LLM Decision-Making

LLM: Large Language Model

This field examines how large language models make choices, use tools, ask for information, and act alone or with other agents, including in settings such as finance, healthcare, law, and strategic games. Researchers draw on behavioral economics and cognitive science, decision theory, reinforcement learning, and multi-agent methods, using controlled choice experiments and benchmarks that test constraints, calibration, fairness, and long-horizon performance. A central challenge is that correct answers or stated reasoning do not guarantee sound actions: choices can shift with framing, option order, context, and how evidence or costs are presented. Current work explores more reliable decision layers, explicit uncertainty and deferral, evidence-grounded rules, and tests that distinguish good outcomes from stable, human-aligned decision processes.

Latest papers

246 papers86 papers in the last four weeks, up 258% on the four weeks before. 0.5% of all new papers.

Understanding LLM Intervention Explanations in Multi-Party Human-Robot Interaction
Jun 28, 2026Micol Spitale, Massimiliano Nigro, Emily CrossExplainable Artificial Intelligence Spoken Dialogue Systems
Department of Electronics, Information and Bioengineering, Politecnico di Milano, Milan, Italy · GESS Department, ETH Zurich, Zurich, Switzerland
Deterministic Decisions for High-Stakes AI. A Zero-Egress Pipeline with the Deployability of RAG and the Accuracy of Machine Learning
Jun 28, 2026Craig AtkinsonAI in Education LLM Decision-Making
Verificate Pty Ltd, Sydney, Australia
Need or Reputation? Region, National Income, and Academic Status in LLM Gatekeeping Decisions
Jun 27, 2026Nouar AlDahoul, Hezerul Abdul Karim, Myles Joshua Toledo TanSocial Bias in Language Models LLM Decision-Making
Computer Science Department, New York University Abu Dhabi UAE · Centre for Image and Vision Computing, Faculty of Artificial Intelligence and Engineering Multimedia University Malaysia · Department of Electrical and Computer Engineering, Herbert Wertheim College of Engineering University of Florida USA
Measuring Behavior Portability in Large Language Models
Jun 22, 2026Tianjia Dong, Nadav Kunievsky, James A. EvansLLM Evaluation LLM Decision-Making
Knowledge Lab University of Chicago
Enhancing Decision-Making with Large Language Models through Multi-Agent Fictitious Play
Jun 17, 2026Leyang Shen, Yang Zhang, Xiaoyan Zhao +2Multi-Agent LLM Systems LLM Decision-Making
National University of Singapore Singapore
LLM Consumer Behavior Theory: Foundations of a Novel Research Field
Jun 16, 2026Manon Reusens, Sofie Goethals, David MartensHuman Preference Modeling LLM Decision-Making
Department of Engineering Management, University of Antwerp
Can LLMs Be CEOs? Benchmarking Strategic Resource Reallocation with Multi-Role Agent Simulation
Jun 16, 2026Yuyang Dai, Xueqing Peng, Lingfei Qian +1LLM Agent Evaluation AI Agent Benchmarks
1MBZUAI · 2Yale University
RetailBench: Benchmarking long horizon reasoning and coherent decision making of LLM agents in realistic retail environments
Jun 14, 2026Linghua Zhang, Jun Wang, Jingtong Wu +1Long-Horizon Agent Evaluation AI Agent Benchmarks
Ant Group · City University of Hong Kong
Knowing When to Ask: Self-Gated Clarification for Hierarchical Language Agents
Jun 9, 2026Aijing Gao, Yiming Kang, Mengdie Flora Wang +1Hierarchical Classification LLM Decision-Making
Amazon Web Services
Superficial Beliefs in LLM Decision-Making
Jun 9, 2026Gabriel Freedman, Francesca ToniLLM Decision-Making Metacognition in Language Models
Department of Computing Imperial College London
Trace2Policy: From Expert Behavior Traces to Self-Evolving Decision Agents
Jun 9, 2026Junli Zha, Jinbo Wang, Chao Zhou +1LLM Decision-Making Iterative Refinement
SF Express
To Nuke or Not to Nuke: LLMs' (Missing) Ethical Reasoning and Actions in a High-Stakes Decision-Making Simulation
Jun 6, 2026John Chen, Sihan Cheng, Can Gurkan +1Moral Reasoning in Language Models LLM Agent Evaluation
University of Arizona, Tucson, AZ, USA · Northwestern University, Evanston, IL, USA
Online Pandora's Box for Contextual LLM Cascading
Jun 5, 2026Alexandre Belloni, Yan Chen, Yehua WeiLLM Decision-Making LLM Routing
The Fuqua School of Business, Duke University
PandaAI: A Practical Agent CQ2 for Neuro-symbolic Data Analysis And Integrated Decision-Making in Quantitative Finance
Jun 5, 2026Yuqi Li, Siyuan Liu, Bingjun LiuQuantitative Finance LLM Decision-Making
Panda AI
An Infectious Disease Spread Simulation Based on Large Language Model Decision Making
Jun 4, 2026Yonchanok Khaokaew, Ruochen Kong, Andreas Zufle +6Human Behavior Simulation Agent-Based Modeling
Computer Science and Engineering Faculty of Engineering The University of New South Wales Sydney, NSW, Australia · King Mongkut’s University of Technology North Bangkok (KMUTNB) · Department of Computer Science Emory University Atlanta, Georgia, USA +5
Probing Outcome-Level Resemblance and Mechanism-Level Alignment in LLM Risk Decisions: Evidence from the St. Petersburg Game
Jun 3, 2026Chensong Huang, Changyu Chen, Chenwei Lin +3LLM Alignment LLM Decision-Making
Fudan University · University of Rochester
Can I Take Another Dose? DoseBench: Evaluating LLM Decision-Making in OTC Dosing QA
Jun 2, 2026Maroof Kousar, Jinsung Han, Mohit Chandra +2Temporal Reasoning Medical QA
Illinois Institute of Technology, Chicago, IL, USA
Auditing Asset-Specific Preferences in Financial Large Language Models: Evidence from Bitcoin Representations and Portfolio Allocation
Jun 1, 2026Wenbin WuLLM Auditing LLM Decision-Making
Cambridge Centre for Alternative Finance, University of Cambridge
Do Gender Cues Affect LLM Value Trade-offs? Evidence from a Controlled Decision Benchmark
Jun 1, 2026Yangyang Liu, Dong Yu, Pengyuan LiuGender Bias in Language Models Moral Reasoning in Language Models
Beijing Language and Culture University
Adversarial Feeds Steer LLM Agent Decisions Against Their Defaults
May 30, 2026Rana Muhammad UsmanAdversarial Attacks on LLMs LLM Agent Evaluation
Independent Researcher
ForeSci: Evaluating LLM Agents for Forward-Looking AI Research Judgment
May 30, 2026Qiuyu Tian, Haojie Yin, Yingce Xia +2LLM Agent Evaluation AI Agent Benchmarks
1Southeast University, Nanjing, China · 3Duke Kunshan University, Kunshan, China · 2Beijing Zhongguancun Academy, Beijing, China
Doing What They Say, Not What They Reason: Locating the Faithfulness Gap in LLM Agents
May 30, 2026Yufeng WangAI Agent Reliability LLM Agent Evaluation
What a One-Hour Interview Does Not Tell an LLM About You: Interviews Elicit Traits, Not Decision Policies
May 28, 2026Ruoxi Su, Yuhan Liu, Jingyu HuLLM Grounding Human Behavior Simulation
University of Cambridge
CyberJurors: A Multi-Agent Simulation Task for E-Commerce Disputes Verdict
May 27, 2026Yanhui Sun, Wu Liu, Haifeng Ming +3Multimodal Reasoning LLM Decision-Making
School of Information Science and Technology, University of Science and Technology of China, Hefei, China.
Framing Matters: Addressing Framing Sensitivity in Decision-Making through Behaviorally-Grounded Value Alignment
May 27, 2026Seojin Hwang, Minju Kim, Junhyuk Choi +2LLM Alignment Framing Effects in Language Models
Chung-Ang University, Seoul, Korea
PortBench: A Correlation-Aware, Full-Pipeline Benchmark for LLM-Driven Portfolio Management
May 27, 2026Yuxuan Zhao, Sijia Chen, Ningxin SuLLM Evaluation Quantitative Finance
Yantai Research Institute of Harbin Engineering University · The Hong Kong University of Science and Technology (Guangzhou)
Knowing but Not Showing: LLMs Recognize Ambiguity but Rarely Ask Clarifying Questions
May 24, 2026Jinyan Su, Claire CardieLLM Evaluation Clarification Question Generation
1Cornell University
Not Yet: Humans Outperform LLMs in a Colonel Blotto Tournament
May 21, 2026Dmitry Dagaev, Egor Ivanov, Petr Parshakov +2Game-Playing Agents Game Theory
HSE University · New Economic School · Central Economic Mathematical Institute, Russian Academy of Sciences +3
Mechanical Enforcement for LLM Governance:Evidence of Governance-Task Decoupling in Financial Decision Systems
May 14, 2026José Manuel de la Chica Rodríguez, Carlos Martí-GonzálezLLM Auditing LLM Safety
1Santander AI Lab, Grupo Santander
Learning Transferable Latent User Preferences for Human-Aligned Decision Making
May 12, 2026Alina Hyk, Sandhya SaisubramanianLLM Alignment LLM Decision-Making
Oregon State University

Jun 28, 2026J/K move · Enter open · S save

Understanding LLM Intervention Explanations in Multi-Party Human-Robot Interaction

Micol Spitale, Massimiliano Nigro, Emily Cross

Department of Electronics, Information and Bioengineering, Politecnico di Milano, Milan, Italy · GESS Department, ETH Zurich, Zurich, Switzerland

Explainable Artificial Intelligence Spoken Dialogue Systems LLM Decision-Making Human-Robot Interaction

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Large Language Models (LLMs) are increasingly embedded in social robots to support natural group interactions, yet their role in complex multi-party settings remains underexplored. In particular, it is unclear how LLM-driven robots decide when and why to intervene in group conversations. This paper investigates the intervention explanations generated by an LLM-based orchestrator in a multi-party interaction involving three human participants and two robots. We conducted a between-subjects study with 24 groups (66 university students), comparing a homogeneous condition (two robots with the same role, i.e., a mover) and a heterogeneous condition (two robots with different roles, i.e., a mover and an opposer). At each conversational turn, the LLM orchestrator decided whether to intervene and generated a textual explanation of its decision. We performed a thematic analysis of 610 intervention explanations, identifying five recurring themes. Results show that explanations are facilitation-oriented, emphasizing agreement, participation, and interaction flow. While patterns remain stable across conditions, role differentiation emerges: the mover supports coordination, whereas the opposer drives goal-oriented interventions. These findings contribute to explainable AI by characterizing how LLM-driven systems justify intervention decisions in real-time, multi-party human-robot interaction.