Overview

Language model ensembles study how to combine multiple models so their complementary strengths can improve answers, predictions, or evaluations. Common approaches include majority and weighted voting, learned stacking and calibration, query-level routing, logit fusion, and deliberation or verification across agents. These methods are tested on tasks such as mathematical reasoning, question answering, forecasting, text classification, and evaluation by LLM judges, with attention to accuracy, uncertainty, and inference cost. A central tension is that ensembles help most when models make different errors, yet correlated failures are common and adding models or computation does not reliably outperform the strongest individual model.

Latest papers

CardsList

137 papers17 papers in the last four weeks, level with the four weeks before. 0.1% of all new papers.

  1. COGNAC at SemEval-2026 Task 5: LLM Ensembles for Human-Level Word Sense Plausibility Rating in Challenging Narratives

    Mar 16, 2026Azwad Anjum Islam, Tisa Islam EranaLanguage Model Ensembles

  2. CSE-UOI at SemEval-2026 Task 6: A Two-Stage Heterogeneous Ensemble with Deliberative Complexity Gating for Political Evasion Detection

    Mar 12, 2026Christos Tzouvaras, Konstantinos Skianis, Athanasios VoulodimosLanguage Model Ensembles

  3. QuadAI at SemEval-2026 Task 3: Ensemble Learning of Hybrid RoBERTa and LLMs for Dimensional Aspect-Based Sentiment Analysis

    Mar 8, 2026A. J. W. de Vink, Filippos Karolos Ventirozos, Natalia Amat-Lefort +1Aspect-Based Sentiment AnalysisLanguage Model Ensembles

  4. Wisdom of the AI Crowd (AI-CROWD) for Ground Truth Approximation in Content Analysis: A Research Protocol & Validation Using Eleven Large Language Models

    Mar 6, 2026Luis de-Marcos, Manuel Goyanes, Adrián Domínguez-DíazLLM-Assisted AnnotationLanguage Model Ensembles

  5. Ensembling Language Models with Sequential Monte Carlo

    Mar 5, 2026Robin Shing Moon Chan, Tianyu Liu, Samuel Kiegeland +5Language Model EnsemblesLanguage Model Decoding

  6. LoRA-MME: Multi-Model Ensemble of LoRA-Tuned Encoders for Code Comment Classification

    Mar 4, 2026Md Akib Haider, Ahsan Bulbul, Nafis Fuad Shahid +2Text ClassificationLanguage Model Ensembles

  7. Trade-offs in Ensembling, Merging and Routing Among Parameter-Efficient Experts

    Mar 3, 2026Sanae Lotfi, Lucas Caccia, Alessandro Sordoni +2Language Model EnsemblesLanguage Model Merging

  8. FinAnchor: Aligned Multi-Model Representations for Financial Prediction

    Feb 24, 2026Zirui He, Huopu Zhang, Yanguang Liu +2Financial ForecastingLanguage Model Ensembles

  9. StackingNet: Collective Inference Across Independent AI Foundation Models

    Feb 14, 2026Siyang Li, Chenhao Liu, Dongrui Wu +2Ensemble LearningLanguage Model Ensembles

  10. CARE: Confounder-Aware Aggregation for Reliable LLM Evaluation

    Feb 9, 2026Jitian Zhao, Changho Shin, Tzu-Heng Huang +2LLM EvaluationLLM-as-a-Judge

  11. Human Values in a Single Sentence: Moral Presence, Hierarchies, and Transformer Ensembles on the Schwartz Continuum

    Jan 20, 2026Víctor Yeste, Paolo RossoMulti-Label ClassificationLanguage Model Ensembles

  12. AdaFuse: Adaptive Ensemble Decoding with Test-Time Scaling for LLMs

    Jan 9, 2026Chengming Cui, Tianxin Wei, Ziyi Chen +6Language Model DecodingTest-Time Scaling

  13. FusionFactory: Fusing LLM Capabilities with Multi-LLM Log Data

    Jul 14, 2025Tao Feng, Haozhen Zhang, Zijie Lei +5LLM EvaluationLLM Routing

  14. Ensemble Learning for Large Language Models in Text and Code Generation: A Survey

    Mar 13, 2025Mari Ashiga, Wei Jie, Fan Wu +5Mixture-of-Experts Language ModelsLanguage Model Ensembles

  15. Dynamic Optimizations of LLM Ensembles with Two-Stage Reinforcement Learning Agents

    Feb 6, 2025Selim Furkan Tekin, Gaowen Liu, Ramana Rao Kompella +1Multi-Agent LLM SystemsLanguage Model Ensembles

  16. Tuning Language Models by Mixture-of-Depths Ensemble

    Oct 16, 2024Haoyan Luo, Lucia SpeciaLLM Fine-TuningLanguage Model Ensembles