Language Model Self-Improvement

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14 papers in the last four weeks, up 17% on the four weeks before. 0.1% of all new papers.

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Failure-Informed Image Self-Augmentation for Multimodal Large Language Model Self-Improvement
Aug 4, 2026Chunyang Jiang, Pingping Zhang, Yuzhi Zhao +9Synthetic Data Augmentation Data Augmentation
Hong Kong University of Science and Technology · City University of Hong Kong · Chinese University of Hong Kong
Self-Improving Large Language Models via Progressive Experience Evolution
Aug 3, 2026Shijie Ren, Xiting Wang, Meng Li +8RL for Language Model Reasoning Language Model Self-Improvement
Gaoling School of Artificial Intelligence, Renmin University of China · Weixin AI, Tencent Inc, China
SERPO: Self-Evolving Rubric Policy Optimization for Open-Ended Test-Time Reinforcement Learning
Jul 29, 2026Jianze Wang, Kunwang Zheng, Ying Liu +5Reinforcement Learning Test-Time RL
School of Artificial Intelligence and Automation, Huazhong University of Science and Technology · Alibaba Group · University of Science and Technology of China
DecoEvo: Score-Decoupled Co-Evolution of Solver and Rubric-Generator Skills in Text Space
Jul 28, 2026Jiangwang Chen, Zixin Song, Junlin Liu +10Large Language Model-Guided Optimization Language Model Self-Improvement
1Tsinghua University · 4Qwen Business Unit of Alibaba · University of Chinese Academy of Sciences +1
From RLVR to RLSVR: Task Transformation Induces Self-Verifiable Rewards for Open-Ended LLM Self-Improvement
Jul 26, 2026Qinsi Wang, Jing Shi, Huazheng Wang +8Self-Play RL Reinforcement Learning with Verifiable Rewards
Duke University · Adobe Inc. · Oregon State University +3
Learning from Synthetic Data without Model Collapse in Iterative Instruction Tuning
Jul 19, 2026Xiaonan Luo, Yue Huang, Kehan Guo +4Self-Training for Language Models Model Collapse
University of Notre Dame · Vanderbilt University · University of Pennsylvania
Cura 1T: Healthcare Foundation Model via Recursive Self-Improvement
Jul 15, 2026Haolin Chen, Leon Qi, Steve Brown +7Medical VLMs LLM Agent Training
actAVA AI Team
Consensus as Privileged Context for Label-Free Self-Distillation
Jul 15, 2026John Gkountouras, Josip Jukić, Ivan TitovSelf-Training for Language Models Language Model Distillation
1ILLC, University of Amsterdam · 2ILCC, University of Edinburgh
Self-Improving is Often Sudden: Enlightenment-style Finetuning for Large-Scale Models
Jul 15, 2026Jing-Xiao Liao, Tianwei Zhang, Yu-Hao Jiang +3LLM Fine-Tuning Language Model Self-Improvement
Frontier of Artificial Network Lab, Department of Data Science, City University of Hong Kong, Hong Kong SAR, China · The Shenzhen Institute of Artificial Intelligence and Robotics for Society, Shenzhen, China, The Chinese University of Hong Kong-Shenzhen, Shenzhen, China · School of Computer Science and Artificial Intelligence, Guangdong University of Education, Guangzhou 510303, China +1
Enhancing LLMs through human feedback: a journey towards self-improvement
Jul 13, 2026Tatiana Pelc, Gila Kamhi, Asaf Avrahamy +1Retrieval-Augmented Generation Human-in-the-Loop AI
1Intel Corporation
Hallucination Self-Play: Bootstrapping Reinforced Detector via Evolved Generator
Jul 8, 2026Shiping Yang, Shining Liang, Weihao Liu +4LLM Hallucination Detection Synthetic Data Generation for Language Models
Simon Fraser University · Microsoft · Work done during an internship at Microsoft +1
Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops
Jul 8, 2026Mingguang Chen, Licheng Wang, Bo QuLLM Self-Refinement Human-in-the-Loop Evaluation
University of California, Riverside (UCR) · AlphaAvatar · Illinois Institute of Technology (IIT)
From Application-Layer Simulation to Native Meta-Architecture: Structural Tension as an Endogenous Driver for Heterogeneous AI Evolution
Jul 7, 2026Heting MaoLLM Alignment Memory-Augmented Language Models
Shanghai Lixin University of Accounting and Finance
Self-Reference in Large Language Models: The Introspection Threshold for Recursive Self-Improvement
Jul 5, 2026Jiang Zhang, Bing Yuan, Qian ZhangLanguage Model Introspection Language Model Self-Improvement
School of Systems Science, Beijing Normal University · Swarma Research
Revisiting Chain-of-Thought Reasoning under Limited Supervision: Semi-supervised Chain-of-Thought Learning
Jul 1, 2026Hongyang He, Jiuming Liu, Victor SanchezSelf-Training for Language Models CoT Reasoning
University of Warwick · University of Cambridge
AutoTrainess: Teaching Language Models to Improve Language Models Autonomously
Jun 30, 2026Zhaojian Yu, Penghao Yin, Shuzheng Gao +3Tool-Augmented Language Model Agents LLM Tool Use
1Tsinghua University · 2The Chinese University of Hong Kong · 3Simple Agent Lab
On the Convergence of Self-Improving Online LLM Alignment
Jun 30, 2026Xudong Wu, Pangpang Liu, Vaneet Aggarwal +1LLM Alignment Optimization Convergence Analysis
The University of Hong Kong, Hong Kong SAR · Yale University, New Haven, CT, USA · Purdue University, West Lafayette, IN, USA
What Drives Interactive Improvement from Feedback?
Jun 29, 2026Bartłomiej Cupiał, Jan Łojek, Mikołaj Garstecki +3LLM Self-Refinement LLM Agent Evaluation
University of Warsaw · AKCES NCBR · Princeton University +2
DRIFT: Difficulty Routing Self-DIstillation with Rhythm-Gated Exploration and Success BuFfer Training
Jun 29, 2026Haisen Luo, Yiwei Liu, Haoning Wang +13Self-Training for Language Models RL for Language Model Reasoning
3Beike Language and Intelligence · 2ENS Paris-Saclay · 1Tsinghua University
Self-Improvement Can Self-Regress: The Rise-and-Collapse Failure Mode of LLM Self-Training
Jun 17, 2026Jianzhe LinRL for Code Generation Reinforcement Learning
MetaAI · *Work done at Meta
When Rules Learn: A Self-Evolving Agent for Legal Case Retrieval
Jun 15, 2026Mingxu Tao, Jiawei Hu, Xian Zhou +5Legal NLP Legal IR
Center of Information Research, AMS · 2Discipline and Technology Research Center for Large Model Intelligence Applications · 3Hebei University of Engineering
Integrating Reasoning and Generalization in Text-to-SQL via Self-Enhanced Fine-Tuning
Jun 14, 2026Feng Lyu, Jinfeng Cen, Sijing Duan +4Self-Training for Language Models LLM Fine-Tuning
Central South University · Tsinghua University · Nanjing University +1
From Chatbot to Digital Colleague: The Paradigm Shift Toward Persistent Autonomous AI
Jun 12, 2026Yongheng Zhang, Ziang Liu, Jiaxuan Zhu +17LLM Tool Use Long-Horizon LLM Agents
Tencent Youtu Lab · Tsinghua University · Sun Yat-sen University +2
Self-Evolving Visual Questioner
Jun 11, 2026Yijun Liang, Hengguang Zhou, Ming Li +3Visual Question Answering Language Model Self-Improvement
University of Maryland, College Park · University of California, Los Angeles · Peking University +2
A-Evolve-Training: Autonomous Post-Training of a 30B Model
Jun 9, 2026Zhan Shi, Bing He, Yisi Sang +2LLM Post-Training Language Model Self-Improvement
Amazon
INFUSER: Influence-Guided Self-Evolution Improves Reasoning
Jun 8, 2026Siyu Chen, Miao Lu, Beining Wu +7RL for Language Model Reasoning Group Relative Policy Optimization
Yale University · Stanford University · University of Chicago +2
More Yap Less Meaning: Uncovering Self-Improvement Behavior in SLMs
Jun 7, 2026Marina Igitkhanian, Erik ArakelyanLLM Self-Correction Test-Time Scaling
American University of Armenia · NVIDIA
When Languages Disagree: Self-Evolving Multilingual LLM Judges
Jun 6, 2026Xiyan Fu, Wei LuMultilingual Language Model Evaluation LLM-as-a-Judge
Nanyang Technological University
Teacher-Free Self-Training Amplifies but Does Not Compound: A Pass@ $K$ Crossover on a Free-Verifier Domain
Jun 5, 2026Igor Lima StrozziSelf-Training for Language Models Self-Training
Applied Mathematics Department Federal University of Rio de Janeiro
Self-Evolving Deep Research via Joint Generation and Evaluation
Jun 3, 2026Han Zhu, Chengkun Cai, Yuanfeng Song +3LLM Evaluation LLM Agent Training
1The Hong Kong University of Science and Technology · 2ByteDance, China · University College London

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Failure-Informed Image Self-Augmentation for Multimodal Large Language Model Self-Improvement

Chunyang Jiang, Pingping Zhang, Yuzhi Zhao, Wenao Ma+8

Hong Kong University of Science and Technology · City University of Hong Kong · Chinese University of Hong Kong

Synthetic Data Augmentation Data Augmentation Multimodal Large Language Models Language Model Self-Improvement

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Multimodal large language models (MLLMs) have achieved remarkable performance across vision-language tasks, but their progress depends heavily on large-scale, high-quality multimodal data that are costly to annotate. Self-augmentation offers a promising alternative by enabling models to expand their own training data without external supervision. However, existing MLLM self-augmentation methods are largely text-centric, while image augmentation remains underexplored and typically relies on generic or handcrafted transformations that are weakly aligned with the model's actual incapability. We propose Failure-informed Image Self-Augmentation (\textbf{FISA}), a framework for MLLM self-improvement that constructs augmented images from the model's own failure cases. Our method generates visually challenging yet answer-preserving image complications, verifies their utility through self-examination, and applies dual fidelity filtering to avoid semantic distortion. Experiments on visual question answering benchmarks show that the proposed method consistently improves performance across both in-distribution and out-of-distribution settings. Further experiments validate the compatibility of FISA with existing textual self-augmentation approaches, the superior data efficiency of the synthesized samples over generic image augmentation baselines, and the practical effectiveness of the proposed filtering strategy.

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