Publications related to ISR-LLM: Iterative Self-Refined Large Language Model for Long-Horizon Sequential Task Planning

Related publications (8)

From Preprocessing to Evaluation: The Role of External Knowledge in Advancing Language Models and Machine Translation

Machine translation (MT) systems and language models (LMs) have demonstrated impressive performance in recent years, driven by advances in architecture, algorithms, and the scaling of parameters and training data. Despite the ability of these models to int ...

EPFL2025

Scaling the Modalities in Multimodal Foundation Models

Oguzhan Fatih Kar

Having a single neural network to handle a wide and varied range of tasks and modalities has been a long-standing goal. Such a model brings notable advantages, such as test-time computational efficiency, modality fusion, and reduced model size. Our goal in ...

EPFL2025

Programming Light Propagation for Efficient Artificial Intelligence

Ilker Oguz

Contemporary artificial intelligence (AI) models' exponentially growing complexity translates to their expanding skill sets. They can create language or image content mimicking human creativity and understanding, becoming indispensable tools in education, ...

EPFL2025

Optical Processors for AI Computing and Networking

Mustafa Yildirim

Computing has long been central to technological advancements, where each leap in compute power has catalyzed applications once thought impossible, such as smartphones. Recently, the exponential growth in the compute demand of artificial intelligence (AI) ...

EPFL2025

Advancing Phonology-Based Sign Language Assessment: From Learner to Machine-Generated Videos

Neha Tarigopula

Sign languages are rich visual languages that use both manual features like handshape, movement, and location and non-manual features such as facial expressions, head movements, and body posture to convey information. Sign language learning technologies ha ...

EPFL2025

GigaPose: Fast and Robust Novel Object Pose Estimation via One Correspondence

Mathieu Salzmann

We present GigaPose, a fast, robust, and accurate method for CAD-based novel object pose estimation in RGB images. GigaPose first leverages discriminative "templates", rendered images of the CAD models, to recover the out-of-plane rotation and then uses pa ...

IEEE2024

Enhancing Hand and Object Detection for Monitoring Patients with Upper-Limb Impairment: A Study on the Impact of Input Size in Foundation Models

Kamiar Aminian, Yasaman Izadmehr

The choice of input image size can have a significant impact on the performance of the state-of-the-art algorithms. We can always customize the algorithms by training and fine-tuning them on our datasets, but it is time consuming. Nowadays there is a trend ...

Institute of Electrical and Electronics Engineers Inc.2023

Automated Taxonomy Induction and its Applications

Amit Gupta

Machine-readable semantic knowledge in the form of taxonomies (i.e., a collection of is-a edges) has proved to be beneficial in an array of NLP tasks including inference, textual entailment, question answering and information extraction. Such widespread ut ...

EPFL2017