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Mingjie Zhang

7 accepted papers

2026

ASKD: Reinforcement Learning-Style Knowledge Distillation with Quality-Adaptive Skewness

AAAI 2026technical

Knowledge distillation (KD) is a widely adopted technique for transferring the capabilities of large teacher models to smaller student models, thereby significantly reducing inference costs and memory consumption. However, existing KD methods are all constrained by an inherent greedy optimization ob

Cited by 0SourcePDFScholar
2026

ApexNav: An Adaptive Exploration Strategy for Zero-Shot Object Navigation with Target-Centric Semantic Fusion

ICRA 2026poster

Navigating unknown environments to find a target object is a significant challenge. While semantic information is crucial for navigation, relying solely on it for decision-making may not always be efficient, especially in environments with weak semantic cues. Additionally, many methods are susceptib…

2025

ApexNAV: An Adaptive Exploration Strategy for Zero-Shot Object Navigation With Target-Centric Semantic Fusion

RA-L 2025

Navigating unknown environments to find a target object is a significant challenge. While semantic information is crucial for navigation, relying solely on it for decision-making may not always be efficient, especially in environments with weak semantic cues. Additionally, many methods are susceptib

Cited by 24SourceScholar
2025

Boosting Resilience of Large Language Models through Causality-Driven Robust Optimization

NeurIPS 2025poster

Large language models (LLMs) have achieved remarkable achievements across diverse applications; however, they remain plagued by spurious correlations and the generation of hallucinated content. Despite extensive efforts to enhance the resilience of LLMs, existing approaches either rely on indiscrimi…

Cited by 0SourceScholar
2025

HaDeMiF: Hallucination Detection and Mitigation in Large Language Models

ICLR 2025poster

The phenomenon of knowledge hallucinations has raised substantial concerns about the security and reliability of deployed large language models (LLMs). Current methods for detecting hallucinations primarily depend on manually designed individual metrics, such as prediction uncertainty and consistenc…

Cited by 0SourcePDFScholar
2024

FC-Planner: A Skeleton-guided Planning Framework for Fast Aerial Coverage of Complex 3D Scenes

ICRA 2024poster

3D coverage path planning for UAVs is a crucial problem in diverse practical applications. However, existing methods have shown unsatisfactory system simplicity, computation efficiency, and path quality in large and complex scenes. To address these challenges, we propose FC-Planner, a skeleton-guide…

Cited by 12SourcecodeScholar
2024

SOAR: Simultaneous Exploration and Photographing with Heterogeneous UAVs for Fast Autonomous Reconstruction

IROS 2024poster

Unmanned Aerial Vehicles (UAVs) have gained significant popularity in scene reconstruction. This paper presents SOAR, a LiDAR-Visual heterogeneous multi-UAV system specifically designed for fast autonomous reconstruction of complex environments. Our system comprises a LiDAR-equipped explorer with a…

Cited by 3SourcecodeScholar