1.5k citations · 1.7k across the 24 of their papers we have counts for
10 papers · 1 filter
Beyond Imitation: Leveraging Fine-grained Quality Signals for Alignment
Geyang Guo, Ranchi Zhao, Tianyi Tang +2
Alignment with human preference is a desired property of large language models (LLMs). Currently, the main alignment approach is based on reinforcement learning from human feedback…
BAMBOO: A Comprehensive Benchmark for Evaluating Long Text Modeling Capacities of Large Language Models
Zican Dong, Tianyi Tang, Junyi Li +2
Large language models (LLMs) have achieved dramatic proficiency over NLP tasks with normal length. Recently, multiple studies have committed to extending the context length and enh…
Towards Effective Ancient Chinese Translation: Dataset, Model, and Evaluation
Geyang Guo, Jiarong Yang, Fengyuan Lu +3
Interpreting ancient Chinese has been the key to comprehending vast Chinese literature, tradition, and civilization. In this paper, we propose Erya for ancient Chinese translation.…
Learning to Imagine: Visually-Augmented Natural Language Generation
Tianyi Tang, Yushuo Chen, Yifan Du +3
People often imagine relevant scenes to aid in the writing process. In this work, we aim to utilize visual information for composition in the same manner as humans. We propose a me…
Zero-shot Visual Question Answering with Language Model Feedback
Yifan Du, Junyi Li, Tianyi Tang +2
In this paper, we propose a novel language model guided captioning approach, LAMOC, for knowledge-based visual question answering (VQA). Our approach employs the generated captions…
The Web Can Be Your Oyster for Improving Large Language Models
Junyi Li, Tianyi Tang, Wayne Xin Zhao +3
Large language models (LLMs) encode a large amount of world knowledge. However, as such knowledge is frozen at the time of model training, the models become static and limited by t…
Not All Metrics Are Guilty: Improving NLG Evaluation by Diversifying References
Tianyi Tang, Hongyuan Lu, Yuchen Eleanor Jiang +5
Most research about natural language generation (NLG) relies on evaluation benchmarks with limited references for a sample, which may result in poor correlations with human judgeme…
Not All Languages Are Created Equal in LLMs: Improving Multilingual Capability by Cross-Lingual-Thought Prompting
Haoyang Huang, Tianyi Tang, Dongdong Zhang +4
Large language models (LLMs) demonstrate impressive multilingual capability, but their performance varies substantially across different languages. In this work, we introduce a sim…
A Survey of Large Language Models
Wayne Xin Zhao, Kun Zhou, Junyi Li +19
Language is essentially a complex, intricate system of human expressions governed by grammatical rules. It poses a significant challenge to develop capable AI algorithms for compre…
A Survey on Long Text Modeling with Transformers
Zican Dong, Tianyi Tang, Junyi Li +1
Modeling long texts has been an essential technique in the field of natural language processing (NLP). With the ever-growing number of long documents, it is important to develop ef…