RewardHarness: Self-Evolving Agentic Post-Training
cs.AI, cs.CL, cs.CV, cs.LG
Submitted: 2026-05-09
Updated: 2026-10-12
Project page: https://rewardharness.com
Terminology
Sources
- BLIP3o-NEXT: Next Frontier of Native Image Generation
- Self-Play Fine-Tuning Converts Weak Language Models to Strong Language Models
- ReTool: Reinforcement Learning for Strategic Tool Use in LLMs
- OneReward: Unified Mask-Guided Image Generation via Multi-Task Human Preference Learning
- VideoScore2: Think before You Score in Generative Video Evaluation
- GenAI Arena: An Open Evaluation Platform for Generative Models
- VerlTool: Towards Holistic Agentic Reinforcement Learning with Tool Use
- Uniworld-V2: Reinforce Image Editing with Diffusion Negative-aware Finetuning and MLLM Implicit Feedback
- Agent0-VL: Exploring Self-Evolving Agent for Tool-Integrated Vision-Language Reasoning
- SimpleMem: Efficient Lifelong Memory for LLM Agents
- Improving Video Generation with Human Feedback
- EditScore: Unlocking Online RL for Image Editing via High-Fidelity Reward Modeling
- Gorilla: Large Language Model Connected with Massive APIs
- SCOPE: Prompt Evolution for Enhancing Agent Effectiveness
- ToolLLM: Facilitating Large Language Models to Master 16000+ Real-world APIs
- EvolveCoder: Evolving Test Cases via Adversarial Verification for Code Reinforcement Learning
- ImagenWorld: Stress-Testing Image Generation Models with Explainable Human Evaluation on Open-ended Real-World Tasks
- WorldPM: Scaling Human Preference Modeling
- Voyager: An Open-Ended Embodied Agent with Large Language Models
- Unified Reward Model for Multimodal Understanding and Generation
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