9 papers
NeoHorse-1: Towards Recursive Self-Improvement via Agentic Post-Training with Routing Harness
NeoHorse Team, Guoliang Cao, Guohao Dai +34
Recursive self-improvement (RSI) requires a concrete mechanism through which an AI system observes its capabilities and converts that evidence into the next round of learning. We p…
Agentic Routing: The Harness-Native Data Flywheel
Xinchen Liu, Hang Zhou, Yingjie Zong +12
Large language model agents are increasingly executed not by a single model call, but by an execution harness that manages observation, context, control, action, state, and verific…
SafeClawBench: Separating Semantic, Audit-Evidence, and Sandbox Harm in Tool-Using LLM Agents
Yuchuan Tian, Mengyu Zheng, Haocheng Mei +5
Tool-using language-model agents introduce security failures that go beyond unsafe text: they can disclose protected objects, write persistent memory, send messages, modify databas…
From Question Answering to Task Completion: A Survey on Agent System and Harness Design
Jianyuan Guo, Zhiwei Hao, Chengcheng Wang +14
LLM-based agents mark a shift from passive question answering to active task completion: they perceive environments, invoke tools, maintain state, and act over extended horizons. A…
Claw-SWE-Bench: A Benchmark for Evaluating OpenClaw-style Agent Harnesses on Coding Tasks
Mengyu Zheng, Kai Han, Boxun Li +13
The software engineering capabilities of general-purpose agent harnesses remain underexplored, and existing benchmarks offer limited support for comparing these harnesses under con…
Early Semantic Grounding in Image Editing Models for Zero-Shot Referring Image Segmentation
Jingxuan He, Xiyu Wang, Yunke Wang +2
Instruction-based image editing (IIE) models have recently demonstrated strong capability in modifying specific image regions according to natural language instructions, which impl…
Rethinking Where to Edit: Task-Aware Localization for Instruction-Based Image Editing
Jingxuan He, Xiyu Wang, Mengyu Zheng +3
Instruction-based image editing (IIE) aims to modify an image according to a natural language instruction. Despite recent advances in diffusion transformers, existing methods often…
MoRAgent: Parameter Efficient Agent Tuning with Mixture-of-Roles
Jing Han, Binwei Yan, Tianyu Guo +4
Despite recent advancements of fine-tuning large language models (LLMs) to facilitate agent tasks, parameter-efficient fine-tuning (PEFT) methodologies for agent remain largely une…
U-REPA: Aligning Diffusion U-Nets to ViTs
Yuchuan Tian, Hanting Chen, Mengyu Zheng +3
Representation Alignment (REPA) that aligns Diffusion Transformer (DiT) hidden-states with ViT visual encoders has proven highly effective in DiT training, demonstrating superior c…