activity
20202026
most citedLasUIE: Unifying Information Extraction with Latent Adaptive Structure-aware Generative Language Model

69 citations · 138 across the 32 of their papers we have counts for

collaborators
Showing 2024Show all

11 papers · 1 filter

cs.CL2024

Can Large Language Models Understand You Better? An MBTI Personality Detection Dataset Aligned with Population Traits

Bohan Li, Jiannan Guan, Longxu Dou +12

The Myers-Briggs Type Indicator (MBTI) is one of the most influential personality theories reflecting individual differences in thinking, feeling, and behaving. MBTI personality de…

cs.CV2024

Exploring Multi-Grained Concept Annotations for Multimodal Large Language Models

Xiao Xu, Tianhao Niu, Yuxi Xie +3

Multimodal Large Language Models (MLLMs) excel in vision--language tasks by pre-training solely on coarse-grained concept annotations (e.g., image captions). We hypothesize that in…

cs.CV2024

CoMT: A Novel Benchmark for Chain of Multi-modal Thought on Large Vision-Language Models

Zihui Cheng, Qiguang Chen, Jin Zhang +5

Large Vision-Language Models (LVLMs) have recently demonstrated amazing success in multi-modal tasks, including advancements in Multi-modal Chain-of-Thought (MCoT) reasoning. Despi…

cs.CL2024

Stealthy Jailbreak Attacks on Large Language Models via Benign Data Mirroring

Honglin Mu, Han He, Yuxin Zhou +9

Large language model (LLM) safety is a critical issue, with numerous studies employing red team testing to enhance model security. Among these, jailbreak methods explore potential…

cs.CL2024

AutoCAP: Towards Automatic Cross-lingual Alignment Planning for Zero-shot Chain-of-Thought

Yongheng Zhang, Qiguang Chen, Min Li +2

Cross-lingual chain-of-thought can effectively complete reasoning tasks across languages, which gains increasing attention. Recently, dominant approaches in the literature improve…

cs.CL2024

CroPrompt: Cross-task Interactive Prompting for Zero-shot Spoken Language Understanding

Libo Qin, Fuxuan Wei, Qiguang Chen +5

Slot filling and intent detection are two highly correlated tasks in spoken language understanding (SLU). Recent SLU research attempts to explore zero-shot prompting techniques in…