20 citations · 37 across the 9 of their papers we have counts for
10 papers
Progressive Multimodal Alignment for Continual Instruction Tuning
Duzhen Zhang, Yahan Yu, Qiaoyi Su +2
Multimodal Large Language Models (MLLMs) rely on a projector to align visual representations with the language embedding space, making it central to cross-modal understanding. In M…
Crafting Your Evolving Dreams: Concept-Incremental Versatile Customization
Jiahua Dong, Wenqi Liang, Hongliu Li +7
Custom diffusion models (CDMs) have garnered significant interest owing to their remarkable capacity for generating personalized concepts. However, the majority of CDMs unrealistic…
BioXArena: Benchmarking LLM Agents on Multi-Modal Biomedical Machine Learning Tasks
Loka Li, Duzhen Zhang, Xingbo Du +11
Large language model (LLM) agents increasingly automate machine-learning model building, yet biomedical benchmarks emphasize question answering, reasoning, and tool use or cover na…
Exploring Stability-Plasticity Trade-offs for Continual Named Entity Recognition
Duzhen Zhang, Chenxing Li, Jiahua Dong +2
Continual Named Entity Recognition (CNER) is an evolving field that focuses on sequentially updating an existing model to incorporate new entity types. Previous CNER methods primar…
MedKGent: A Large Language Model Agent Framework for Constructing Temporally Evolving Medical Knowledge Graph
Duzhen Zhang, Zixiao Wang, Zhong-Zhi Li +10
The rapid expansion of medical literature challenges the scalable structuring of domain knowledge. Knowledge Graphs (KGs) offer a solution, yet current construction methods lack ge…
Enhancing Multimodal Continual Instruction Tuning with BranchLoRA
Duzhen Zhang, Yong Ren, Zhong-Zhi Li +5
Multimodal Continual Instruction Tuning (MCIT) aims to finetune Multimodal Large Language Models (MLLMs) to continually align with human intent across sequential tasks. Existing ap…
From System 1 to System 2: A Survey of Reasoning Large Language Models
Zhong-Zhi Li, Duzhen Zhang, Ming-Liang Zhang +18
Achieving human-level intelligence requires refining the transition from the fast, intuitive System 1 to the slower, more deliberate System 2 reasoning. While System 1 excels in qu…
Federated Incremental Named Entity Recognition
Duzhen Zhang, Yahan Yu, Chenxing Li +2
Federated Named Entity Recognition (FNER) boosts model training within each local client by aggregating the model updates of decentralized local clients, without sharing their priv…
MM-LLMs: Recent Advances in MultiModal Large Language Models
Duzhen Zhang, Yahan Yu, Jiahua Dong +4
In the past year, MultiModal Large Language Models (MM-LLMs) have undergone substantial advancements, augmenting off-the-shelf LLMs to support MM inputs or outputs via cost-effecti…
Continual Named Entity Recognition without Catastrophic Forgetting
Duzhen Zhang, Wei Cong, Jiahua Dong +4
Continual Named Entity Recognition (CNER) is a burgeoning area, which involves updating an existing model by incorporating new entity types sequentially. Nevertheless, continual le…