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Zeren Luo

9 accepted papers

2026

JALMBench: Benchmarking Jailbreak Vulnerabilities in Audio Language Models

ICLR 2026poster

Large Audio Language Models (LALMs) integrate the audio modality directly into the model, rather than converting speech into text and inputting text to Large Language Models (LLMs). While jailbreak attacks on LLMs have been extensively studied, the security of LALMs with audio modalities remains lar…

Cited by 0SourcecodeScholar
2026

Learning Autonomous and Safe Quadruped Traversal of Complex Terrains Using Multi-Layer Elevation Maps

ICRA 2026poster

Legged robots hold great promise for agile and flexible mobility across diverse and unstructured terrains, inspired by the remarkable adaptability of bipeds and quadrupeds in nature. However, achieving robust autonomous locomotion in cluttered and complex environments remains a significant challenge…

Cited by 0SourceScholar
2026

MILD: Tractable Terrain Modeling for Learning Improved Bipedal Locomotion on Deformable Surfaces

RA-L 2026

Enabling robots to walk on yielding terrain is vital for applications ranging from disaster response to planetary exploration. While bipedal robots hold immense potential, their locomotion on deformable surfaces remains limited as current simulators fail to capture the spatiotemporal heterogeneity o

Cited by 1SourceScholar
2026

MILD: Tractable Terrain Modeling for Learning Improved Bipedal Locomotion on Deformable Surfaces

ICRA 2026poster

Enabling robots to walk on yielding terrain is vital for applications ranging from disaster response to planetary exploration. While bipedal robots hold immense potential, their locomotion on deformable surfaces remains limited as current simulators fail to capture the spatiotemporal heterogeneity o…

Cited by 0SourceScholar
2026

OmniNet: Omnidirectional Jumping Neural Network with Height-Awareness for Quadrupedal Robots

ICRA 2026poster

In the robotics community, it has been a longstanding challenge for quadrupeds to achieve highly explosive movements similar to their biological counterparts. In this work, we introduce a novel training framework that achieves height-aware and omnidirectional jumping for quadrupedal robots. To facil…

Cited by 0SourceScholar
2025

Learning Autonomous and Safe Quadruped Traversal of Complex Terrains Using Multi-Layer Elevation Maps

RA-L 2025

Legged robots hold great promise for agile and flexible mobility across diverse and unstructured terrains, inspired by the remarkable adaptability of bipeds and quadrupeds in nature. However, achieving robust autonomous locomotion in cluttered and complex environments remains a significant challenge

Cited by 11SourceScholar
2025

OmniNet: Omnidirectional Jumping Neural Network With Height-Awareness for Quadrupedal Robots

RA-L 2025

In the robotics community, it has been a longstanding challenge for quadrupeds to achieve highly explosive movements similar to their biological counterparts. In this work, we introduce a novel training framework that achieves height-aware and omnidirectional jumping for quadrupedal robots. To facil

Cited by 3SourceScholar
2024

MorAL: Learning Morphologically Adaptive Locomotion Controller for Quadrupedal Robots on Challenging Terrains

RA-L 2024

Due to the rapid development of the quadruped robot industry in the past decade, various commercial quadruped robots have emerged with distinct physical attributes. Different from the previous work in which the designed controller is robot-specific, this article proposes a learning-based control fra

Cited by 37SourceScholar