37 citations · 194 across the 44 of their papers we have counts for
44 papers
ALaRM: Align Language Models via Hierarchical Rewards Modeling
Yuhang Lai, Siyuan Wang, Shujun Liu +2
We introduce ALaRM, the first framework modeling hierarchical rewards in reinforcement learning from human feedback (RLHF), which is designed to enhance the alignment of large lang…
Debatrix: Multi-dimensional Debate Judge with Iterative Chronological Analysis Based on LLM
Jingcong Liang, Rong Ye, Meng Han +4
How can we construct an automated debate judge to evaluate an extensive, vibrant, multi-turn debate? This task is challenging, as judging a debate involves grappling with lengthy t…
Benchmark Self-Evolving: A Multi-Agent Framework for Dynamic LLM Evaluation
Siyuan Wang, Zhuohan Long, Zhihao Fan +2
This paper presents a benchmark self-evolving framework to dynamically evaluate rapidly advancing Large Language Models (LLMs), aiming for a more accurate assessment of their capab…
Can LLMs Reason with Rules? Logic Scaffolding for Stress-Testing and Improving LLMs
Siyuan Wang, Zhongyu Wei, Yejin Choi +1
Large language models (LLMs) have achieved impressive human-like performance across various reasoning tasks. However, their mastery of underlying inferential rules still falls shor…
CauESC: A Causal Aware Model for Emotional Support Conversation
Wei Chen, Hengxu Lin, Qun Zhang +4
Emotional Support Conversation aims at reducing the seeker's emotional distress through supportive response. Existing approaches have two limitations: (1) They ignore the emotion c…
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…
Locate Then Ask: Interpretable Stepwise Reasoning for Multi-hop Question Answering
Siyuan Wang, Zhongyu Wei, Zhihao Fan +2
Multi-hop reasoning requires aggregating multiple documents to answer a complex question. Existing methods usually decompose the multi-hop question into simpler single-hop question…
A Unified Continuous Learning Framework for Multi-modal Knowledge Discovery and Pre-training
Zhihao Fan, Zhongyu Wei, Jingjing Chen +4
Multi-modal pre-training and knowledge discovery are two important research topics in multi-modal machine learning. Nevertheless, none of existing works make attempts to link knowl…
DxFormer: A Decoupled Automatic Diagnostic System Based on Decoder-Encoder Transformer with Dense Symptom Representations
Wei Chen, Cheng Zhong, Jiajie Peng +1
Diagnosis-oriented dialogue system queries the patient's health condition and makes predictions about possible diseases through continuous interaction with the patient. A few studi…