activity
20232026
most citedUncertainty-Penalized Reinforcement Learning from Human Feedback with Diverse Reward LoRA Ensembles

1 citations · 1 across the 9 of their papers we have counts for

collaborators

12 papers

cs.RO2026

Resilience Matters for Embodied Agents System: New Metrics, Systematic Evaluation, and Optimization

Yapeng Liu, Yuanzhao Zhai, Xudong Gong +4

Embodied Agents System (EAS) are increasingly deployed in open-world physical domains, where reliability directly dictates deployment quality and human-agent trust. However, existi…

cs.AI2026

ReFrame: Evidence-Guided Test-Time Safety Alignment in Multimodal Large Language Models

Wenzheng Jiang, Xuankun Rong, Yuanzhao Zhai +2

While multimodal large language models (MLLMs) extend model capabilities beyond text, they also make safety alignment increasingly challenging. Multimodal safety alignment methods…

cs.SE2026

An Empirical Study on the Impact of Normalized Use-Case Specifications on Traceability

Luoyuan Shi, Yuanzhao Zhai, Dawei Feng +4

Traceability link recovery between requirements and source code is vital for software quality assurance and evolution analysis. Although automated traceability techniques have adva…

cs.RO2026

Energy-Structured Latent World Models with Neural Time Fields for Physically Constistent Open-World Motion Planning

Yapeng Liu, Yuanzhao Zhai, Bo Ding +2

Physically consistent motion planning remains a fundamental challenge in embodied AI, as generated trajectories must strictly conform to real-world execution dynamics. While latent…

cs.AI2026

MCPEvol-Bench: Benchmarking LLM Agent Performance Across Dynamic Evolutions of MCP Servers

Huanxi Liu, Kun Hu, Jiaqi Liao +6

As Model Context Protocol (MCP) servers emerge as the core infrastructure for connecting LLMs with external tools, existing benchmarks leverage real-world MCP servers to evaluate L…

cs.LG2024

Correcting Large Language Model Behavior via Influence Function

Han Zhang, Zhuo Zhang, Yi Zhang +8

Recent advancements in AI alignment techniques have significantly improved the alignment of large language models (LLMs) with static human preferences. However, the dynamic nature…