Design the Feedback, Not Just the Reward: Environments for Open-Ended Reinforcement Learning
cs.AI
Submitted: 2026-08-28
Updated: 2026-10-15
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Terminology
Sources
- Program Synthesis with Large Language Models
- Evaluating Large Language Models Trained on Code
- DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning
- Segment Policy Optimization: Effective Segment-Level Credit Assignment in RL for Large Language Models
- Where Hindsight Credit Can Reside: A Signed-Capacity View of Token Updates in RLVR
- Unlocking the conversion of Web Screenshots into HTML Code with the WebSight Dataset
- Proximal Policy Optimization Algorithms
- DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models
- Text2Grad: Reinforcement Learning from Natural Language Feedback
- DashArena: Benchmarking LLMs on Interactive Analytic Dashboard Generation
- Profile-Aware Maneuvering: A Dynamic Multi-Agent System for Robust GAIA Problem Solving by AWorld
- ArtifactsBench: Bridging the Visual-Interactive Gap in LLM Code Generation Evaluation
- DelTA: Discriminative Token Credit Assignment for Reinforcement Learning from Verifiable Rewards
- MiniAppBench: Evaluating the Shift from Text to Interactive HTML Responses in LLM-Powered Assistants
Related papers
- MAVEN-T: Reinforced Heterogeneous Distillation for Real-Time Multi-Agent Trajectory Prediction
- Model Discovery Agent: LLM-assisted Bayesian experiment design for data-efficient discovery of mechanistic world models
- Agents' Last Exam
- The Clinician's Veto: Navigating Trust, Liability, and Uncertainty in Autonomous AI Prescribing
- MindHelper: Closed-Loop Embodied Mental-State Reasoning for Precision Intervention
- Incumbent Advantage: Brand Bias and Cognitive Manipulation Dynamics in LLM Recommendation Systems