Jul 23, 2026Wei Liu, Siya Qi, Linhai Zhang +2LLM Agents Wearable Health Monitoring
King’s College London · The Alan Turing Institute
Mi-Memory: A Lifecycle Memory Framework for Personal AI
Jul 21, 2026Xule Liu, Hanlin Teng, Chao Li +15Multimodal Memory LLM Personalization
Darwin Agent Team
PersonaMem-v3: Toward Omni-Platform Personal Intelligence for Holistic User Understanding, Recommendation, and Agentic Tasks
Jul 16, 2026Bowen Jiang, Yuan Yuan, Zhuoqun Hao +12Personal AI Agents LLM Personalization
University of Pennsylvania · Meta Recommendation Systems · MIT
PaperRouter-Agent: A Content-Grounded LLM Agent for Personalized Hierarchical Paper Routing
Jul 13, 2026Keshen Zhou, Lintao Wang, Suqin Yuan +3LLM Personalization Retrieval-Augmented Classification
University of Sydney, Sydney, NSW 2006, Australia
SovereignPA-Bench: Evaluating User-Owned Personal Agents under Evolving Intent, Platform Mediation, and Consent Constraints
Jul 6, 2026Dylan Zongmin LiuLLM Agent Evaluation AI Agent Benchmarks
Stanford University
SovereignNegotiation-Bench: Evaluating User-Owned Personal Agents In Delegated Bargaining Under Privacy, Consent, Evidence, And Institutional Pressure
Jul 2, 2026Dylan Zongmin LiuAutomated Negotiation AI Agent Benchmarks
Stanford University
AOHP: An Open-Source OS-Level Agent Harness for Personalized, Efficient and Secure Interaction
Jun 22, 2026Shanhui Zhao, Jiacheng Liu, Guohong Liu +13Computer-Use Agents AI Agent Security
Tsinghua University · Peking University · The University of Hong Kong
AdaMem: Learning What to Remember with Adaptive Memory Policies for Personalized Agents
Jun 19, 2026Xingyu Chen, Rui Wang, Zhaopeng Tu +1LLM Agent Memory Persistent Memory for Language Models
Shanghai Jiao Tong University, Tencent · Shanghai Jiao Tong University · Tencent
MyPCBench: A Benchmark for Personally Intelligent Computer-Use Agents
Jun 15, 2026Lawrence Keunho Jang, Andrew Keunwoo Jang, Jing Yu Koh +1Computer-Use Agent Benchmarks Tool-Augmented Language Model Agents
Carnegie Mellon University
User as Code: Executable Memory for Personalized Agents
Jun 15, 2026Bojie LiPersistent Memory for Language Models Knowledge Representation
Pine AI
iOSWorld: A Benchmark for Personally Intelligent Phone Agents
Jun 8, 2026Lawrence Keunho Jang, Mareks Woodside, Geronimo Carom +3Computer-Use Agent Benchmarks Computer-Use Agents
Carnegie Mellon University
Personal AI Agent for Camera Roll VQA
Jun 3, 2026Thao Nguyen, Krishna Kumar Singh, Donghyun Kim +2Visual Question Answering Long-Horizon LLM Agents
University of Wisconsin-Madison · Adobe Research · Korea University
TIDE: Proactive Multi-Problem Discovery via Template-Guided Iteration
Jun 3, 2026Soyeong Jeong, Jinheon Baek, Minki Kang +1Software Engineering Agents Personal AI Agents
KAIST
COLLEAGUE.SKILL: Automated AI Skill Generation via Expert Knowledge Distillation
May 29, 2026Tianyi Zhou, Dongrui Liu, Leitao Yuan +2LLM Agent Skill Learning Persona-Conditioned Generation
Shanghai Artificial Intelligence Laboratory
Syll: Open-Source Personal Automation with Cross-Surface Execution
May 28, 2026Bo Zhang, Borui Zhang, Chenghao Jiang +5LLM Agent Skill Learning Human-in-the-Loop AI
Tsinghua University · GigaAI
Claw-Anything: Benchmarking Always-On Personal Assistants with Broader Access to User's Digital World
May 25, 2026Yusong Lin, Xinyuan Liang, Haiyang Wang +8Computer-Use Agent Benchmarks AI Agent Benchmarks
Beijing Institute of Technology · Huawei Technologies Co., Ltd · Peking University +1
Beyond Scaling: Agents Are Heading to the Edge
May 18, 2026Chunlin Tian, Dongqi Cai, Wanru Zhao +1Edge Computing Personal AI Agents
University of Cambridge · Nanjing University · University of Macau
OpenJarvis: Personal AI, On Personal Devices
May 16, 2026Jon Saad-Falcon, Avanika Narayan, Robby Manihani +10On-Device Language Model Inference LLM Agents
Stanford University · Lambda Labs
Toward Natural and Companionable Virtual Agents via Cross-Temporal Emotional Modeling
May 15, 2026Feier Qin, Xiao Li, Yi Zheng +5Long-Horizon LLM Agents Memory-Augmented Agents
Communication University of China BeiJing, China · Microsoft Research Asia BeiJing, China · Institute of Artificial Intelligence, China Telecom BeiJing, China
Orchard: An Open-Source Agentic Modeling Framework
May 14, 2026Baolin Peng, Wenlin Yao, Qianhui Wu +11AI Coding Agents Computer-Use Agents
Microsoft Research · Columbia University · UIUC

Oct 5, 2026, cs.MAJ/K move · Enter open · S save

Who Keeps the Gains from Personal AI Assistants? Seller Adaptation and the Unassisted in a Language-Model Market Simulation

Haonan Huang, Joey Xiao

Princeton University · New York University

Agentic Commerce Personal AI Agents

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Personal AI assistants are beginning to transact for consumers, and early adopters capture real savings. Whether those savings survive, and what happens to consumers who have no assistant, depends on how sellers respond -- a question single-user evidence cannot answer. We build an agent-based rental market in which language models play consumers, assistants, and six adaptive sellers guided by an algorithmic pricing tool. Half the population receives an assistant under an advisory or an executing mandate; the contract pairs a fee only the renter's physical action avoids with a pre-selected add-on an authorised assistant can cancel online. An analytical benchmark and a behaviourally calibrated rule market supply ex-ante predictions, and paired branches with frozen versus adaptive sellers separate adoption effects from market feedback. Across thirty simulated markets, executing assistants cut adopters' spending by 13.7 USD per renter-day when sellers are frozen; adaptation claws back about a third, leaving 8.7, with the gains arriving both as lower bills and as rentals completed at all. Sellers raise headline rates while cutting fees, and the calibrated forecast of the burden on unassisted consumers (+3.6) does not transfer: their mean spending change is +0.4, confidence interval -0.6 to +1.3. Seller-model swaps and a within-market transfer of fee-setting to the pricing tool show that fee conduct, and with it the division of the gains, is decided on the seller side. Assistants, we conclude, should be evaluated at market level -- completion, total spending, and non-users included -- and the comparison layers locate exactly where a calibrated behavioural forecast fails in a language-model market.

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Latest papers 41