Large Language Model Agents

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Large Language Model Agents

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Multi-Agent Large Language Model

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PrefBench: Evaluating Zero-Shot LLM Agents in Hidden-Preference Personalized Pricing Negotiations
May 19, 2026Yingjie LeiNegotiation Agentic Commerce
MMoA: An AI-Agent framework with recurrence for Memoried Mixure-of-Agent
May 18, 2026Rui ChuMulti-Agent Large Language Model Multi-Agent Large Language Model Systems
SkillGenBench: Benchmarking Skill Generation Pipelines for LLM Agents
May 18, 2026Yifan Zhou, Zhentao Zhang, Ziming Cheng +8Reusable Agent Skills Agentic Benchmarks
Position: A Three-Layer Probabilistic Assume-Guarantee Architecture Is Structurally Required for Safe LLM Agent Deployment
May 18, 2026S. Bensalem, Y. Dong, M. Franzle +6Large Language Model Safety Large Language Model Agents
OEP: Poisoning Self-Evolving LLM Agents via Locally Correct but Non-Transferable Experiences
May 18, 2026Kaixiang Wang, Jiong Lou, Zhaojiacheng Zhou +1Language Model Evasion Attacks Poisoning
PPAI: Enabling Personalized LLM Agent Interoperability for Collaborative Edge Intelligence
May 18, 2026Zile Wang, Qianli Liu, Kaibin Guo +4Heterogeneous Edge Devices Personalized Large Language Model Agents
PROTEA: Offline Evaluation and Iterative Refinement for Multi-Agent LLM Workflows
May 18, 2026Kazuki Kawamura, Satoshi Waki, Kei TatenoMulti-Agent Large Language Model Systems Workflow Automation and Optimization
DuIVRS-2: An LLM-based Interactive Voice Response System for Large-scale POI Attribute Acquisition
May 18, 2026Le Zhang, Shengming Zhang, Rui Zha +3Voice Agents Large Language Model Agents
Multi-agent AI systems outperform human teams in creativity
May 18, 2026Tiancheng Hu, Yixuan Jiang, Haotian Li +5Creativity Multi-Agent Large Language Model
Remembering More, Risking More: Longitudinal Safety Risks in Memory-Equipped LLM Agents
May 18, 2026Ahmad Al-Tawaha, Shangding Gu, Peizhi Niu +2Agent Memory Large Language Model Safety
HydroAgent: Closing the Gap Between Frontier LLMs and Human Experts in Hydrologic Model Calibration via Simulator-Grounded RL
May 18, 2026Zhi Li, Songkun Yan, Jie Cao +4Fundamental Hydrological Principles Personalized Large Language Model Agents
Harnessing LLM Agents with Skill Programs
May 18, 2026Hongjun Liu, Yifei Ming, Shafiq Joty +1Large Language Model Agents Inference-Time
Do LLM Agents Mirror Socio-Cognitive Effects in Power-Asymmetric Conversations?
May 17, 2026Anvesh Rao Vijjini, Sagar Manjunath, Snigdha ChaturvediLarge Language Model Bias Personalized Large Language Model Agents
NeuSymMS: A Hybrid Neuro-Symbolic Memory System for Persistent, Self-Curating LLM Agents
May 17, 2026Mujahid Sultan, Sri Thuraisamy, Daya RajaratnamAgent Memory Neuro-Symbolic Framework
Trust No Tool: Evaluating and Defending LLM Agents under Untrusted Tool Feedback
May 17, 2026Lecheng Yan, Ruizhe Li, Xicheng Han +5Untrusted Input Large Language Model Safety
Learning Transferable Topology Priors for Multi-Agent LLM Collaboration Across Domains
May 17, 2026Taolin Zhang, Zijie Zhou, Jiuheng Wan +4Multi-Agent Large Language Model Reasoning Benchmark
ASPI: Seeking Ambiguity Clarification Amplifies Prompt Injection Vulnerability in LLM Agents
May 17, 2026Udari Madhushani Sehwag, Zhengyang Shan, Heming Liu +3Indirect Prompt Injection Large Language Model Agents
MetaCogAgent: A Metacognitive Multi-Agent LLM Framework with Self-Aware Task Delegation
May 17, 2026Chenyu Wang, Yang ShuMulti-Agent Large Language Model Metacognition
ContractBench: Can LLM Agents Preserve Observation Contracts?
May 17, 2026Jicheng Wang, Yifeng He, Zili Wang +3Kernel Contracts Large Language Model Agents
S-Bus: Automatic Read-Set Reconstruction for Multi-Agent LLM State Coordination
May 16, 2026Sajjad KhanFault Tolerance Multi-Agent Large Language Model
To Call or Not to Call: Diagnosing Intrinsic Over-Calling Bias in LLM Agents
May 16, 2026Wei Shi, Ziheng Peng, Sihang Li +4Call Large Language Model Agents
NeuroMAS: Multi-Agent Systems as Neural Networks with Joint Reinforcement Learning
May 16, 2026Haoran Lu, Luyang Fang, Wenxuan Zhong +1Multi-Agent Systems Multi-Agent Large Language Model
State Contamination in Memory-Augmented LLM Agents
May 16, 2026Yian Wang, Agam Goyal, Yuen Chen +1Agent Memory Large Language Model Agents
Counterparty Modeling is Not Strategy: The Limits of LLM Negotiators
May 15, 2026Romain Cosentino, Sarath Shekkizhar, Adam Earle +1Negotiation Large Language Model Agents
The Scaling Laws of Skills in LLM Agent Systems
May 15, 2026Charles Chen, Qiming Yu, Yuhang Gu +12Large Language Model Agents Scaling Laws
FORGE: Self-Evolving Agent Memory With No Weight Updates via Population Broadcast
May 15, 2026Igor Bogdanov, Chung-Horng Lung, Thomas Kunz +3Large Language Model Agents Agent Memory
Context, Reasoning, and Hierarchy: A Cost-Performance Study of Compound LLM Agent Design in an Adversarial POMDP
May 15, 2026Igor Bogdanov, Chung-Horng Lung, Thomas Kunz +3Large Language Model Agents Partially Observable Markov Decision Process
paper.json: A Coordination Convention for LLM-Agent-Actionable Papers
May 15, 2026Arquimedes CanedoReproducibility Large Language Model Agents
Look Before You Leap: Autonomous Exploration for LLM Agents
May 15, 2026Ziang Ye, Wentao Shi, Yuxin Liu +6Efficient Exploration Large Language Model Agents
Optimization-as-a-Service via Multi-Agent Large Language Model for Radio Access Networks
May 15, 2026Chaoqun You, Yueyue Dai, Xingqiu He +3Open Radio Access Networks Optimal Scheduling
DimMem: Dimensional Structuring for Efficient Long-Term Agent Memory
May 15, 2026Wentao Qiu, Haotian Hu, Fanyi Wang +2Agent Memory Long-Term Memory
Differentiable Mixture-of-Agents Incentivizes Swarm Intelligence of Large Language Models
May 15, 2026Xingjian Wu, Junkai Lu, Siyu Yan +4Multi-Agent Large Language Model Swarms
Rule2DRC: Benchmarking LLM Agents for DRC Script Synthesis with Execution-Guided Test Generation
May 15, 2026Jinuk Kim, Junsoo Byun, Donghwi Hwang +2Test Generation Mock-Interface Synthesis
Response-Conditioned Parallel-to-Sequential Orchestration for Multi-Agent Systems
May 15, 2026Nurbek Tastan, Alex Iacob, Lorenzo Sani +4Multi-Agent Systems Large Language Model Agents
Hybrid LLM-based Intelligent Framework for Robot Task Scheduling
May 15, 2026Swayamjit Saha, Subhabrata Das, Haonan Duan +1Large Language Model Agents Hybrid
Hidden in Memory: Sleeper Memory Poisoning in LLM Agents
May 14, 2026Sidharth Pulipaka, Stanislau Hlebik, Leonidas Raghav +4Large Language Model Agents Multiple Attack Surfaces
From Text to Voice: A Reproducible and Verifiable Framework for Evaluating Tool Calling LLM Agents
May 14, 2026Md Tahmid Rahman Laskar, Xue-Yong Fu, Seyyed Saeed Sarfjoo +3Voice Agents Large Language Model Judges
Concurrency without Model Changes: Future-based Asynchronous Function Calling for LLMs
May 14, 2026Guangyu Feng, Huanzhi Mao, Prabal Dutta +1Asynchronous Execution Large Language Model Agents
Trustworthy Multi-Agent Systems: Mitigating Semantic Drift with the Argent Signaling Protocol
May 14, 2026Anantha SharmaMulti-Agent Large Language Model Systems Multi-Agent Systems
Latency-Quality Routing for Functionally Equivalent Tools in LLM Agents
May 14, 2026Kexin Chu, Dawei Xiang, Wei ZhangLarge Language Model Routing Large Language Model Calls
Distribution-Aware Algorithm Design with LLM Agents
May 13, 2026Saharsh Koganti, Priyadarsi Mishra, Pierfrancesco Beneventano +1Future Llm-Assisted Solver Development Large Language Model Agents
SPIN: Structural LLM Planning via Iterative Navigation for Industrial Tasks
May 13, 2026Yusuke Ozaki, Dhaval PatelLarge Language Model Planning Planning Methods
From Descriptive to Prescriptive: Uncover the Social Value Alignment of LLM-based Agents
May 13, 2026Jinxian Qu, Qingqing Gu, Teng Chen +1Llm-Based Agent Behavioral Alignment
Collider-Bench: Benchmarking AI Agents with Particle Physics Analysis Reproduction
May 13, 2026Darius A. Faroughy, Sofia Palacios Schweitzer, Ian Pang +2Agentic Benchmarks Large Language Model Agents
Good Agentic Friends Do Not Just Give Verbal Advice: They Can Update Your Weights
May 13, 2026Wenrui Bao, Huan Wang, Jian Wang +3Multi-Agent Large Language Model Weight
EvolveMem:Self-Evolving Memory Architecture via AutoResearch for LLM Agents
May 13, 2026Jiaqi Liu, Xinyu Ye, Peng Xia +4Large Language Model Agents Autoresearch
AgentTrap: Measuring Runtime Trust Failures in Third-Party Agent Skills
May 13, 2026Haomin Zhuang, Hanwen Xing, Yujun Zhou +5Malicious Code Large Language Model Agents
SkillOps: Managing LLM Agent Skill Libraries as Self-Maintaining Software Ecosystems
May 13, 2026Hongji Pu, Xinyuan Song, Liang ZhaoLarge Language Model Agents Skillaudit
FlowCompile: An Optimizing Compiler for Structured LLM Workflows
May 13, 2026Junyan Li, Zhang-Wei Hong, Maohao Shen +2Code Optimization Workflow Automation and Optimization
RealICU: Do LLM Agents Understand Long-Context ICU Data? A Benchmark Beyond Behavior Imitation
May 13, 2026Chengzhi Shen, Weixiang Shen, Tobias Susetzky +8Intensive Care Unit Patient Trajectories
R^2-Mem: Reflective Experience for Memory Search
May 13, 2026Xinyuan Wang, Wenyu Mao, Junkang Wu +2Agent Memory Search Agents
PersonalAI 2.0: Enhancing knowledge graph traversal/retrieval with planning mechanism for Personalized LLM Agents
May 13, 2026Mikhail Menschikov, Matvey Iskornev, Alexander Kharitonov +8Graph-Based Retrieval Augmented Generation Knowledge Graphs
Why We Need World Models for AGI: Where LLMs Fail and How World Models May Outperform
May 13, 2026Feisal Alaswad, Batoul Aljaddouh, Maher Alrahhal +2Latent World Models Efficient Latent Reasoning
Text2Score: Generating Sheet Music From Textual Prompts
May 13, 2026Keshav Bhandari, Sungkyun Chang, Abhinaba Roy +4Music Generation Sheet Music
GAGPO: Generalized Advantage Grouped Policy Optimization
May 13, 2026Siyuan Zhu, Chao Yu, Rongxin Yang +4Agentic Reinforcement-Learning Framework Group Relative Policy Optimization
No Attack Required: Semantic Fuzzing for Specification Violations in Agent Skills
May 13, 2026Ying Li, Hongbo Wen, Yanju Chen +3Fuzzing Llm-Based Agent
Embodied Multi-Agent Coordination by Aligning World Models Through Dialogue
May 13, 2026Vardhan Dongre, Dilek Hakkani-TürMulti-Agent Coordination Embodied Agents
Revisiting DAgger in the Era of LLM-Agents
May 13, 2026Changhao Li, Rushi Qiang, Jiawei Huang +4Large Language Model Agents Iterative Co-Training
Beyond Cooperative Simulators: Generating Realistic User Personas for Robust Evaluation of LLM Agents
May 13, 2026Harshita Chopra, Kshitish Ghate, Aylin Caliskan +3User Simulation Persona
Large Language Models for Agentic NetOps and AIOps: Architectures, Evaluation, and Safety
May 12, 2026Muhammad Bilal, Jon Crowcroft, Ruizhi Wang +2Artificial Intelligence Safety Multi-Agent Large Language Model Systems

May 19, 2026 · cs.GTJ/K move · Enter open · S save

PrefBench: Evaluating Zero-Shot LLM Agents in Hidden-Preference Personalized Pricing Negotiations

Yingjie Lei

University of Aberdeen

Personalized pricing negotiations are a challenging testbed for LLM agents because successful interaction does not guarantee profitable decision making. A seller may produce valid actions and close many deals while still pricing poorly when buyer willingness to pay and bargaining traits remain hidden. This paper presents PrefBench, a simulator-based benchmark for hidden-preference personalized pricing negotiations. Each episode pairs a simulated buyer with a fixed vehicle-customization bundle; the seller observes public persona descriptors, bundle information, and negotiation history, while latent buyer variables govern valuation, patience, counter-offer behavior, and walkaway decisions. PrefBench evaluates this setting through an LLM-facing state-summary protocol that constrains agents to return strict JSON actions under a fixed hidden-information boundary. We evaluate zero-shot LLM sellers against heuristic references over 7,500 episodes. The tested LLMs follow the protocol reliably and achieve deal rates above 0.99, but their seller-profit outcomes remain weak: the best LLM average profit is only slightly above the random baseline and far below a simple concession heuristic under the same episode stream. These results show that structured action compliance and agreement-seeking behavior can coexist with weak profit-sensitive bargaining. PrefBench provides a controlled benchmark for evaluating pricing-agent behavior under hidden buyer preferences.

Negotiation Agentic Commerce Prices Large Language Model Agents Model Preference Refusals

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