3 citations · 5 across the 14 of their papers we have counts for
14 papers
PathoSage: Towards Multi-Source Evidence Adjudication in Pathology via Experience-Aware Agentic Workflow
Chengyang Zhang, Wenchuan Zhang, Bo Li +5
Recent advances in Multimodal Large Language Models (MLLMs) and agent workflows have shown strong promise for computational pathology, yet reliable patch-level reasoning remains ch…
Can Large Language Models Understand Internet Buzzwords Through User-Generated Content
Chen Huang, Junkai Luo, Xinzuo Wang +2
The massive user-generated content (UGC) available in Chinese social media is giving rise to the possibility of studying internet buzzwords. In this paper, we study if large langua…
How to Enable Effective Cooperation Between Humans and NLP Models: A Survey of Principles, Formalizations, and Beyond
Chen Huang, Yang Deng, Wenqiang Lei +3
With the advancement of large language models (LLMs), intelligent models have evolved from mere tools to autonomous agents with their own goals and strategies for cooperating with…
Cross-model Transferability among Large Language Models on the Platonic Representations of Concepts
Youcheng Huang, Chen Huang, Duanyu Feng +2
Understanding the inner workings of Large Language Models (LLMs) is a critical research frontier. Prior research has shown that a single LLM's concept representations can be captur…
Effective and Efficient Adversarial Detection for Vision-Language Models via A Single Vector
Youcheng Huang, Fengbin Zhu, Jingkun Tang +4
Visual Language Models (VLMs) are vulnerable to adversarial attacks, especially those from adversarial images, which is however under-explored in literature. To facilitate research…
Dishonesty in Helpful and Harmless Alignment
Youcheng Huang, Jingkun Tang, Duanyu Feng +4
People tell lies when seeking rewards. Large language models (LLMs) are aligned to human values with reinforcement learning where they get rewards if they satisfy human preference.…
ARAIDA: Analogical Reasoning-Augmented Interactive Data Annotation
Chen Huang, Yiping Jin, Ilija Ilievski +2
Human annotation is a time-consuming task that requires a significant amount of effort. To address this issue, interactive data annotation utilizes an annotation model to provide s…
Co-Matching: Towards Human-Machine Collaborative Legal Case Matching
Chen Huang, Xinwei Yang, Yang Deng +3
Recent efforts have aimed to improve AI machines in legal case matching by integrating legal domain knowledge. However, successful legal case matching requires the tacit knowledge…
Concept -- An Evaluation Protocol on Conversational Recommender Systems with System-centric and User-centric Factors
Chen Huang, Peixin Qin, Yang Deng +3
The conversational recommendation system (CRS) has been criticized regarding its user experience in real-world scenarios, despite recent significant progress achieved in academia.…
Selective Annotation via Data Allocation: These Data Should Be Triaged to Experts for Annotation Rather Than the Model
Chen Huang, Yang Deng, Wenqiang Lei +2
To obtain high-quality annotations under limited budget, semi-automatic annotation methods are commonly used, where a portion of the data is annotated by experts and a model is the…
Cross-Space Adaptive Filter: Integrating Graph Topology and Node Attributes for Alleviating the Over-smoothing Problem
Chen Huang, Haoyang Li, Yifan Zhang +2
The vanilla Graph Convolutional Network (GCN) uses a low-pass filter to extract low-frequency signals from graph topology, which may lead to the over-smoothing problem when GCN goe…
DREditor: An Time-efficient Approach for Building a Domain-specific Dense Retrieval Model
Chen Huang, Duanyu Feng, Wenqiang Lei +1
Deploying dense retrieval models efficiently is becoming increasingly important across various industries. This is especially true for enterprise search services, where customizing…
See the Unseen: Better Context-Consistent Knowledge-Editing by Noises
Youcheng Huang, Wenqiang Lei, Zheng Zhang +2
Knowledge-editing updates knowledge of large language models (LLMs) and contributes to the interpretability and application of LLMs. However, knowledge applying is context-consiste…
Towards Equipping Transformer with the Ability of Systematic Compositionality
Chen Huang, Peixin Qin, Wenqiang Lei +1
One of the key factors in language productivity and human cognition is the ability of systematic compositionality, which refers to understanding composed unseen examples of seen pr…