no code implementations • 24 Nov 2024 • Lifu Tu, Rui Meng, Shafiq Joty, Yingbo Zhou, Semih Yavuz
Interestingly, even without significant changes in the models' self-judgment (Self-Known and Self-Unknown), the number of unsupported claims can increases, likely as an artifact of long-form generation.
no code implementations • 19 Nov 2024 • Ye Liu, Rui Meng, Shafiq Joty, Silvio Savarese, Caiming Xiong, Yingbo Zhou, Semih Yavuz
This gap leaves existing models unable to effectively capture the diversity of programming languages and tasks across different domains, highlighting the need for more focused research in code retrieval.
no code implementations • 13 Nov 2024 • Rui Meng, Hangyu Zhao, Bingxuan Xu, Yining Wang, Xiaodong Xu, Suyu Lv, Xiaofeng Tao, Ping Zhang
Physical-Layer Authentication (PLA) offers endogenous security, lightweight implementation, and high reliability, making it a promising complement to upper-layer security methods in Edge Intelligence (EI)-empowered Industrial Internet of Things (IIoT).
1 code implementation • 31 Oct 2024 • Jianqun Zhou, Yuanlei Zheng, Wei Chen, Qianqian Zheng, Zeyuan Shang, Wei zhang, Rui Meng, Xiaoyu Shen
Instruction-following capabilities in large language models (LLMs) have significantly progressed, enabling more complex user interactions through detailed prompts.
no code implementations • 7 Oct 2024 • Yuelyu Ji, Zhuochun Li, Rui Meng, Daqing He
Reranking documents based on their relevance to a given query is a critical task in information retrieval.
no code implementations • 7 Oct 2024 • Ziyan Jiang, Rui Meng, Xinyi Yang, Semih Yavuz, Yingbo Zhou, Wenhu Chen
Embedding models have been crucial in enabling various downstream tasks such as semantic similarity, information retrieval, and clustering.
no code implementations • 4 Oct 2024 • Zhuochun Li, Yuelyu Ji, Rui Meng, Daqing He
While reasoning capabilities typically emerge in large language models (LLMs) with tens of billions of parameters, recent research focuses on improving smaller open-source models through knowledge distillation (KD) from commercial LLMs.
1 code implementation • 3 Oct 2024 • Rui Meng, Ye Liu, Lifu Tu, Daqing He, Yingbo Zhou, Semih Yavuz
Phrases are fundamental linguistic units through which humans convey semantics.
no code implementations • 10 Jun 2024 • Yujee Song, DongHyun Lee, Rui Meng, Won Hwa Kim
While most previous studies focus on the inter-event dependencies and their representations, how individual events influence the overall dynamics over time has been under-explored.
1 code implementation • 21 May 2024 • Yuelyu Ji, Zhuochun Li, Rui Meng, Sonish Sivarajkumar, Yanshan Wang, Zeshui Yu, Hui Ji, Yushui Han, Hanyu Zeng, Daqing He
This paper introduces the RAG-RLRC-LaySum framework, designed to make complex biomedical research understandable to laymen through advanced Natural Language Processing (NLP) techniques.
1 code implementation • 11 Dec 2023 • Lifu Tu, Semih Yavuz, Jin Qu, Jiacheng Xu, Rui Meng, Caiming Xiong, Yingbo Zhou
Large Language Models (LLMs) have demonstrated a powerful ability for text generation.
no code implementations • 15 Sep 2023 • Meghana Moorthy Bhat, Rui Meng, Ye Liu, Yingbo Zhou, Semih Yavuz
As we embark on a new era of LLMs, it becomes increasingly crucial to understand their capabilities, limitations, and differences.
1 code implementation • 7 Sep 2023 • Erik Nijkamp, Tian Xie, Hiroaki Hayashi, Bo Pang, Congying Xia, Chen Xing, Jesse Vig, Semih Yavuz, Philippe Laban, Ben Krause, Senthil Purushwalkam, Tong Niu, Wojciech Kryściński, Lidiya Murakhovs'ka, Prafulla Kumar Choubey, Alex Fabbri, Ye Liu, Rui Meng, Lifu Tu, Meghana Bhat, Chien-Sheng Wu, Silvio Savarese, Yingbo Zhou, Shafiq Joty, Caiming Xiong
Most open-source LLMs, on the other hand, are limited in their ability to support longer sequence lengths, which is a key requirement for many tasks that require inference over an input context.
no code implementations • 24 Aug 2023 • Ye Liu, Semih Yavuz, Rui Meng, Meghana Moorthy, Shafiq Joty, Caiming Xiong, Yingbo Zhou
This paper aims to fill this gap by investigating different methods of combining retrieved passages with LLMs to enhance answer generation.
no code implementations • 16 Aug 2023 • JianGuo Zhang, Stephen Roller, Kun Qian, Zhiwei Liu, Rui Meng, Shelby Heinecke, Huan Wang, Silvio Savarese, Caiming Xiong
End-to-end task-oriented dialogue (TOD) systems have achieved promising performance by leveraging sophisticated natural language understanding and natural language generation capabilities of pre-trained models.
no code implementations • 23 Jul 2023 • Rui Meng, Fangzhou Zhu, Xiaodong Xu, Bizhu Wang, Bingxuan Xu, Ping Zhang
Furthermore, our proposed fingerprint selection algorithms achieve the reduction in the authentication error rate of up to 86. 93% compared to baseline active learning algorithms.
1 code implementation • 19 Jul 2023 • JianGuo Zhang, Kun Qian, Zhiwei Liu, Shelby Heinecke, Rui Meng, Ye Liu, Zhou Yu, Huan Wang, Silvio Savarese, Caiming Xiong
Despite advancements in conversational AI, language models encounter challenges to handle diverse conversational tasks, and existing dialogue dataset collections often lack diversity and comprehensiveness.
no code implementations • 12 May 2023 • Ye Liu, Semih Yavuz, Rui Meng, Dragomir Radev, Caiming Xiong, Yingbo Zhou
It comprises two central pillars: (1) We parse the question of varying complexity into an intermediate representation, named H-expression, which is composed of simple questions as the primitives and symbolic operations representing the relationships among them; (2) To execute the resulting H-expressions, we design a hybrid executor, which integrates the deterministic rules to translate the symbolic operations with a drop-in neural reader network to answer each decomposed simple question.
no code implementations • 19 Apr 2023 • Bingxuan Xu, Rui Meng, Yue Chen, Xiaodong Xu, Chen Dong, Hao Sun
Upon the designed DNSC architecture, we further combine adversarial learning, variational autoencoder, and diffusion model to propose the Latent Diffusion DNSC (Latent-Diff DNSC) scheme to realize intelligent online de-noising.
1 code implementation • 19 Dec 2022 • Ning Yu, Chia-Chih Chen, Zeyuan Chen, Rui Meng, Gang Wu, Paul Josel, Juan Carlos Niebles, Caiming Xiong, ran Xu
Graphic layout designs play an essential role in visual communication.
1 code implementation • 17 Dec 2022 • Rui Meng, Ye Liu, Semih Yavuz, Divyansh Agarwal, Lifu Tu, Ning Yu, JianGuo Zhang, Meghana Bhat, Yingbo Zhou
In this study, we aim to develop unsupervised methods for improving dense retrieval models.
no code implementations • 9 Nov 2022 • Ye Liu, Semih Yavuz, Rui Meng, Dragomir Radev, Caiming Xiong, Yingbo Zhou
Parsing natural language questions into executable logical forms is a useful and interpretable way to perform question answering on structured data such as knowledge bases (KB) or databases (DB).
1 code implementation • 20 Aug 2022 • Rui Meng, Tong Wang, Xingdi Yuan, Yingbo Zhou, Daqing He
Finally, we fine-tune the model with limited data with true labels to fully adapt it to the target domain.
1 code implementation • Findings (NAACL) 2022 • Yifan Gao, Qingyu Yin, Zheng Li, Rui Meng, Tong Zhao, Bing Yin, Irwin King, Michael R. Lyu
Keyphrase generation is the task of automatically predicting keyphrases given a piece of long text.
no code implementations • Findings (ACL) 2022 • Tianyi Luo, Rui Meng, Xin Eric Wang, Yang Liu
Research Replication Prediction (RRP) is the task of predicting whether a published research result can be replicated or not.
no code implementations • 3 Mar 2022 • Rui Meng, Tianyi Luo, Kristofer Bouchard
The key insight of our framework is to learn representations by minimizing the compression complexity and maximizing the predictive information in latent space.
no code implementations • 25 Jun 2021 • Rui Meng, Kristofer Bouchard
Stochastic linear mixing models (SLMM) assume the mixture coefficients depend on input, making them more flexible and effective to capture complex output dependence.
no code implementations • 1 Jun 2021 • Rui Meng, Herbie Lee, Kristofer Bouchard
This paper presents an efficient variational inference framework for deriving a family of structured gaussian process regression network (SGPRN) models.
2 code implementations • ACL 2021 • Rui Meng, Khushboo Thaker, Lei Zhang, Yue Dong, Xingdi Yuan, Tong Wang, Daqing He
Faceted summarization provides briefings of a document from different perspectives.
Ranked #1 on Unsupervised Extractive Summarization on FacetSum
1 code implementation • 18 Apr 2021 • Xianjie Shen, Yinghan Wang, Rui Meng, Jingbo Shang
Keyphrase generation aims to summarize long documents with a collection of salient phrases.
no code implementations • 1 Oct 2020 • Rui Meng, Zhen Yue, Alyssa Glass
Therefore, we consider predicting user engagement status as the very first and critical step to online evaluation for intelligent assistants.
1 code implementation • NAACL 2021 • Rui Meng, Xingdi Yuan, Tong Wang, Sanqiang Zhao, Adam Trischler, Daqing He
Recent years have seen a flourishing of neural keyphrase generation (KPG) works, including the release of several large-scale datasets and a host of new models to tackle them.
2 code implementations • 11 Aug 2020 • Tryambak Gangopadhyay, Sin Yong Tan, Zhanhong Jiang, Rui Meng, Soumik Sarkar
Accurate interpretation of such prediction outcomes from a machine learning model that explicitly captures temporal correlations can significantly benefit the domain experts.
no code implementations • 13 Oct 2019 • Rui Meng, Braden Soper, Herbert Lee, Vincent X. Liu, John D. Greene, Priyadip Ray
We propose multivariate nonstationary Gaussian processes for jointly modeling multiple clinical variables, where the key parameters, length-scales, standard deviations and the correlations between the observed output, are all time dependent.
no code implementations • 13 Oct 2019 • Rui Meng, Soper Braden, Jan Nygard, Mari Nygrad, Herbert Lee
In this paper, we propose a piece-wise stationary transition matrix to explain the heterogeneity in time.
no code implementations • 13 Oct 2019 • Rui Meng, Herbert Lee, Soper Braden, Priyadip Ray
An issue faced by SGP, especially in latent variable models, is the inefficient learning of the inducing inputs, which leads to poor model prediction.
1 code implementation • 9 Sep 2019 • Rui Meng, Xingdi Yuan, Tong Wang, Peter Brusilovsky, Adam Trischler, Daqing He
Recently, concatenating multiple keyphrases as a target sequence has been proposed as a new learning paradigm for keyphrase generation.
1 code implementation • EMNLP 2018 • Sanqiang Zhao, Rui Meng, Daqing He, Saptono Andi, Parmanto Bambang
Sentence simplification aims to reduce the complexity of a sentence while retaining its original meaning.
Ranked #3 on Text Simplification on ASSET
1 code implementation • ACL 2020 • Xingdi Yuan, Tong Wang, Rui Meng, Khushboo Thaker, Peter Brusilovsky, Daqing He, Adam Trischler
With both previous and new evaluation metrics, our model outperforms strong baselines on all datasets.
no code implementations • 16 May 2017 • Rui Meng, Hao Xin, Lei Chen, Yangqiu Song
In our work, we propose a system, called crowdsourced subjective knowledge acquisition (CoSKA), for subjective knowledge acquisition powered by crowdsourcing and existing KBs.
4 code implementations • ACL 2017 • Rui Meng, Sanqiang Zhao, Shuguang Han, Daqing He, Peter Brusilovsky, Yu Chi
Keyphrase provides highly-condensed information that can be effectively used for understanding, organizing and retrieving text content.