Search Results for author: Xiaocui Yang

Found 21 papers, 17 papers with code

AnnaAgent: Dynamic Evolution Agent System with Multi-Session Memory for Realistic Seeker Simulation

1 code implementation31 May 2025 Ming Wang, Peidong Wang, Lin Wu, Xiaocui Yang, Daling Wang, Shi Feng, Yuxin Chen, Bixuan Wang, Yifei Zhang

Constrained by the cost and ethical concerns of involving real seekers in AI-driven mental health, researchers develop LLM-based conversational agents (CAs) with tailored configurations, such as profiles, symptoms, and scenarios, to simulate seekers.

Why Do More Experts Fail? A Theoretical Analysis of Model Merging

1 code implementation27 May 2025 Zijing Wang, Xingle Xu, Yongkang Liu, Yiqun Zhang, Peiqin Lin, Shi Feng, Xiaocui Yang, Daling Wang, Hinrich Schütze

This implies that the effective parameter space becomes rapidly saturated as the number of merged models increases.

Nature-Inspired Population-Based Evolution of Large Language Models

1 code implementation3 Mar 2025 Yiqun Zhang, Peng Ye, Xiaocui Yang, Shi Feng, Shufei Zhang, Lei Bai, Wanli Ouyang, Shuyue Hu

Evolution, the engine behind the survival and growth of life on Earth, operates through the population-based process of reproduction.

Zero-shot Generalization

Pixel-Level Reasoning Segmentation via Multi-turn Conversations

1 code implementation13 Feb 2025 Dexian Cai, Xiaocui Yang, Yongkang Liu, Daling Wang, Shi Feng, Yifei Zhang, Soujanya Poria

To establish a benchmark for this novel task, we build a Pixel-level ReasonIng Segmentation Dataset Based on Multi-Turn Conversations (PRIST), comprising 24k utterances from 8. 3k multi-turn conversational scenarios with segmentation targets.

Reasoning Segmentation Segmentation

PsyDraw: A Multi-Agent Multimodal System for Mental Health Screening in Left-Behind Children

1 code implementation19 Dec 2024 Yiqun Zhang, Xiaocui Yang, Xiaobai Li, Siyuan Yu, Yi Luan, Shi Feng, Daling Wang, Yifei Zhang

Left-behind children (LBCs), numbering over 66 million in China, face severe mental health challenges due to parental migration for work.

Language Models as Continuous Self-Evolving Data Engineers

no code implementations19 Dec 2024 Peidong Wang, Ming Wang, ZhiMing Ma, Xiaocui Yang, Shi Feng, Daling Wang, Yifei Zhang

Large Language Models (LLMs) have demonstrated remarkable capabilities on various tasks, while the further evolvement is limited to the lack of high-quality training data.

TOOL-ED: Enhancing Empathetic Response Generation with the Tool Calling Capability of LLM

1 code implementation4 Dec 2024 Huiying Cao, Yiqun Zhang, Shi Feng, Xiaocui Yang, Daling Wang, Yifei Zhang

We validate EKTC on the ED dataset, and the experimental results demonstrate that our framework can enhance the ability of LLMs to generate empathetic responses effectively.

Empathetic Response Generation Response Generation

Generative Emotion Cause Explanation in Multimodal Conversations

no code implementations1 Nov 2024 Lin Wang, Xiaocui Yang, Shi Feng, Daling Wang, Yifei Zhang

Multimodal conversation, a crucial form of human communication, carries rich emotional content, making the exploration of the causes of emotions within it a research endeavor of significant importance.

Large Language Model

Hierarchical Retrieval-Augmented Generation Model with Rethink for Multi-hop Question Answering

1 code implementation20 Aug 2024 XiaoMing Zhang, Ming Wang, Xiaocui Yang, Daling Wang, Shi Feng, Yifei Zhang

Multi-hop Question Answering (QA) necessitates complex reasoning by integrating multiple pieces of information to resolve intricate questions.

Multi-hop Question Answering Question Answering +2

Affective Computing in the Era of Large Language Models: A Survey from the NLP Perspective

no code implementations30 Jul 2024 Yiqun Zhang, Xiaocui Yang, Xingle Xu, Zeran Gao, YiJie Huang, Shiyi Mu, Shi Feng, Daling Wang, Yifei Zhang, Kaisong Song, Ge Yu

The emergence of Large Language Models (LLMs), such as the ChatGPT series and LLaMA models, brings new opportunities and challenges, catalyzing a paradigm shift in AC.

Common Sense Reasoning In-Context Learning +1

Is Mamba Effective for Time Series Forecasting?

1 code implementation17 Mar 2024 Zihan Wang, Fanheng Kong, Shi Feng, Ming Wang, Xiaocui Yang, Han Zhao, Daling Wang, Yifei Zhang

For TSF tasks, these characteristics enable Mamba to comprehend hidden patterns as the Transformer and reduce computational overhead compared to the Transformer.

Computational Efficiency Mamba +2

Consistency Guided Knowledge Retrieval and Denoising in LLMs for Zero-shot Document-level Relation Triplet Extraction

1 code implementation24 Jan 2024 Qi Sun, Kun Huang, Xiaocui Yang, Rong Tong, Kun Zhang, Soujanya Poria

In this paper, we propose a Zero-shot Document-level Relation Triplet Extraction (ZeroDocRTE) framework, which generates labeled data by retrieval and denoising knowledge from LLMs, called GenRDK.

Denoising Relation +3

MM-BigBench: Evaluating Multimodal Models on Multimodal Content Comprehension Tasks

2 code implementations13 Oct 2023 Xiaocui Yang, Wenfang Wu, Shi Feng, Ming Wang, Daling Wang, Yang Li, Qi Sun, Yifei Zhang, XiaoMing Fu, Soujanya Poria

Consequently, our work complements research on the performance of MLLMs in multimodal comprehension tasks, achieving a more comprehensive and holistic evaluation of MLLMs.

multimodal interaction Multimodal Reasoning

Uncertainty Guided Label Denoising for Document-level Distant Relation Extraction

1 code implementation18 May 2023 Qi Sun, Kun Huang, Xiaocui Yang, Pengfei Hong, Kun Zhang, Soujanya Poria

Therefore, how to select effective pseudo labels to denoise DS data is still a challenge in document-level distant relation extraction.

Denoising Document-level Relation Extraction +1

Few-shot Multimodal Sentiment Analysis based on Multimodal Probabilistic Fusion Prompts

1 code implementation12 Nov 2022 Xiaocui Yang, Shi Feng, Daling Wang, Pengfei Hong, Soujanya Poria

To tackle this problem, we propose a novel method called Multimodal Probabilistic Fusion Prompts (MultiPoint) that leverages diverse cues from different modalities for multimodal sentiment detection in the few-shot scenario.

Language Modelling Multimodal Sentiment Analysis

Multimodal Sentiment Detection Based on Multi-channel Graph Neural Networks

1 code implementation ACL 2021 Xiaocui Yang, Shi Feng, Yifei Zhang, Daling Wang

In this paper, we propose Multi-channel Graph Neural Networks with Sentiment-awareness (MGNNS) for image-text sentiment detection.

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