no code implementations • ACL (dialdoc) 2021 • Jiapeng Li, Mingda Li, Longxuan Ma, Wei-Nan Zhang, Ting Liu
The task requires identifying the grounding knowledge in form of a document span for the next dialogue turn.
1 code implementation • 28 Dec 2023 • Abhijit Mishra, Mingda Li, Soham Deo
After adaptation, models are fine-tuned on encrypted versions of existing training datasets.
no code implementations • 15 Aug 2023 • Ziyu Zhuang, Qiguang Chen, Longxuan Ma, Mingda Li, Yi Han, Yushan Qian, Haopeng Bai, Zixian Feng, Weinan Zhang, Ting Liu
From pre-trained language model (PLM) to large language model (LLM), the field of natural language processing (NLP) has witnessed steep performance gains and wide practical uses.
no code implementations • 21 Feb 2023 • Jinglun Cai, Mingda Li, Ziyan Jiang, Eunah Cho, Zheng Chen, Yang Liu, Xing Fan, Chenlei Guo
Query Rewriting (QR) plays a critical role in large-scale dialogue systems for reducing frictions.
1 code implementation • 7 Feb 2023 • Ryotaro Okabe, Shangjie Xue, Jiankai Yu, Tongtong Liu, Benoit Forget, Stefanie Jegelka, Gordon Kohse, Lin-wen Hu, Mingda Li
Here we present a computational framework using Tetris-inspired detector pixels and machine learning for radiation mapping.
1 code implementation • COLING 2022 • Longxuan Ma, Ziyu Zhuang, Weinan Zhang, Mingda Li, Ting Liu
This paper introduces a novel Self-supervised Fine-grained Dialogue Evaluation framework (SelF-Eval).
no code implementations • 8 Apr 2022 • Zijun Xue, Ruirui Li, Mingda Li
Conversational artificial intelligence (AI) is becoming an increasingly popular topic among industry and academia.
no code implementations • 11 Jan 2021 • Thanh Nguyen, Yoichiro Tsurimaki, Ricardo Pablo-Pedro, Grigory Bednik, Anuj Apte, Nina Andrejevic, Mingda Li
Topological nodal semimetals are known to host a variety of fascinating electronic properties due to the topological protection of the band-touching nodes.
Materials Science
no code implementations • COLING 2020 • Mingda Li, Xinyue Liu, Weitong Ruan, Luca Soldaini, Wael Hamza, Chengwei Su
The comparison shows that our model could recover the transcription by integrating the fragmented information among hypotheses and identifying the frequent error patterns of the ASR module, and even rewrite the query for a better understanding, which reveals the characteristic of multi-task learning of broadcasting knowledge.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +6
no code implementations • 17 Apr 2020 • Longxuan Ma, Wei-Nan Zhang, Mingda Li, Ting Liu
We believe that extracting unstructured document(s) information is the future trend of the DS because a great amount of human knowledge lies in these document(s).
no code implementations • 11 Jan 2020 • Mingda Li, Weitong Ruan, Xinyue Liu, Luca Soldaini, Wael Hamza, Chengwei Su
The NLU module usually uses the first best interpretation of a given speech in downstream tasks such as domain and intent classification.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +5
no code implementations • 18 Sep 2019 • Ariyam Das, Youfu Li, Jin Wang, Mingda Li, Carlo Zaniolo
In the past, the semantic issues raised by the non-monotonic nature of aggregates often prevented their use in the recursive statements of logic programs and deductive databases.