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Haocheng Wang

5 accepted papers

2026

Emergent Co-Adaptive Strategies in Heterogeneous Multi-Robot Systems Via Meta-Learning

ICRA 2026poster

Abstract— As teamed robots increasingly share public spaces with humans, the ability to co-adapt—to mutually adjust behavior in response to one another—becomes essential for safe, efficient, and socially acceptable operation. This paper introduces a socially co-adaptive framework for heterogeneous m…

Cited by 0Scholar
2026

FormalRx: Rectify and eXamine Semantic Failures in Autoformalization

ICML 2026poster

Autoformalization—translating mathematical problems from natural language into formal proof assistant code—is essential for rigorous machine reasoning. However, existing evaluation frameworks provide only opaque binary verdicts or scalar scores, offering no interpretable insight into where or why tr…

Cited by 0SourceScholar
2025

DeepSeek-Prover-V1.5: Harnessing Proof Assistant Feedback for Reinforcement Learning and Monte-Carlo Tree Search

ICLR 2025poster

Lean is an advanced proof assistant designed to facilitate formal theorem proving by providing a variety of interactive feedback. In this paper, we explore methodologies to leverage proof assistant feedback to augment the capabilities of large language models in constructing formal proofs. First, we…

2025

Point Cloud Registration Based on Adaptively Fused Multimodal Features

RA-L 2025

Point cloud registration is a fundamental task in 3D vision, which plays an important role in various fields but faces challenges in geometrically weak or repetitive scenes. Traditional geometric-based methods struggle in these cases, while recent multimodal approaches improve robustness in weak sce

Cited by 4SourceScholar
2025

Unsupervised RGB-D Point Cloud Registration for Scenes with Low Overlap and Photometric Inconsistency

ICCV 2025poster

Point cloud registration is a fundamental task in 3D vision, playing a crucial role in various fields. With the rapid advancement of RGB-D sensors, unsupervised point cloud registration methods based on RGB-D sequences have demonstrated excellent performance. However, existing methods struggle in sc…

Cited by 0SourcePDFScholar