no code implementations • 26 Feb 2024 • Lingjun Zhao, Khanh Nguyen, Hal Daumé III
This paper addresses the challenge of leveraging imperfect language models to guide human decision-making in the context of a grounded navigation task.
1 code implementation • 20 Feb 2024 • Benjamin Plaut, Khanh Nguyen, Tu Trinh
Although large language models (LLMs) perform impressively on many tasks, overconfidence remains a problem.
no code implementations • 24 Jan 2024 • Alex Zhang, Khanh Nguyen, Jens Tuyls, Albert Lin, Karthik Narasimhan
Installing probabilistic world models into artificial agents opens an efficient channel for humans to communicate with and control these agents.
no code implementations • 15 Dec 2023 • Rubèn Tito, Khanh Nguyen, Marlon Tobaben, Raouf Kerkouche, Mohamed Ali Souibgui, Kangsoo Jung, Lei Kang, Ernest Valveny, Antti Honkela, Mario Fritz, Dimosthenis Karatzas
We employ a federated learning scheme, that reflects the real-life distribution of documents in different businesses, and we explore the use case where the ID of the invoice issuer is the sensitive information to be protected.
no code implementations • 23 Oct 2023 • Lingjun Zhao, Khanh Nguyen, Hal Daumé III
We investigate the problem of generating instructions to guide humans to navigate in simulated residential environments.
no code implementations • 13 Oct 2023 • Ruijie Zheng, Khanh Nguyen, Hal Daumé III, Furong Huang, Karthik Narasimhan
By equipping a learning agent with an abstract, dynamic language and an intrinsic motivation to learn with minimal communication effort, CEIL leads to emergence of a human-like pattern where the learner and the teacher communicate progressively efficiently by exchanging increasingly more abstract intentions.
no code implementations • 28 May 2023 • Khanh Nguyen
How do language models "think"?
no code implementations • 25 Feb 2023 • Zhiyi Ren, Chun-Cheng Hsu, Can Kocabalkanli, Khanh Nguyen, Iulian I. Iordachita, Serap Bastepe-Gray, Nathan Scott
Hand injuries from repetitive high-strain and physical overload can hamper or even end a musician's career.
no code implementations • 21 Dec 2022 • Lingjun Zhao, Khanh Nguyen, Hal Daumé III
Recent work studies the cognitive capabilities of language models through psychological tests designed for humans.
no code implementations • 21 Sep 2022 • Khanh Nguyen, Ali Furkan Biten, Andres Mafla, Lluis Gomez, Dimosthenis Karatzas
Particularly, a similar Wikimedia image can be used to illustrate different articles, and the produced caption needs to be adapted to a specific context, therefore allowing us to explore the limits of a model to adjust captions to different contextual information.
1 code implementation • 21 Sep 2022 • Nhat Le, Khanh Nguyen, Quang Tran, Erman Tjiputra, Bac Le, Anh Nguyen
In this paper, we propose a new uncertainty-aware label distribution learning method to improve the robustness of deep models against uncertainty and ambiguity.
Facial Expression Recognition Facial Expression Recognition (FER)
1 code implementation • 5 May 2022 • Khanh Nguyen, Huy Hoang Nguyen, Aleksei Tiulpin
CBIR with DNNs is generally solved by minimizing a ranking loss, such as Triplet loss (TL), computed on image representations extracted by a DNN from the original data.
no code implementations • 15 Feb 2022 • Harpreet Kaur, Khanh Nguyen, Pradeep Kumar
At atmospheric pressure, anisotropy decreases with increasing temperature but exhibits a maximum with temperature for pressure larger than 20 MPa.
1 code implementation • 7 Nov 2021 • Nhat Le, Khanh Nguyen, Anh Nguyen, Bac Le
Our network is designed to extract features from both facial and context regions independently, then learn them together using the attention module.
no code implementations • 14 Oct 2021 • Khanh Nguyen, Yonatan Bisk, Hal Daumé III
We show that the agent can take advantage of different types of information depending on the context, and analyze the benefits and challenges of learning the assistance-requesting policy when the assistant can recursively decompose tasks into subtasks.
1 code implementation • 13 Feb 2021 • Khanh Nguyen, Dipendra Misra, Robert Schapire, Miro Dudík, Patrick Shafto
We present a novel interactive learning protocol that enables training request-fulfilling agents by verbally describing their activities.
General Reinforcement Learning Grounded language learning +2
no code implementations • 14 Jun 2020 • Khanh Nguyen, Hal Daumé III
We formulate the problem of learning to imitate multiple, non-deterministic teachers with minimal interaction cost.
1 code implementation • 22 Mar 2020 • Thi Phuoc Hanh Nguyen, Zinan Cai, Khanh Nguyen, Sokuntheariddh Keth, Ningyuan Shen, Mira Park
This paper focuses on finding the most optimal pre-processing methods considering three common algorithms for image enhancement: Brightening, CLAHE and Retinex.
no code implementations • WS 2019 • Khanh Nguyen, Hal Daumé III
We construct Global Voices, a multilingual dataset for evaluating cross-lingual summarization methods.
1 code implementation • IJCNLP 2019 • Khanh Nguyen, Hal Daumé III
An agent solving tasks in a HANNA environment can leverage simulated human assistants, called ANNA (Automatic Natural Navigation Assistants), which, upon request, provide natural language and visual instructions to direct the agent towards the goals.
1 code implementation • CVPR 2019 • Khanh Nguyen, Debadeepta Dey, Chris Brockett, Bill Dolan
We present Vision-based Navigation with Language-based Assistance (VNLA), a grounded vision-language task where an agent with visual perception is guided via language to find objects in photorealistic indoor environments.
no code implementations • 15 Nov 2018 • Trung Le, Khanh Nguyen, Nhat Ho, Hung Bui, Dinh Phung
The underlying idea of deep domain adaptation is to bridge the gap between source and target domains in a joint space so that a supervised classifier trained on labeled source data can be nicely transferred to the target domain.
no code implementations • 19 Sep 2017 • Trung Le, Khanh Nguyen, Tu Dinh Nguyen, Dinh Phung
With this spirit, in this paper, we propose Analogical-based Bayesian Optimization that can maximize black-box function over a domain where only a similarity score can be defined.
no code implementations • WS 2017 • Amr Sharaf, Shi Feng, Khanh Nguyen, Kianté Brantley, Hal Daumé III
We describe the University of Maryland machine translation systems submitted to the WMT17 German-English Bandit Learning Task.
1 code implementation • EMNLP 2017 • Khanh Nguyen, Hal Daumé III, Jordan Boyd-Graber
Machine translation is a natural candidate problem for reinforcement learning from human feedback: users provide quick, dirty ratings on candidate translations to guide a system to improve.
no code implementations • 18 Jul 2016 • Khanh Nguyen
We present a novel view that unifies two frameworks that aim to solve sequential prediction problems: learning to search (L2S) and recurrent neural networks (RNN).
no code implementations • 22 Jun 2016 • Trung Le, Khanh Nguyen, Van Nguyen, Vu Nguyen, Dinh Phung
Acquiring labels are often costly, whereas unlabeled data are usually easy to obtain in modern machine learning applications.
no code implementations • EMNLP 2015 • Khanh Nguyen, Brendan O'Connor
Many models in natural language processing define probabilistic distributions over linguistic structures.