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Honglei Guo

6 accepted papers

2026

Empowering Multi-Robot Cooperation via Sequential World Models

ICLR 2026poster

Model-based reinforcement learning (MBRL) has achieved remarkable success in robotics due to its high sample efficiency and planning capability. However, extending MBRL to physical multi-robot cooperation remains challenging due to the complexity of joint dynamics. To address this challenge, we prop…

Cited by 0SourcecodeScholar
2025

EIC Framework for Hand Exoskeletons Based on a Multimodal Large Language Model

IROS 2025

Current hand exoskeleton interaction methods primarily focus on recognizing a limited range of hand motion intentions and rely on pre-programmed control to execute predefined commands. However, these approaches face significant limitations when confronted with unanticipated or non-predefined scenari

Cited by 1SourceScholar
2025

Feel the Difference? A Comparative Analysis of Emotional Arcs in Real and LLM-Generated CBT Sessions

EMNLP 2025

Synthetic therapy dialogues generated by large language models (LLMs) are increasingly used in mental health NLP to simulate counseling scenarios, train models, and supplement limited real-world data. However, it remains unclear whether these synthetic conversations capture the nuanced emotional dyn

Cited by 0SourcePDFScholar
2021

Efficient Mind-Map Generation via Sequence-to-Graph and Reinforced Graph Refinement

EMNLP 2021main

A mind-map is a diagram that represents the central concept and key ideas in a hierarchical way. Converting plain text into a mind-map will reveal its key semantic structure and be easier to understand. Given a document, the existing automatic mind-map generation method extracts the relationships of…

Cited by 4SourcePDFScholar
2021

Multi-Label Few-Shot Learning for Aspect Category Detection

ACL 2021long

Aspect category detection (ACD) in sentiment analysis aims to identify the aspect categories mentioned in a sentence. In this paper, we formulate ACD in the few-shot learning scenario. However, existing few-shot learning approaches mainly focus on single-label predictions. These methods can not work…

Cited by 52SourcePDFScholar
2020

Deep Semantic Compliance Advisor for Unstructured Document Compliance Checking

IJCAI 2020poster

Unstructured document compliance checking is always a big challenge for banks since huge amounts of contracts and regulations written in natural language require professionals' interpretation and judgment. Traditional rule-based or keyword-based methods cannot precisely characterize the deep s…

Cited by 0SourcePDFScholar