Search Results for author: Hongliang He

Found 20 papers, 11 papers with code

APSeg: Auto-Prompt Model with Acquired and Injected Knowledge for Nuclear Instance Segmentation and Classification

no code implementations3 Apr 2025 Liying Xu, Hongliang He, Wei Han, Hanbin Huang, Siwei Feng, Guohong Fu

Therefore, we focus on generating prompts with more accurate localization and classification and propose \textbf{APSeg}, \textbf{A}uto-\textbf{P}rompt model with acquired and injected knowledge for nuclear instance \textbf{Seg}mentation and classification.

Classification Instance Segmentation +2

Instance Migration Diffusion for Nuclear Instance Segmentation in Pathology

no code implementations2 Apr 2025 Lirui Qi, Hongliang He, Tong Wang, Siwei Feng, Guohong Fu

To tackle this challenge, we propose a novel data augmentation framework Instance Migration Diffusion Model (IM-Diffusion), IM-Diffusion designed to generate more varied pathological images by constructing diverse nuclear layouts and internuclear spatial relationships.

Data Augmentation Instance Segmentation +2

MaintAGT:Sim2Real-Guided Multimodal Large Model for Intelligent Maintenance with Chain-of-Thought Reasoning

no code implementations30 Nov 2024 Hongliang He, Jinfeng Huang, Qi Li, Xu Wang, Feibin Zhang, Kangding Yang, Li Meng, Fulei Chu

In recent years, large language models have made significant advancements in the field of natural language processing, yet there are still inadequacies in specific domain knowledge and applications.

OpenWebVoyager: Building Multimodal Web Agents via Iterative Real-World Exploration, Feedback and Optimization

1 code implementation25 Oct 2024 Hongliang He, Wenlin Yao, Kaixin Ma, Wenhao Yu, Hongming Zhang, Tianqing Fang, Zhenzhong Lan, Dong Yu

In this paper, we introduce an open-source framework designed to facilitate the development of multimodal web agent that can autonomously conduct real-world exploration and improve itself.

Imitation Learning

VSLLaVA: a pipeline of large multimodal foundation model for industrial vibration signal analysis

no code implementations3 Sep 2024 Qi Li, Jinfeng Huang, Hongliang He, Xinran Zhang, Feibin Zhang, Zhaoye Qin, Fulei Chu

This paper presents a pipeline named VSLLaVA that leverages a large language model to integrate expert knowledge for identification of signal parameters and diagnosis of faults.

Fault Diagnosis Language Modeling +2

Facilitating Pornographic Text Detection for Open-Domain Dialogue Systems via Knowledge Distillation of Large Language Models

1 code implementation20 Mar 2024 Huachuan Qiu, Shuai Zhang, Hongliang He, Anqi Li, Zhenzhong Lan

Pornographic content occurring in human-machine interaction dialogues can cause severe side effects for users in open-domain dialogue systems.

Chatbot Knowledge Distillation +1

WebVoyager: Building an End-to-End Web Agent with Large Multimodal Models

2 code implementations25 Jan 2024 Hongliang He, Wenlin Yao, Kaixin Ma, Wenhao Yu, Yong Dai, Hongming Zhang, Zhenzhong Lan, Dong Yu

The rapid advancement of large language models (LLMs) has led to a new era marked by the development of autonomous applications in real-world scenarios, which drives innovation in creating advanced web agents.

ConceptPsy:A Benchmark Suite with Conceptual Comprehensiveness in Psychology

no code implementations16 Nov 2023 Junlei Zhang, Hongliang He, Nirui Song, Zhanchao Zhou, Shuyuan He, Shuai Zhang, Huachuan Qiu, Anqi Li, Yong Dai, Lizhi Ma, Zhenzhong Lan

The critical field of psychology necessitates a comprehensive benchmark to enhance the evaluation and development of domain-specific Large Language Models (LLMs).

MMLU Multiple-choice

Facilitating NSFW Text Detection in Open-Domain Dialogue Systems via Knowledge Distillation

1 code implementation18 Sep 2023 Huachuan Qiu, Shuai Zhang, Hongliang He, Anqi Li, Zhenzhong Lan

NSFW (Not Safe for Work) content, in the context of a dialogue, can have severe side effects on users in open-domain dialogue systems.

Chatbot Knowledge Distillation +1

A Benchmark for Understanding Dialogue Safety in Mental Health Support

1 code implementation31 Jul 2023 Huachuan Qiu, Tong Zhao, Anqi Li, Shuai Zhang, Hongliang He, Zhenzhong Lan

Our study reveals that ChatGPT struggles to detect safety categories with detailed safety definitions in a zero- and few-shot paradigm, whereas the fine-tuned model proves to be more suitable.

Latent Jailbreak: A Benchmark for Evaluating Text Safety and Output Robustness of Large Language Models

1 code implementation17 Jul 2023 Huachuan Qiu, Shuai Zhang, Anqi Li, Hongliang He, Zhenzhong Lan

We present a systematic analysis of the safety and robustness of LLMs regarding the position of explicit normal instructions, word replacements (verbs in explicit normal instructions, target groups in malicious instructions, cue words for explicit normal instructions), and instruction replacements (different explicit normal instructions).

Instance Smoothed Contrastive Learning for Unsupervised Sentence Embedding

1 code implementation12 May 2023 Hongliang He, Junlei Zhang, Zhenzhong Lan, Yue Zhang

Contrastive learning-based methods, such as unsup-SimCSE, have achieved state-of-the-art (SOTA) performances in learning unsupervised sentence embeddings.

Contrastive Learning Semantic Similarity +6

SMILE: Single-turn to Multi-turn Inclusive Language Expansion via ChatGPT for Mental Health Support

1 code implementation30 Apr 2023 Huachuan Qiu, Hongliang He, Shuai Zhang, Anqi Li, Zhenzhong Lan

Further, we employ our method to generate a large-scale, lifelike, and diverse dialogue dataset named SMILECHAT, consisting of 55k dialogues.

Chatbot

Robust Secrecy via Aerial Reflection and Jamming: Joint Optimization of Deployment and Transmission

no code implementations28 Feb 2023 Xiao Tang, Hongliang He, Limeng Dong, Lixin Li, Qinghe Du, Zhu Han

The security gain with aerial reflection and jamming is further improved with the optimized deployment of the aerial platform.

Deep Reinforcement Learning

TopoSeg: Topology-Aware Nuclear Instance Segmentation

no code implementations ICCV 2023 Hongliang He, Jun Wang, Pengxu Wei, Fan Xu, Xiangyang Ji, Chang Liu, Jie Chen

Experiments on three nuclear instance segmentation datasets justify the superiority of TopoSeg, which achieves state-of-the-art performance.

Instance Segmentation Segmentation +1

Towards Automated Real-time Evaluation in Text-based Counseling

no code implementations7 Mar 2022 Anqi Li, Jingsong Ma, Lizhi Ma, Pengfei Fang, Hongliang He, Zhenzhong Lan

However, these methods often demand large scale and high quality counseling data, which are difficult to collect.

Uni-Encoder: A Fast and Accurate Response Selection Paradigm for Generation-Based Dialogue Systems

1 code implementation2 Jun 2021 Chiyu Song, Hongliang He, Haofei Yu, Pengfei Fang, Leyang Cui, Zhenzhong Lan

The current state-of-the-art ranking methods mainly use an encoding paradigm called Cross-Encoder, which separately encodes each context-candidate pair and ranks the candidates according to their fitness scores.

Computational Efficiency Conversational Response Selection

CDNet: Centripetal Direction Network for Nuclear Instance Segmentation

2 code implementations ICCV 2021 Hongliang He, Zhongyi Huang, Yao Ding, Guoli Song, Lin Wang, Qian Ren, Pengxu Wei, Zhiqiang Gao, Jie Chen

Specifically, we define the centripetal direction feature as a class of adjacent directions pointing to the nuclear center to represent the spatial relationship between pixels within the nucleus.

Instance Segmentation Segmentation +1

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