1 code implementation • 21 Mar 2024 • Longzheng Wang, Xiaohan Xu, Lei Zhang, Jiarui Lu, Yongxiu Xu, Hongbo Xu, Minghao Tang, Chuang Zhang
Automatic detection of multimodal misinformation has gained a widespread attention recently.
no code implementations • 16 Feb 2024 • Jiarui Lu, Zuobai Zhang, Bozitao Zhong, Chence Shi, Jian Tang
The protein dynamics are common and important for their biological functions and properties, the study of which usually involves time-consuming molecular dynamics (MD) simulations in silico.
no code implementations • 10 Feb 2024 • Zuobai Zhang, Jiarui Lu, Vijil Chenthamarakshan, Aurélie Lozano, Payel Das, Jian Tang
Protein function annotation is an important yet challenging task in biology.
1 code implementation • 7 Feb 2024 • Zuobai Zhang, Jiarui Lu, Vijil Chenthamarakshan, Aurélie Lozano, Payel Das, Jian Tang
To address this issue, we introduce the integration of remote homology detection to distill structural information into protein language models without requiring explicit protein structures as input.
no code implementations • 1 Feb 2024 • YIlun Zhu, Joel Ruben Antony Moniz, Shruti Bhargava, Jiarui Lu, Dhivya Piraviperumal, Site Li, Yuan Zhang, Hong Yu, Bo-Hsiang Tseng
Understanding context is key to understanding human language, an ability which Large Language Models (LLMs) have been increasingly seen to demonstrate to an impressive extent.
1 code implementation • 29 Jan 2024 • Shengchao Liu, Chengpeng Wang, Jiarui Lu, Weili Nie, Hanchen Wang, Zhuoxinran Li, Bolei Zhou, Jian Tang
Deep generative models (DGMs) have been widely developed for graph data.
no code implementations • 3 Nov 2023 • Halim Cagri Ates, Shruti Bhargava, Site Li, Jiarui Lu, Siddhardha Maddula, Joel Ruben Antony Moniz, Anil Kumar Nalamalapu, Roman Hoang Nguyen, Melis Ozyildirim, Alkesh Patel, Dhivya Piraviperumal, Vincent Renkens, Ankit Samal, Thy Tran, Bo-Hsiang Tseng, Hong Yu, Yuan Zhang, Rong Zou
Successfully handling context is essential for any dialog understanding task.
no code implementations • 25 Oct 2023 • Leon Liyang Zhang, Jiarui Lu, Joel Ruben Antony Moniz, Aditya Kulkarni, Dhivya Piraviperumal, Tien Dung Tran, Nicholas Tzou, Hong Yu
In the context of a voice assistant system, steering refers to the phenomenon in which a user issues a follow-up command attempting to direct or clarify a previous turn.
1 code implementation • 6 Oct 2023 • Dominique Beaini, Shenyang Huang, Joao Alex Cunha, Zhiyi Li, Gabriela Moisescu-Pareja, Oleksandr Dymov, Samuel Maddrell-Mander, Callum McLean, Frederik Wenkel, Luis Müller, Jama Hussein Mohamud, Ali Parviz, Michael Craig, Michał Koziarski, Jiarui Lu, Zhaocheng Zhu, Cristian Gabellini, Kerstin Klaser, Josef Dean, Cas Wognum, Maciej Sypetkowski, Guillaume Rabusseau, Reihaneh Rabbany, Jian Tang, Christopher Morris, Ioannis Koutis, Mirco Ravanelli, Guy Wolf, Prudencio Tossou, Hadrien Mary, Therence Bois, Andrew Fitzgibbon, Błażej Banaszewski, Chad Martin, Dominic Masters
Recently, pre-trained foundation models have enabled significant advancements in multiple fields.
1 code implementation • 2 Oct 2023 • Yizhe Zhang, Jiarui Lu, Navdeep Jaitly
In this paper, we offer a surrogate problem which assesses an LLMs's capability to deduce an entity unknown to itself, but revealed to a judge, by asking the judge a series of queries.
no code implementations • 7 Aug 2023 • Cecilia Aas, Hisham Abdelsalam, Irina Belousova, Shruti Bhargava, Jianpeng Cheng, Robert Daland, Joris Driesen, Federico Flego, Tristan Guigue, Anders Johannsen, Partha Lal, Jiarui Lu, Joel Ruben Antony Moniz, Nathan Perkins, Dhivya Piraviperumal, Stephen Pulman, Diarmuid Ó Séaghdha, David Q. Sun, John Torr, Marco Del Vecchio, Jay Wacker, Jason D. Williams, Hong Yu
It has recently become feasible to run personal digital assistants on phones and other personal devices.
1 code implementation • 5 Jun 2023 • Jiarui Lu, Bozitao Zhong, Zuobai Zhang, Jian Tang
The dynamic nature of proteins is crucial for determining their biological functions and properties, for which Monte Carlo (MC) and molecular dynamics (MD) simulations stand as predominant tools to study such phenomena.
no code implementations • 2 Jun 2023 • Jiarui Lu, Bo-Hsiang Tseng, Joel Ruben Antony Moniz, Site Li, Xueyun Zhu, Hong Yu, Murat Akbacak
Providing voice assistants the ability to navigate multi-turn conversations is a challenging problem.
1 code implementation • 9 Feb 2023 • Shengchao Liu, Yanjing Li, Zhuoxinran Li, Anthony Gitter, Yutao Zhu, Jiarui Lu, Zhao Xu, Weili Nie, Arvind Ramanathan, Chaowei Xiao, Jian Tang, Hongyu Guo, Anima Anandkumar
Current AI-assisted protein design mainly utilizes protein sequential and structural information.
1 code implementation • 21 Dec 2022 • Shengchao Liu, Weili Nie, Chengpeng Wang, Jiarui Lu, Zhuoran Qiao, Ling Liu, Jian Tang, Chaowei Xiao, Anima Anandkumar
Here we present a multi-modal molecule structure-text model, MoleculeSTM, by jointly learning molecules' chemical structures and textual descriptions via a contrastive learning strategy.
no code implementations • 17 Oct 2022 • Chence Shi, Chuanrui Wang, Jiarui Lu, Bozitao Zhong, Jian Tang
Proteins are macromolecules that perform essential functions in all living organisms.
1 code implementation • 5 Jun 2022 • Minghao Xu, Zuobai Zhang, Jiarui Lu, Zhaocheng Zhu, Yangtian Zhang, Chang Ma, Runcheng Liu, Jian Tang
However, there is a lack of a standard benchmark to evaluate the performance of different methods, which hinders the progress of deep learning in this field.
1 code implementation • 16 Feb 2022 • Zhaocheng Zhu, Chence Shi, Zuobai Zhang, Shengchao Liu, Minghao Xu, Xinyu Yuan, Yangtian Zhang, Junkun Chen, Huiyu Cai, Jiarui Lu, Chang Ma, Runcheng Liu, Louis-Pascal Xhonneux, Meng Qu, Jian Tang
However, lacking domain knowledge (e. g., which tasks to work on), standard benchmarks and data preprocessing pipelines are the main obstacles for machine learning researchers to work in this domain.
1 code implementation • NAACL 2021 • Bo-Hsiang Tseng, Shruti Bhargava, Jiarui Lu, Joel Ruben Antony Moniz, Dhivya Piraviperumal, Lin Li, Hong Yu
In this work, we propose a novel joint learning framework of modeling coreference resolution and query rewriting for complex, multi-turn dialogue understanding.
no code implementations • 26 Nov 2019 • Abhishek Chakrabortty, Jiarui Lu, T. Tony Cai, Hongzhe Li
Under mild tail assumptions and arbitrarily chosen (working) models for the propensity score (PS) and the outcome regression (OR) estimators, satisfying only some high-level conditions, we establish finite sample performance bounds for the DDR estimator showing its (optimal) $L_2$ error rate to be $\sqrt{s (\log d)/ n}$ when both models are correct, and its consistency and DR properties when only one of them is correct.