SLP-L19.6
ROBUST SELF-SUPERVISED LEARNING WITH CONTRAST SAMPLES FOR NATURAL LANGUAGE UNDERSTANDING
Jie Liu, Xue Han, Chao Deng, Junlan Feng, China Mobile Research, China
Session:
SLP-L19: Language understanding and computational semantics II - Language Models Lecture
Track:
Speech and Language Processing
Location:
Room 102
Presentation Time:
Thu, 18 Apr, 10:00 - 10:20 (UTC +9)
Session Chair:
Chiori Hori, MERL
Session SLP-L19
SLP-L19.1: HINT-ENHANCED IN-CONTEXT LEARNING WAKES LARGE LANGUAGE MODELS UP FOR KNOWLEDGE-INTENSIVE TASKS
Yifan Wang, Qingyan Guo, Xinzhe Ni, Chufan Shi, Tsinghua University, China; Lemao Liu, Haiyun Jiang, Tencent AI Lab, China; Yujiu Yang, Tsinghua University, China
SLP-L19.2: ENABLING DEVICE CONTROL PLANNING CAPABILITIES OF SMALL LANGUAGE MODEL
Sudipta Paul, Lingyu Zhang, Yilin Shen, Hongxia Jin, Samsung Research America, United States of America
SLP-L19.3: TREE OF UNCERTAIN THOUGHTS REASONING FOR LARGE LANGUAGE MODELS
Shentong Mo, Carnegie Mellon University, United States of America; Miao Xin, Institute of Automation, Chinese Academy of Sciences, China
SLP-L19.4: RETRIEVAL-GENERATION SYNERGY AUGMENTED LARGE LANGUAGE MODELS
Zhangyin Feng, Xiaocheng Feng, Dezhi Zhao, Maojin Yang, Bing Qin, Harbin institute of technology, China
SLP-L19.5: LEVERAGING BIASES IN LARGE LANGUAGE MODELS: “BIAS-KNN” FOR EFFECTIVE FEW-SHOT LEARNING
Yong Zhang, Hanzhang Li, Zhitao Li, Ning Cheng, Ming Li, Jing Xiao, Jianzong Wang, Ping An Technology (Shenzhen) Co., Ltd., China, China
SLP-L19.6: ROBUST SELF-SUPERVISED LEARNING WITH CONTRAST SAMPLES FOR NATURAL LANGUAGE UNDERSTANDING
Jie Liu, Xue Han, Chao Deng, Junlan Feng, China Mobile Research, China
Contacts