32 citations · 53 across the 6 of their papers we have counts for
6 papers
Quantifying and Attributing the Hallucination of Large Language Models via Association Analysis
Li Du, Yequan Wang, Xingrun Xing +4
Although demonstrating superb performance on various NLP tasks, large language models (LLMs) still suffer from the hallucination problem, which threatens the reliability of LLMs. T…
FLM-101B: An Open LLM and How to Train It with $100K Budget
Xiang Li, Yiqun Yao, Xin Jiang +10
Large language models (LLMs) are considered important approaches towards foundational machine intelligence, achieving remarkable success in Natural Language Processing and multimod…
FreeLM: Fine-Tuning-Free Language Model
Xiang Li, Xin Jiang, Xuying Meng +2
Pre-trained language models (PLMs) have achieved remarkable success in NLP tasks. Despite the great success, mainstream solutions largely follow the pre-training then finetuning pa…
CofeNet: Context and Former-Label Enhanced Net for Complicated Quotation Extraction
Yequan Wang, Xiang Li, Aixin Sun +3
Quotation extraction aims to extract quotations from written text. There are three components in a quotation: source refers to the holder of the quotation, cue is the trigger word(…
ConvLab-2: An Open-Source Toolkit for Building, Evaluating, and Diagnosing Dialogue Systems
Qi Zhu, Zheng Zhang, Yan Fang +7
We present ConvLab-2, an open-source toolkit that enables researchers to build task-oriented dialogue systems with state-of-the-art models, perform an end-to-end evaluation, and di…
ConvLab: Multi-Domain End-to-End Dialog System Platform
Sungjin Lee, Qi Zhu, Ryuichi Takanobu +8
We present ConvLab, an open-source multi-domain end-to-end dialog system platform, that enables researchers to quickly set up experiments with reusable components and compare a lar…