Language Model Post-Training

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Overview

Language model post-training studies how to turn a pretrained model into a more useful, reliable, or specialized system without training it from scratch. Common approaches include supervised fine-tuning on demonstrations, preference optimization such as DPO, reinforcement learning with human or verifiable rewards, and distillation from other models. Researchers apply these methods to tasks from mathematical reasoning and coding to translation, tool use, and domain-specific work, evaluating both task performance and qualities such as calibration, safety, and diversity. A central tension is that gains on targeted tasks can come with weaker generalization or loss of capabilities, and which methods work best often depends on the model, data, and evaluation setting.

Latest papers

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197 papers47 papers in the last four weeks, up 104% on the four weeks before. 0.3% of all new papers.

  1. Do Post-Training Algorithms Actually Differ? A Controlled Study Across Model Scales Uncovers Scale-Dependent Ranking Inversions

    Mar 19, 2026Xiaoyi LiLanguage Model Post-TrainingLLM Alignment

  2. Sabiá-4 Technical Report

    Mar 10, 2026Thiago Laitz, Thales Sales Almeida, Hugo Abonizio +6Portuguese Language ModelsLanguage Modeling

    Maritaca AI · Jusbrasil

  3. Post-Training with Policy Gradients: Optimality and the Base Model Barrier

    Mar 7, 2026Alireza Mousavi-Hosseini, Murat A. ErdogduLanguage Model Post-TrainingPolicy Gradient

    University of Toronto, Vector Institute. · University of Toronto, Vector Institute, and Numurho.

  4. From Prompting to Preference Optimization: A Comparative Study of LLM-based Automated Essay Scoring

    Mar 6, 2026Minh Hoang Nguyen, Vu Hoang Pham, Xuan Thanh Huynh +5Automated Essay ScoringLanguage Model Post-Training

    Faculty of Information Technology, University of Science, Ho Chi Minh City, Vietnam · Vietnam National University, Ho Chi Minh City, Vietnam

  5. Post-Training Language Models for Crosslingual Consistency

    Mar 4, 2026Tianyu Liu, Jirui Qi, Mrinmaya Sachan +3Cross-Lingual Consistency in Language ModelsLanguage Model Post-Training

    ETH Zürich · CLCG, University of Groningen · University of Amsterdam

  6. Tucano 2 Cool: Better Open Source LLMs for Portuguese

    Mar 3, 2026Nicholas Kluge Corrêa, Aniket Sen, Shiza Fatimah +4Portuguese Language ModelsLanguage Modeling

    Bonn-Aachen International Center for Information Technology (b-it) / CAISA Lab · Lamarr Institute for Machine Learning and Artificial Intelligence · Center for Science and Thought +2

  7. Theoretical Perspectives on Data Quality and Synergistic Effects in Pre- and Post-Training Reasoning Models

    Mar 1, 2026Adel Javanmard, Baharan Mirzasoleiman, Vahab MirrokniData Selection for Language Model Fine-TuningLLM Fine-Tuning

    University of Southern California · Google Research · University of California Los Angeles

  8. IAPO: Information-Aware Policy Optimization for Token-Efficient Reasoning

    Feb 22, 2026Yinhan He, Yaochen Zhu, Mingjia Shi +5Efficient Language Model ReasoningLanguage Model Post-Training

    University of Virginia, Charlottesville, VA, USA · LinkedIn Inc., Sunnyvale, CA, USA

  9. Operationalising the Superficial Alignment Hypothesis via Task Complexity

    Feb 17, 2026Tomás Vergara-Browne, Darshan Patil, Ivan Titov +3LLM AlignmentLanguage Model Post-Training

    Mila Quebec AI Institute · McGill University · Université de Montréal +4

  10. What Is Missing: Interpretable Ratings for Large Language Model Outputs

    Feb 17, 2026Nicholas Stranges, Yimin YangLLM EvaluationLanguage Model Post-Training

    Department of Electrical and Computer Engineering, Western University, Canada

  11. GRRM: Group Relative Reward Modeling for Machine Translation

    Feb 15, 2026Sen Yang, Shanbo Cheng, Lu Xu +2Reward ModelingRL for Language Models

    National Key Laboratory for Novel Software Technology, Nanjing University · Singapore University of Technology and Design

  12. LMSpell: Spell Correction with Pre-Trained Language Models

    Dec 5, 2025Akesh Gunathilake, Nadil Karunarathna, Tharusha Bandaranayake +3Low-Resource Language ProcessingLanguage Model Post-Training

    Department of Computer Science and Engineering, University of Moratuwa, Katubedda, 10400, Sri Lanka · School of Mathematical and Computational Sciences, Massey University, Auckland, 102904, New Zealand

  13. POPI: Personalizing LLMs via Optimized Natural Language Preference Inference

    Oct 17, 2025Yizhuo Chen, Xin Liu, Ruijie Wang +7LLM PersonalizationPersonalized Language Models

    University of Illinois Urbana-Champaign · Amazon · University of Notre Dame

  14. Verbalized Sampling: How to Mitigate Mode Collapse and Unlock LLM Diversity

    Oct 1, 2025Jiayi Zhang, Simon Yu, Derek Chong +4LLM PromptingModel Collapse

    Northeastern University · Stanford University · West Virginia University

  15. Agnostics: Learning to Code in Any Programming Language via Reinforcement with a Universal Learning Environment

    Aug 6, 2025Aleksander Boruch-Gruszecki, Yangtian Zi, Zixuan Wu +4RL for Code GenerationCode Generation

    1Northeastern University · University of Texas · 3Wellesley College

  16. BOW: Training Language Models to Reason Over Plausible Next Words

    Jun 16, 2025Ming Shen, Zhikun Xu, Jacob Dineen +2RL for Language Model ReasoningNext-Token Prediction

    Arizona State University

  17. LearNAT: Learning NL2SQL with AST-guided Task Decomposition for Large Language Models

    Apr 3, 2025Weibin Liao, Xin Gao, Tianyu Jia +6LLM PlanningRL for Language Model Reasoning

    School of Computer Science, Peking University · 2Key Laboratory of High Confidence Software Technologies, Ministry of Education · School of Computer Sciences, Beijing University of Posts and Telecommunications +5