Pairwise Preference Evaluation

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A Finite Time Analysis of Thompson Sampling for Bayesian Optimization with Preferential Feedback
Apr 27, 2026Joseph Lazzaro, Davide Buffelli, Da-shan Shiu +1Thompson Sampling Pairwise Preference Evaluation
Imperial College London · MediaTek Research
Learning from Noisy Preferences: A Semi-Supervised Learning Approach to Direct Preference Optimization
Apr 27, 2026Xinxin Liu, Ming Li, Zonglin Lyu +2Pairwise Preference Learning Diffusion Model Alignment
University of Central Florida
Preferences of a Voice-First Nation: Large-Scale Pairwise Evaluation and Preference Analysis for TTS in Indian Languages
Apr 23, 2026Srija Anand, Ashwin Sankar, Ishvinder Sethi +10Pairwise Preference Learning Human Preference Evaluation
Indian Institute of Technology Madras, India · AI4Bharat, India · Josh Talks, India
SpeechParaling-Bench: A Comprehensive Benchmark for Paralinguistic-Aware Speech Generation
Apr 22, 2026Ruohan Liu, Shukang Yin, Tao Wang +6Audio-Language Model Evaluation LLM Evaluation
1Nanjing University · 2Xiaomi
Relational Preference Encoding in Looped Transformer Internal States
Apr 10, 2026Jan KirinPairwise Preference Learning Reward Modeling
Mediocrity is the key for LLM as a Judge Anchor Selection
Mar 17, 2026Shachar Don-Yehiya, Asaf Yehudai, Leshem Choshen +1LLM-as-a-Judge Pairwise Preference Evaluation
1The Hebrew University of Jerusalem · 2IBM Research · 3MIT +1
SpreadsheetArena: Decomposing Preference in LLM Generation of Spreadsheet Workbooks
Feb 16, 2026Srivatsa Kundurthy, Clara Na, Michael Handley +5LLM Evaluation Language Model Generation Evaluation
Longitude Labs Inc., New York, NY · Cornell University, Ithaca, NY · Carnegie Mellon University, Pittsburgh, PA +1
Dropping Just a Handful of Preferences Can Change Top Large Language Model Rankings
Aug 16, 2025Jenny Y. Huang, Yunyi Shen, Dennis Wei +1Pairwise Preference Learning LLM Evaluation
Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology · MIT-IBM Watson AI Lab · IBM Research
Pairwise Comparisons without Stochastic Transitivity: Model, Theory and Applications
Jan 13, 2025Sze Ming Lee, Yunxiao ChenPairwise Comparison Pairwise Preference Evaluation
Department of Statistics · London School of Economics and Political Science · London WC2A 2AE, United Kingdom
Edu-QuRating: Multi-Dimensional Educational Data Curation with Distilled Pairwise Judgements
Date pendingOliver G. B. Garrod, Robin A. A. Ince, Meng Liu +6Language Model Pretraining Pairwise Preference Learning
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A Finite Time Analysis of Thompson Sampling for Bayesian Optimization with Preferential Feedback

Joseph Lazzaro, Davide Buffelli, Da-shan Shiu, Sattar Vakili

Imperial College London · MediaTek Research

Thompson Sampling Pairwise Preference Evaluation Bayesian Optimization

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Preference feedback, in the form of pairwise comparisons rather than scalar scores, has seen increasing use in applications such as human-, laboratory-, and expert-in-the-loop design, as well as scientific discovery. We propose a Thompson Sampling (TS) approach to Bayesian optimization with preferential feedback that models comparisons using a monotone link on latent utility differences and leverages the dueling kernel induced by a base kernel. We provide a finite-time analysis showing that the performance of the proposed method matches that of standard TS for conventional Bayesian optimization with scalar feedback. The analysis exploits the anchor invariance of TS for challenger selection and introduces a double-TS pairing variant. We also demonstrate the performance of the method on both synthetic and real-world examples.

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