Dueling Bandits

Follow this topic Ask about this topic

Latest papers

14 papers3 papers in the last four weeks, with none the four weeks before. 0.0% of all new papers.

Bridging Exploration and Persona: Information-Directed Dueling for Test-Time Agent Personalization
Oct 17, 2026Jie Mao, Pingchen Lu, Xiangyi Wang +4LLM Personalization User Preference Modeling
The Chinese University of Hong Kong, Shenzhen · University of Copenhagen · City University of Hong Kong +1
Replicable Dueling Bandits
Oct 14, 2026Rohan Deb, Aadirupa Saha, Udaya Ghai +2Dueling Bandits Multi-Armed Bandits
University of Illinois, Urbana Champaign · University of Illinois, Chicago · Amazon +1
Cost-Aware Best-LLM Identification using Dueling Feedback
Sep 24, 2026Sarvesh Gharat, Nikhil Karamchandani, Jayakrishnan NairDueling Bandits Best-Arm Identification
Centre for Machine Intelligence and Data Science (C-MInDS) Indian Institute of Technology Bombay · Department of Electrical Engineering Indian Institute of Technology Bombay
Optimal Top- $k$ Identification from Pairwise Comparisons
Jul 9, 2026Motti Goldberger, Nils RudiPairwise Preference Learning Multi-Armed Bandits
Yale University, New Haven, CT, USA.
Tree-Guided Identify-Then-Exploit: A Unified Framework of Best Arm Identification and Regret Minimization for Dueling Bandits
Jun 1, 2026Pu Wang, Yao-Xiang DingMulti-Armed Bandits Best-Arm Identification
State Key Lab of CAD&CG, Zhejiang University
CUPID in the Model Zoo: Online Matchmaking for Selecting Your Dream LLM
May 30, 2026Son Nguyen, Xinyuan Liu, Ransalu SenanayakeMulti-Armed Bandits Dueling Bandits
School of Computing and Augmented Intelligence, Arizona State University, Tempe, United States of America
Near-Optimal Last-Iterate Convergence for Zero-Sum Games with Bandit Feedback and Opponent Actions
May 10, 2026Soumita Hait, Ping Li, Haipeng Luo +1Last-Iterate Convergence Imperfect-Information Games
University of Southern California · Shanghai University of Finance and Economics · University of Iowa
Best Arm Identification in Generalized Linear Bandits via Hybrid Feedback
May 7, 2026Qirun Zeng, Xuchuang Wang, Jiayi Shen +3Multi-Armed Bandits Best-Arm Identification
Department of Computer Science City University of Hong Kong, Hong Kong SAR, China · Manning College of Information & Computer Science University of Massachusetts Amherst, Amherst, MA, USA · School of Management University of Science and Technology of China, Hefei, Anhui, China +3
Multi-User Dueling Bandits: A Fair Approach using Nash Social Welfare
May 3, 2026Maheed H. Ahmed, Mahsa GhasemiPairwise Preference Learning Multi-Armed Bandits
Electrical and Computer Engineering Purdue University
Analysis of Search Heuristics in the Multi-Armed Bandit Setting
Apr 9, 2026Jasmin Brandt, Barbara Hammer, Timo Kötzing +1Dueling Bandits Multi-Armed Bandits
University of Bielefeld Bielefeld, Germany · Hasso Plattner Institute University of Potsdam Potsdam, Germany
Lipschitz Dueling Bandits over Continuous Action Spaces
Apr 1, 2026Mudit Sharma, Shweta Jain, Vaneet Aggarwal +1Lipschitz Bandits Dueling Bandits
Indian Institute of Technology Ropar · Purdue University · Indian Institute of Technology Hyderabad
Best-of-Both-Worlds Multi-Dueling Bandits: Unified Algorithms for Stochastic and Adversarial Preferences under Condorcet and Borda Objectives
Mar 19, 2026S Akash, Pratik Gajane, Jawar SinghDueling Bandits Multi-Armed Bandits
Indian Institute of Technology Patna, India · University of Orléans, France
The Sampling Complexity of Condorcet Winner Identification in Dueling Bandits
Mar 16, 2026El Mehdi Saad, Victor Thuot, Nicolas VerzelenDueling Bandits Best-Arm Identification
CC-UM6P-Rabat · INRAE, MISTEA, Institut Agro, Univ. Montpellier Montpellier, France · MISTEA +1
PARWiS: Winner determination under shoestring budgets using active pairwise comparisons
Mar 1, 2026Shailendra BhandariDueling Bandits Pairwise Preference Learning
Department of Computer Science OsloMet– Oslo Metropolitan University Oslo, Norway

Oct 17, 2026J/K move · Enter open · S save

Bridging Exploration and Persona: Information-Directed Dueling for Test-Time Agent Personalization

Jie Mao, Pingchen Lu, Xiangyi Wang, Hengquan Huang+3

The Chinese University of Hong Kong, Shenzhen · University of Copenhagen · City University of Hong Kong+1

LLM Personalization User Preference Modeling Dueling Bandits Pairwise Preference Learning

Open paper AskPDF arXiv

Effective test-time personalization requires LLM agents to adapt to query-dependent user preferences from lightweight interaction. We study persona selection with binary comparisons between candidate responses as the online signal. We present ID-TAP, a scalable, IDS-inspired neural dueling-bandit framework for large discrete persona spaces. ID-TAP combines a query-conditioned neural utility model with a lightweight Bradley-Terry explorer, and transfers comparison evidence across related queries through similarity-weighted warm starts. The neural model shares statistical strength across queries while preserving query-specific scores, and efficient BT updates score hypothetical challengers. Across seven user-conditioned generation benchmarks under reference- and model-based preference simulators, ID-TAP achieves the strongest aggregate performance among the evaluated baselines within a fixed ten-round comparison budget. These results support information-directed challenger selection as an effective design for test-time persona adaptation.