ICLR 2026PastOther
ICLR 2026 Workshop on AI with Recursive Self-Improvement
ICLR 2026 Workshop RSI
- Submission deadline
- Feb 11, 2026, 11:00 UTCOpenReview-synced 2026-02-11 11:00 UTC (as of 2026-06-23) — extensions on OpenReview are applied automatically; verify on the website.
- Submission portal
- OpenReview
- Notes
- Topics were auto-suggested and may be imprecise — edits welcome.
Accepted papers (110)
Fetched from OpenReview (v2) on 2026-06-10.
A Framework for Prompt Optimization and Translation Across Foundation Models
A Task-Centric Theory for Iterative Self-Improvement with Easy-to-Hard Curricula
ACE: Self-Evolving LLM Coding Framework Adversarial Unit Test Generation and Preference Optimization
Actor-Curator: Scalable Policy-driven Curriculum Learning for RL Post-Training
Adaptive Decoding via Test-Time Policy Learning for Self-Improving Generation
Adaptive Meta-Curriculum for Test-Time Self-Improvement
Agent0-VL: Exploring Self-Evolving Agent for Tool-Integrated Vision-Language Reasoning
Agent0: Unleashing Self-Evolving Agents from Zero Data via Tool-Integrated Reasoning
Agentic Context Engineering: Evolving Contexts for Self-Improving Language Models
Aligned but Stereotypical? Understanding and Mitigating Social Bias in LLM-Driven Text-to-Image Models
AlphaApollo: A System for Deep Agentic Reasoning
Anchored Self-Play for Code Repair
AUTOHARNESS: IMPROVING LLM AGENTS BY AUTOMATICALLY SYNTHESIZING A CODE HARNESS
Beyond Solving: A Closer Look at LLMs as Solution Verifiers
Build, Judge, Optimize: A Blueprint for Continuous Improvement of Multi-Agent Consumer Assistants
Can Current Language Models Close the Discovery to Application Loop?
Can Language Models Discover Scaling Laws?
CausalEvolve: Towards Open-Ended Discovery with Causal Scratchpad
CircuitBuilder: From Polynomials to Circuits via Reinforcement Learning
Compute as Teacher: Turning Inference Compute Into Reference-Free Supervision
Constructive Distortion: Improving MLLMs with Attention-Guided Image Warping
Contextual Drag: How Errors in the Context Affect LLM Reasoning
Contrastive Self-Refinement for Low-Cost Adaptation in Real-World Text-to-SQL
Correct Reasoning Paths Visit Shared Decision Pivots
CoT-Seg: Rethinking Segmentation with Chain-of-Thought Reasoning and Self-Correction
Cross-Family Speculative Prefill: Training-Free Long-Context Compression with Small Draft Models
Depth vs Recursion: Outperforming Transformers in Jigsaw Reconstruction
Differentiable Evolutionary Reinforcement Learning
Discover the distinguishing and effective reasoning patterns among LLMs via an LLM
Do Depth-Grown Models Overcome the Curse of Depth? An In-Depth Analysis
Duel-Evolve: Reward-Free Test-Time Scaling via LLM Self-Preferences
Dynamic Noise Preference Optimization: Self-Improvement of Large Language Models with Self-Synthetic Data
Emergent temporal abstractions in autoregressive models enable hierarchical reinforcement learning
Escaping Model Collapse via Synthetic Data Verification: Near-term Improvements and Long-term Convergence
ESDAE: Evaluating Synthetic Data for Agent Evaluation
Evaluating AGENTS.md: Are Repository-Level Context Files Helpful for Coding Agents?
Federated Agent Reinforcement Learning
Federation over Text
Feedback Descent: Open-Ended Text Optimization via Pairwise Comparison
From Growing to Looping: A Unified View of Iterative Computation in LLMs
GASP: Guided Asymmetric Self-Play For Coding LLMs
Generative Recursive Reasoning Models
Improved Iterative Refinement for Chart-to-Code Generation via Structured Instruction
In-Context Adaptation
Inference-Time Scaling in Diffusion Models through Iterative Partial Refinement
Intelligent Robot Manipulation Requires Self-Directed Learning
Interestingness as an Inductive Heuristic for Future Compression Progress
Just Enough Learning: GRPO-Guided Controllers for Hyperparameter Sweeps
Knowledge is Not Enough: Injecting RL Skills for Continual Adaptation
Lang-PINN: From Language to Physics-Informed Neural Networks via a Multi-Agent Framework
Language Self-Play For Data-Free Training
Language-Guided Expertise Evolution for Protein Optimization
Learning to Continually Learn via Meta-learning Agentic Memory Designs
Learning to Evolve: Scaling Open-Ended Discovery with Relative-Progress RL
Learning What to Learn: Curriculum Curation for Test-Time Agent Learning
Leveraging Suboptimal and Noisy Trajectories for Goal-Conditional Offline RL
LLM-FE: Automated Feature Engineering for Tabular Data with LLMs as Evolutionary Optimizers
Log-Augmented Generation: Scaling Test-Time Reasoning with Reusable Computation
MAPPA: Scaling Multiagent Systems with Process Rewards
MimicAgent: Learning Quadruped Skills via Text-to-Trajectory Generation
OMEGA: Optimizing Machine learning by Evaluating Generated Algorithms
One-Step Video Depth Estimation via Self-Distillation
Orthogonal Gradient Projection for Continual LLM Unlearning
POLARIS: A GODEL AGENT FRAMEWORK FOR SMALL LANGUAGE MODELS THROUGH EXPERIENCE ABSTRACTED POLICY REPAIR
PostTrainBench: Can LLM Agents Automate LLM Post-Training?
Presenting a Paper is an Art: Self-Improvement Aesthetic Agents for Academic Presentations
Real-Time Procedural Learning From Experience for AI Agents
Reasoning as Gradient: Scaling MLE Agents Beyond Tree Search
Reasoning Cache: Learning to Extrapolate to Long Lengths via Short-Length RL
Reasoning Within the Mind: Dynamic Multimodal Interleaving in Latent Space
Reference-Guided Machine Unlearning
Refining Large Language Models with Self-Generated Data Through Iterative Training
Residual Off-Policy RL for Finetuning Behavior Cloning Policies
Rethinking Machine Unlearning: Models Designed to Forget via Key Deletion
Reward Hacking in Self-Improving Code Agents
RFTF: Reinforcement Fine-tuning for Vision-language-action Models with Temporal Feedback
SAGE: Self-play Adversarial Games Enhance Large Language Model Reasoning Capabilities
SAHOO: Safeguarded Alignment for High-Order Optimization Objectives in Recursive Self-Improvement
Self-Adapting Agents for Automating Research Coding Workflows
Self-CriTeach: LLM Self-Teaching and Self-Critiquing for Improving Robotic Planning via Automated Domain Generation
Self-EvolveRec: Self-Evolving Recommender Systems with LLM-based Directional Feedback
Self-Evolving Language Models through Co-evolved Discriminative Rubrics
Self-Improvement via Fast Tree-search
Self-Improving Clinical Reasoning via Textual Gradients
Self-Improving Vision-Language-Action Models with Data Generation via Residual RL
Self-Improving VLM Judges Without Human Annotations
Shape of Thought: When Distribution Matters More than Correctness in Reasoning Tasks
Simple Baselines are Competitive with Code Evolution
SimpleMem: Efficient Lifelong Memory for LLM Agents
SkillRL: Evolving Agents via Recursive Skill-Augmented Reinforcement Learning
Soft Mellowmax Monte Carlo Planning
Structure Enables Effective Self-Localization of Errors in LLMs
TamperBench: A Systematic Framework to Stress-Test LLM Safety Under Fine-Tuning and Tampering
TangramSR: A Benchmark for Recursive Self-Improvement In Continuous Geometric Reasoning
Teaching Models to Teach Themselves: Reasoning at the Edge of Learnability
Test-Time Adaptation via Many-Shot Prompting: Benefits, Limits, and Pitfalls
Test-Time Meta-Adaptation with Self-Synthesis
Test-Time Self-Distillation
TextBO: Bayesian Optimization in Language Space for Eval-Efficient Self-Improving AI
Theory-Driven Modeling and LLM-Guided Evolution for Power System Scheduling
Tiny Autoregressive Recursive Models
Towards Execution-Grounded Automated AI Research
Unlocking Intrinsic Self-Reflection for LLM Preference Policy Optimization
Unrolled Policy Iteration for Tiny Recursive Models
Verifying the Verifiers: Failure Attribution for Agentic Benchmark Diagnostics and Training Data Curation
VerlTool: Towards Holistic Agentic Reinforcement Learning with Tool Use
Vision-Guided Iterative Refinement for Frontend Code Generation
VLAW: Iterative Co-Improvement of Vision-Language-Action Policy and World Model
World Action Verifier: Self-Improving World Models via Forward-Inverse Asymmetry
Your Self-Play Algorithm is Secretly an Adversarial Imitator: Understanding LLM Self-Play through the Lens of Imitation Learning