58 citations · 64 across the 16 of their papers we have counts for
17 papers
MMHBench: A Multi-Perspective Benchmark for Mental Health Understanding in Long-Form Videos
Jinpeng Hu, Erqiang Wang, Shan Wang +4
Mental health understanding in long-form videos requires nuanced reasoning over observable behavior, interpersonal context, and latent psychological states. Existing benchmarks lar…
WebUncertainty: Dual-Level Uncertainty Driven Planning and Reasoning For Autonomous Web Agent
Lingfeng Zhang, Yongan Sun, Jinpeng Hu +5
Recent advancements in large language models (LLMs) have empowered autonomous web agents to execute natural language instructions directly on real-world webpages. However, existing…
APLOT: Robust Reward Modeling via Adaptive Preference Learning with Optimal Transport
Zhuo Li, Yuege Feng, Dandan Guo +3
The reward model (RM) plays a crucial role in aligning Large Language Models (LLMs) with human preferences through Reinforcement Learning, where the Bradley-Terry (BT) objective ha…
Beyond Emotion Recognition: A Multi-Turn Multimodal Emotion Understanding and Reasoning Benchmark
Jinpeng Hu, Hongchang Shi, Chongyuan Dai +3
Multimodal large language models (MLLMs) have been widely applied across various fields due to their powerful perceptual and reasoning capabilities. In the realm of psychology, the…
In-Context Examples Matter: Improving Emotion Recognition in Conversation with Instruction Tuning
Hui Ma, Bo Zhang, Jinpeng Hu +1
Emotion recognition in conversation (ERC) aims to identify the emotion of each utterance in a conversation, playing a vital role in empathetic artificial intelligence. With the gro…
AgentMental: An Interactive Multi-Agent Framework for Explainable and Adaptive Mental Health Assessment
Jinpeng Hu, Ao Wang, Qianqian Xie +3
Mental health assessment is crucial for early intervention and effective treatment, yet traditional clinician-based approaches are limited by the shortage of qualified professional…
Psyche-R1: Towards Reliable Psychological LLMs through Unified Empathy, Expertise, and Reasoning
Chongyuan Dai, Jinpeng Hu, Hongchang Shi +4
Amidst a shortage of qualified mental health professionals, the integration of large language models (LLMs) into psychological applications offers a promising way to alleviate the…
Add-One-In: Incremental Sample Selection for Large Language Models via a Choice-Based Greedy Paradigm
Zhuo Li, Yuhao Du, Xiaoqi Jiao +5
Selecting high-quality and diverse training samples from extensive datasets plays a crucial role in reducing training overhead and enhancing the performance of Large Language Model…
Self-Instructed Derived Prompt Generation Meets In-Context Learning: Unlocking New Potential of Black-Box LLMs
Zhuo Li, Yuhao Du, Jinpeng Hu +2
Large language models (LLMs) have shown success in generating high-quality responses. In order to achieve better alignment with LLMs with human preference, various works are propos…
PsycoLLM: Enhancing LLM for Psychological Understanding and Evaluation
Jinpeng Hu, Tengteng Dong, Luo Gang +6
Mental health has attracted substantial attention in recent years and LLM can be an effective technology for alleviating this problem owing to its capability in text understanding…
Is ChatGPT a Highly Fluent Grammatical Error Correction System? A Comprehensive Evaluation
Tao Fang, Shu Yang, Kaixin Lan +4
ChatGPT, a large-scale language model based on the advanced GPT-3.5 architecture, has shown remarkable potential in various Natural Language Processing (NLP) tasks. However, there…
Improving Radiology Summarization with Radiograph and Anatomy Prompts
Jinpeng Hu, Zhihong Chen, Yang Liu +2
The impression is crucial for the referring physicians to grasp key information since it is concluded from the findings and reasoning of radiologists. To alleviate the workload of…
Multi-Modal Masked Autoencoders for Medical Vision-and-Language Pre-Training
Zhihong Chen, Yuhao Du, Jinpeng Hu +4
Medical vision-and-language pre-training provides a feasible solution to extract effective vision-and-language representations from medical images and texts. However, few studies h…
A Simple yet Effective Relation Information Guided Approach for Few-Shot Relation Extraction
Yang Liu, Jinpeng Hu, Xiang Wan +1
Few-Shot Relation Extraction aims at predicting the relation for a pair of entities in a sentence by training with a few labelled examples in each relation. Some recent works have…
Hero-Gang Neural Model For Named Entity Recognition
Jinpeng Hu, Yaling Shen, Yang Liu +2
Named entity recognition (NER) is a fundamental and important task in NLP, aiming at identifying named entities (NEs) from free text. Recently, since the multi-head attention mecha…
Graph Enhanced Contrastive Learning for Radiology Findings Summarization
Jinpeng Hu, Zhuo Li, Zhihong Chen +3
The impression section of a radiology report summarizes the most prominent observation from the findings section and is the most important section for radiologists to communicate t…
Word Graph Guided Summarization for Radiology Findings
Jinpeng Hu, Jianling Li, Zhihong Chen +4
Radiology reports play a critical role in communicating medical findings to physicians. In each report, the impression section summarizes essential radiology findings. In clinical…