20 papers
LazyTrain: Limited-resource Allocation toward Zero-waste Yield Optimization in Large Language Model Training
Xiaojun Wu, Cehao Yang, Honghao Liu +5
Training large language models on limited hardware is increasingly a scheduling problem across GPU compute, host memory, PCIe transfer, and storage bandwidth. Existing offloading s…
LiveClawBench: Benchmarking LLM Agents on Complex, Real-World Assistant Tasks
Xiang Long, Li Du, Yilong Xu +11
OpenClaw-style personal assistants extend LLM agents from isolated tool use to open-ended, stateful, and personalized software environments. Evaluating these assistants is fundamen…
Bayesian-Agent: Posterior-Guided Skill Evolution Across LLM Agent Harnesses
Xiaojun Wu, Cehao Yang, Honghao Liu +7
LLM agents increasingly rely on prompts, tools, memory, SOPs, skills, and harness feedback, yet current self-evolution pipelines often update these assets through heuristic reflect…
NTIRE 2026 The 3rd Restore Any Image Model (RAIM) Challenge: Professional Image Quality Assessment (Track 1)
Guanyi Qin, Jie Liang, Bingbing Zhang +50
In this paper, we present an overview of the NTIRE 2026 challenge on the 3rd Restore Any Image Model in the Wild, specifically focusing on Track 1: Professional Image Quality Asses…
Conflicts Make Large Reasoning Models Vulnerable to Attacks
Honghao Liu, Chengjin Xu, Xuhui Jiang +5
Large Reasoning Models (LRMs) have achieved remarkable performance across diverse domains, yet their decision-making under conflicting objectives remains insufficiently understood.…
JudgeAgent: Beyond Static Benchmarks for Knowledge-Driven and Dynamic LLM Evaluation
Zhichao Shi, Xuhui Jiang, Chengjin Xu +6
Current evaluation methods for large language models (LLMs) primarily rely on static benchmarks, presenting two major challenges: limited knowledge coverage and fixed difficulties…