18 citations · 94 across the 22 of their papers we have counts for
13 papers · 1 filter
From LLMs to MLLMs: Exploring the Landscape of Multimodal Jailbreaking
Siyuan Wang, Zhuohan Long, Zhihao Fan +1
The rapid development of Large Language Models (LLMs) and Multimodal Large Language Models (MLLMs) has exposed vulnerabilities to various adversarial attacks. This paper provides a…
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…
AI Hospital: Benchmarking Large Language Models in a Multi-agent Medical Interaction Simulator
Zhihao Fan, Jialong Tang, Wei Chen +5
Artificial intelligence has significantly advanced healthcare, particularly through large language models (LLMs) that excel in medical question answering benchmarks. However, their…
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…
Text Generation with Diffusion Language Models: A Pre-training Approach with Continuous Paragraph Denoise
Zhenghao Lin, Yeyun Gong, Yelong Shen +5
In this paper, we introduce a novel dIffusion language modEl pre-training framework for text generation, which we call GENIE. GENIE is a large-scale pretrained diffusion language m…
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…
Contextual Fine-to-Coarse Distillation for Coarse-grained Response Selection in Open-Domain Conversations
Wei Chen, Yeyun Gong, Can Xu +9
We study the problem of coarse-grained response selection in retrieval-based dialogue systems. The problem is equally important with fine-grained response selection, but is less ex…
Logic-Driven Context Extension and Data Augmentation for Logical Reasoning of Text
Siyuan Wang, Wanjun Zhong, Duyu Tang +5
Logical reasoning of text requires understanding critical logical information in the text and performing inference over them. Large-scale pre-trained models for logical reasoning m…
Mask Attention Networks: Rethinking and Strengthen Transformer
Zhihao Fan, Yeyun Gong, Dayiheng Liu +6
Transformer is an attention-based neural network, which consists of two sublayers, namely, Self-Attention Network (SAN) and Feed-Forward Network (FFN). Existing research explores t…
An Enhanced Knowledge Injection Model for Commonsense Generation
Zhihao Fan, Yeyun Gong, Zhongyu Wei +6
Commonsense generation aims at generating plausible everyday scenario description based on a set of provided concepts. Digging the relationship of concepts from scratch is non-triv…