37 citations · 194 across the 44 of their papers we have counts for
16 papers · 1 filter
Argue with Me Tersely: Towards Sentence-Level Counter-Argument Generation
Jiayu Lin, Rong Ye, Meng Han +6
Counter-argument generation -- a captivating area in computational linguistics -- seeks to craft statements that offer opposing views. While most research has ventured into paragra…
K-ESConv: Knowledge Injection for Emotional Support Dialogue Systems via Prompt Learning
Wei Chen, Gang Zhao, Xiaojin Zhang +3
Automatic psychological counseling requires mass of professional knowledge that can be found in online counseling forums. Motivated by this, we propose K-ESConv, a novel prompt lea…
Hi-ArG: Exploring the Integration of Hierarchical Argumentation Graphs in Language Pretraining
Jingcong Liang, Rong Ye, Meng Han +6
The knowledge graph is a structure to store and represent knowledge, and recent studies have discussed its capability to assist language models for various applications. Some varia…
DISC-FinLLM: A Chinese Financial Large Language Model based on Multiple Experts Fine-tuning
Wei Chen, Qiushi Wang, Zefei Long +8
We propose Multiple Experts Fine-tuning Framework to build a financial large language model (LLM), DISC-FinLLM. Our methodology improves general LLMs by endowing them with multi-tu…
ReForm-Eval: Evaluating Large Vision Language Models via Unified Re-Formulation of Task-Oriented Benchmarks
Zejun Li, Ye Wang, Mengfei Du +9
Recent years have witnessed remarkable progress in the development of large vision-language models (LVLMs). Benefiting from the strong language backbones and efficient cross-modal…
DISC-MedLLM: Bridging General Large Language Models and Real-World Medical Consultation
Zhijie Bao, Wei Chen, Shengze Xiao +6
We propose DISC-MedLLM, a comprehensive solution that leverages Large Language Models (LLMs) to provide accurate and truthful medical response in end-to-end conversational healthca…
Breaking Down the Task: A Unit-Grained Hybrid Training Framework for Vision and Language Decision Making
Ruipu Luo, Jiwen Zhang, Zhongyu Wei
Vision language decision making (VLDM) is a challenging multimodal task. The agent have to understand complex human instructions and complete compositional tasks involving environm…
DSRM: Boost Textual Adversarial Training with Distribution Shift Risk Minimization
Songyang Gao, Shihan Dou, Yan Liu +5
Adversarial training is one of the best-performing methods in improving the robustness of deep language models. However, robust models come at the cost of high time consumption, as…
Actively Supervised Clustering for Open Relation Extraction
Jun Zhao, Yongxin Zhang, Qi Zhang +4
Current clustering-based Open Relation Extraction (OpenRE) methods usually adopt a two-stage pipeline. The first stage simultaneously learns relation representations and assignment…
RE-Matching: A Fine-Grained Semantic Matching Method for Zero-Shot Relation Extraction
Jun Zhao, Wenyu Zhan, Xin Zhao +6
Semantic matching is a mainstream paradigm of zero-shot relation extraction, which matches a given input with a corresponding label description. The entities in the input should ex…
Open Set Relation Extraction via Unknown-Aware Training
Jun Zhao, Xin Zhao, Wenyu Zhan +6
The existing supervised relation extraction methods have achieved impressive performance in a closed-set setting, where the relations during both training and testing remain the sa…
Valley: Video Assistant with Large Language model Enhanced abilitY
Ruipu Luo, Ziwang Zhao, Min Yang +6
Large Language Models (LLMs), with remarkable conversational capability, have emerged as AI assistants that can handle both visual and textual modalities. However, their effectiven…
KNSE: A Knowledge-aware Natural Language Inference Framework for Dialogue Symptom Status Recognition
Wei Chen, Shiqi Wei, Zhongyu Wei +1
Symptom diagnosis in medical conversations aims to correctly extract both symptom entities and their status from the doctor-patient dialogue. In this paper, we propose a novel fram…
Query Structure Modeling for Inductive Logical Reasoning Over Knowledge Graphs
Siyuan Wang, Zhongyu Wei, Meng Han +4
Logical reasoning over incomplete knowledge graphs to answer complex logical queries is a challenging task. With the emergence of new entities and relations in constantly evolving…
AR-Diffusion: Auto-Regressive Diffusion Model for Text Generation
Tong Wu, Zhihao Fan, Xiao Liu +9
Diffusion models have gained significant attention in the realm of image generation due to their exceptional performance. Their success has been recently expanded to text generatio…
Unifying Structure Reasoning and Language Model Pre-training for Complex Reasoning
Siyuan Wang, Zhongyu Wei, Jiarong Xu +2
Recent pre-trained language models (PLMs) equipped with foundation reasoning skills have shown remarkable performance on downstream complex tasks. However, the significant structur…