20 citations · 32 across the 14 of their papers we have counts for
10 papers · 1 filter
STAMPsy: Towards SpatioTemporal-Aware Mixed-Type Dialogues for Psychological Counseling
Jieyi Wang, Yue Huang, Zeming Liu +7
Online psychological counseling dialogue systems are trending, offering a convenient and accessible alternative to traditional in-person therapy. However, existing psychological co…
ReFF: Reinforcing Format Faithfulness in Language Models across Varied Tasks
Jiashu Yao, Heyan Huang, Zeming Liu +4
Following formatting instructions to generate well-structured content is a fundamental yet often unmet capability for large language models (LLMs). To study this capability, which…
MlingConf: A Comprehensive Study of Multilingual Confidence Estimation on Large Language Models
Boyang Xue, Hongru Wang, Rui Wang +5
The tendency of Large Language Models (LLMs) to generate hallucinations raises concerns regarding their reliability. Therefore, confidence estimations indicating the extent of trus…
FAME: Towards Factual Multi-Task Model Editing
Li Zeng, Yingyu Shan, Zeming Liu +2
Large language models (LLMs) embed extensive knowledge and utilize it to perform exceptionally well across various tasks. Nevertheless, outdated knowledge or factual errors within…
A Survey on Data Synthesis and Augmentation for Large Language Models
Ke Wang, Jiahui Zhu, Minjie Ren +8
The success of Large Language Models (LLMs) is inherently linked to the availability of vast, diverse, and high-quality data for training and evaluation. However, the growth rate o…
AppBench: Planning of Multiple APIs from Various APPs for Complex User Instruction
Hongru Wang, Rui Wang, Boyang Xue +5
Large Language Models (LLMs) can interact with the real world by connecting with versatile external APIs, resulting in better problem-solving and task automation capabilities. Prev…