Search Results for author: Zhenzhong Lan

Found 46 papers, 23 papers with code

Predicting the Big Five Personality Traits in Chinese Counselling Dialogues Using Large Language Models

1 code implementation25 Jun 2024 Yang Yan, Lizhi Ma, Anqi Li, Jingsong Ma, Zhenzhong Lan

This study exams whether Large Language Models (LLMs) can predict the Big Five personality traits directly from counseling dialogues and introduces an innovative framework to perform the task.

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

Automatic Evaluation for Mental Health Counseling using LLMs

no code implementations19 Feb 2024 Anqi Li, Yu Lu, Nirui Song, Shuai Zhang, Lizhi Ma, Zhenzhong Lan

High-quality psychological counseling is crucial for mental health worldwide, and timely evaluation is vital for ensuring its effectiveness.

Unveiling the Secrets of Engaging Conversations: Factors that Keep Users Hooked on Role-Playing Dialog Agents

no code implementations18 Feb 2024 Shuai Zhang, Yu Lu, Junwen Liu, JIA YU, Huachuan Qiu, Yuming Yan, Zhenzhong Lan

With the growing humanlike nature of dialog agents, people are now engaging in extended conversations that can stretch from brief moments to substantial periods of time.

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

1 code implementation25 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.

AgentBoard: An Analytical Evaluation Board of Multi-turn LLM Agents

2 code implementations24 Jan 2024 Chang Ma, Junlei Zhang, Zhihao Zhu, Cheng Yang, Yujiu Yang, Yaohui Jin, Zhenzhong Lan, Lingpeng Kong, Junxian He

Evaluating large language models (LLMs) as general-purpose agents is essential for understanding their capabilities and facilitating their integration into practical applications.

Benchmarking

PsyChat: A Client-Centric Dialogue System for Mental Health Support

1 code implementation7 Dec 2023 Huachuan Qiu, Anqi Li, Lizhi Ma, Zhenzhong Lan

Dialogue systems are increasingly integrated into mental health support to help clients facilitate exploration, gain insight, take action, and ultimately heal themselves.

Quality and Quantity: Unveiling a Million High-Quality Images for Text-to-Image Synthesis in Fashion Design

no code implementations19 Nov 2023 JIA YU, Lichao Zhang, Zijie Chen, Fayu Pan, Miaomiao Wen, Yuming Yan, Fangsheng Weng, Shuai Zhang, Lili Pan, Zhenzhong Lan

Moreover, to foster standardization in the T2I-based fashion design field, we propose a new benchmark comprising multiple datasets for evaluating the performance of fashion design models.

Image Generation

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).

Multiple-choice

Tailored Visions: Enhancing Text-to-Image Generation with Personalized Prompt Rewriting

1 code implementation CVPR 2024 Zijie Chen, Lichao Zhang, Fangsheng Weng, Lili Pan, Zhenzhong Lan

Despite significant progress in the field, it is still challenging to create personalized visual representations that align closely with the desires and preferences of individual users.

Text-to-Image Generation

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.

SuperCLUE: A Comprehensive Chinese Large Language Model Benchmark

no code implementations27 Jul 2023 Liang Xu, Anqi Li, Lei Zhu, Hang Xue, Changtai Zhu, Kangkang Zhao, Haonan He, Xuanwei Zhang, Qiyue Kang, Zhenzhong Lan

We fill this gap by proposing a comprehensive Chinese benchmark SuperCLUE, named after another popular Chinese LLM benchmark CLUE.

Language Modelling Large Language Model

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).

Enhancing Grammatical Error Correction Systems with Explanations

1 code implementation25 May 2023 Yuejiao Fei, Leyang Cui, Sen yang, Wai Lam, Zhenzhong Lan, Shuming Shi

Grammatical error correction systems improve written communication by detecting and correcting language mistakes.

Grammatical Error Correction

Contrastive Learning of Sentence Embeddings from Scratch

2 code implementations24 May 2023 Junlei Zhang, Zhenzhong Lan, Junxian He

Contrastive learning has been the dominant approach to train state-of-the-art sentence embeddings.

Contrastive Learning Natural Language Inference +3

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

Furthermore, we implement an expert evaluation and the results demonstrate that the dialogues generated with our proposed method are of higher quality than those generated with other baseline methods.

Chatbot

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.

S-SimCSE: Sampled Sub-networks for Contrastive Learning of Sentence Embedding

no code implementations23 Nov 2021 Junlei Zhang, Zhenzhong Lan

The corresponding outputs, two sentence embeddings derived from the same sentence with different dropout masks, can be used to build a positive pair.

Contrastive Learning Data Augmentation +4

Dynamic Resolution Network

3 code implementations NeurIPS 2021 Mingjian Zhu, Kai Han, Enhua Wu, Qiulin Zhang, Ying Nie, Zhenzhong Lan, Yunhe Wang

To this end, we propose a novel dynamic-resolution network (DRNet) in which the input resolution is determined dynamically based on each input sample.

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

Do Transformer Modifications Transfer Across Implementations and Applications?

1 code implementation EMNLP 2021 Sharan Narang, Hyung Won Chung, Yi Tay, William Fedus, Thibault Fevry, Michael Matena, Karishma Malkan, Noah Fiedel, Noam Shazeer, Zhenzhong Lan, Yanqi Zhou, Wei Li, Nan Ding, Jake Marcus, Adam Roberts, Colin Raffel

The research community has proposed copious modifications to the Transformer architecture since it was introduced over three years ago, relatively few of which have seen widespread adoption.

Attention that does not Explain Away

no code implementations29 Sep 2020 Nan Ding, Xinjie Fan, Zhenzhong Lan, Dale Schuurmans, Radu Soricut

Models based on the Transformer architecture have achieved better accuracy than the ones based on competing architectures for a large set of tasks.

Talking-Heads Attention

4 code implementations5 Mar 2020 Noam Shazeer, Zhenzhong Lan, Youlong Cheng, Nan Ding, Le Hou

We introduce "talking-heads attention" - a variation on multi-head attention which includes linearprojections across the attention-heads dimension, immediately before and after the softmax operation. While inserting only a small number of additional parameters and a moderate amount of additionalcomputation, talking-heads attention leads to better perplexities on masked language modeling tasks, aswell as better quality when transfer-learning to language comprehension and question answering tasks.

Language Modelling Masked Language Modeling +2

Multi-stage Pretraining for Abstractive Summarization

no code implementations23 Sep 2019 Sebastian Goodman, Zhenzhong Lan, Radu Soricut

Neural models for abstractive summarization tend to achieve the best performance in the presence of highly specialized, summarization specific modeling add-ons such as pointer-generator, coverage-modeling, and inferencetime heuristics.

Abstractive Text Summarization

Hidden Two-Stream Convolutional Networks for Action Recognition

3 code implementations2 Apr 2017 Yi Zhu, Zhenzhong Lan, Shawn Newsam, Alexander G. Hauptmann

State-of-the-art action recognition approaches rely on traditional optical flow estimation methods to pre-compute motion information for CNNs.

Action Recognition Optical Flow Estimation +2

Guided Optical Flow Learning

no code implementations8 Feb 2017 Yi Zhu, Zhenzhong Lan, Shawn Newsam, Alexander G. Hauptmann

We study the unsupervised learning of CNNs for optical flow estimation using proxy ground truth data.

Image Reconstruction Optical Flow Estimation

Deep Local Video Feature for Action Recognition

no code implementations25 Jan 2017 Zhenzhong Lan, Yi Zhu, Alexander G. Hauptmann

We investigate the problem of representing an entire video using CNN features for human action recognition.

Action Recognition Temporal Action Localization

Strategies for Searching Video Content with Text Queries or Video Examples

no code implementations17 Jun 2016 Shoou-I Yu, Yi Yang, Zhongwen Xu, Shicheng Xu, Deyu Meng, Zexi Mao, Zhigang Ma, Ming Lin, Xuanchong Li, Huan Li, Zhenzhong Lan, Lu Jiang, Alexander G. Hauptmann, Chuang Gan, Xingzhong Du, Xiaojun Chang

The large number of user-generated videos uploaded on to the Internet everyday has led to many commercial video search engines, which mainly rely on text metadata for search.

Event Detection Retrieval +1

Improving Human Activity Recognition Through Ranking and Re-ranking

no code implementations11 Dec 2015 Zhenzhong Lan, Shoou-I Yu, Alexander G. Hauptmann

We propose two well-motivated ranking-based methods to enhance the performance of current state-of-the-art human activity recognition systems.

Human Activity Recognition Re-Ranking

Handcrafted Local Features are Convolutional Neural Networks

no code implementations16 Nov 2015 Zhenzhong Lan, Shoou-I Yu, Ming Lin, Bhiksha Raj, Alexander G. Hauptmann

We approach this problem by first showing that local handcrafted features and Convolutional Neural Networks (CNNs) share the same convolution-pooling network structure.

Action Recognition Optical Flow Estimation +2

The Best of Both Worlds: Combining Data-independent and Data-driven Approaches for Action Recognition

no code implementations17 May 2015 Zhenzhong Lan, Dezhong Yao, Ming Lin, Shoou-I Yu, Alexander Hauptmann

First, we propose a two-stream Stacked Convolutional Independent Subspace Analysis (ConvISA) architecture to show that unsupervised learning methods can significantly boost the performance of traditional local features extracted from data-independent models.

Action Recognition Multi-class Classification +3

Long-short Term Motion Feature for Action Classification and Retrieval

no code implementations13 Feb 2015 Zhenzhong Lan, Xuanchong Li, Ming Lin, Alexander G. Hauptmann

Therefore, they need to occur frequently enough in the videos and to be be able to tell the difference among different types of motions.

Action Classification Classification +3

Self-Paced Learning with Diversity

no code implementations NeurIPS 2014 Lu Jiang, Deyu Meng, Shoou-I Yu, Zhenzhong Lan, Shiguang Shan, Alexander Hauptmann

Self-paced learning (SPL) is a recently proposed learning regime inspired by the learning process of humans and animals that gradually incorporates easy to more complex samples into training.

Diversity

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