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Hongxu Liu

4 accepted papers

2026

An Information-Theoretic Parameter-Free Bayesian Framework for Probing Labeled Dependency Trees from Attention Score

ICLR 2026poster

Figuring out how neural language models comprehend syntax acts as a key to revealing how they understand languages. We systematically analyzed methods of extracting syntax from models, namely _probing_, and found limitations yet widely exist in previous probing practice. We proposed a method capab…

Cited by 0SourcecodeScholar
2024

Dual-Stage Multi-Task Syntax-Oriented Pre-Training for Syntactically Controlled Paraphrase Generation

ACL 2024findings

Syntactically Controlled Paraphrase Generation (SCPG), which aims at generating sentences having syntactic structures resembling given exemplars, is attracting more research efforts in recent years. We took an empirical survey on previous SCPG datasets and methods and found three tacitly approved wh…

2021

Combining Learning from Demonstration with Learning by Exploration to Facilitate Contact-Rich Tasks

IROS 2021poster

Collaborative robots are expected to work alongside humans and directly replace human workers in some cases, thus effectively responding to rapid changes in assembly lines. Current methods for programming contact-rich tasks, particularly in heavily constrained spaces, tend to be fairly inefficient.…

Cited by 20SourceScholar
2021

Proactive Action Visual Residual Reinforcement Learning for Contact-Rich Tasks Using a Torque-Controlled Robot

ICRA 2021poster

Contact-rich manipulation tasks are commonly found in modern manufacturing settings. However, manually designing a robot controller is considered hard for traditional control methods as the controller requires an effective combination of modalities and vastly different characteristics. In this paper…

Cited by 22SourceScholar