Výsledky vyhledávání

Report

Meta-Reasoning Improves Tool Use in Large Language Models

Autor: Alazraki, Lisa, Rei, Marek

External tools help large language models (LLMs) succeed at tasks where they would otherwise typically fail. In existing frameworks, LLMs learn tool use either by in-context demonstrations or via full model fine-tuning on annotated data. As these app

Externí odkaz: http://arxiv.org/abs/2411.04535

Zobrazit plný text záznamu

Report

Automatic Quantification of Serial PET/CT Images for Pediatric Hodgkin Lymphoma Patients Using a Longitudinally-Aware Segmentation Network

Autor: Tie, Xin, Shin, Muheon, Lee, Changhee, Perlman, Scott B., Huemann, Zachary, Weisman, Amy J., Castellino, Sharon M., Kelly, Kara M., McCarten, Kathleen M., Alazraki, Adina L., Hu, Junjie, Cho, Steve Y., Bradshaw, Tyler J.

$\textbf{Purpose}$: Automatic quantification of longitudinal changes in PET scans for lymphoma patients has proven challenging, as residual disease in interim-therapy scans is often subtle and difficult to detect. Our goal was to develop a longitudin

Externí odkaz: http://arxiv.org/abs/2404.08611

Zobrazit plný text záznamu

Report

A Multilingual Virtual Guide for Self-Attachment Technique

Autor: Law, Alicia Jiayun, Hu, Ruoyu, Alazraki, Lisa, Gopalan, Anandha, Polydorou, Neophytos, Edalat, Abbas

Publikováno v: 2022 IEEE 4th International Conference on Cognitive Machine Intelligence (CogMI)

In this work, we propose a computational framework that leverages existing out-of-language data to create a conversational agent for the delivery of Self-Attachment Technique (SAT) in Mandarin. Our framework does not require large-scale human transla

Externí odkaz: http://arxiv.org/abs/2310.18366

Zobrazit plný text záznamu

Report

From Words and Exercises to Wellness: Farsi Chatbot for Self-Attachment Technique

Autor: Elahimanesh, Sina, Salehi, Shayan, Movahed, Sara Zahedi, Alazraki, Lisa, Hu, Ruoyu, Edalat, Abbas

In the wake of the post-pandemic era, marked by social isolation and surging rates of depression and anxiety, conversational agents based on digital psychotherapy can play an influential role compared to traditional therapy sessions. In this work, we

Externí odkaz: http://arxiv.org/abs/2310.09362

Zobrazit plný text záznamu

Report

How (not) to ensemble LVLMs for VQA

Autor: Alazraki, Lisa, Castrejon, Lluis, Dehghani, Mostafa, Huot, Fantine, Uijlings, Jasper, Mensink, Thomas

This paper studies ensembling in the era of Large Vision-Language Models (LVLMs). Ensembling is a classical method to combine different models to get increased performance. In the recent work on Encyclopedic-VQA the authors examine a wide variety of

Externí odkaz: http://arxiv.org/abs/2310.06641

Zobrazit plný text záznamu

Report

An Empathetic AI Coach for Self-Attachment Therapy

Autor: Alazraki, Lisa, Ghachem, Ali, Polydorou, Neophytos, Khosmood, Foaad, Edalat, Abbas

Publikováno v: 2021 IEEE Third International Conference on Cognitive Machine Intelligence (CogMI), 2021, pp. 78-87

In this work, we present a new dataset and a computational strategy for a digital coach that aims to guide users in practicing the protocols of self-attachment therapy. Our framework augments a rule-based conversational agent with a deep-learning cla

Externí odkaz: http://arxiv.org/abs/2209.08316

Zobrazit plný text záznamu

Akademický článek

The Queen and the Sultana: Early Modern Female Circuits of Diplomacy and the Consumption of Gendered Luxury Items Between East and West

Autor: Mathilde Alazraki

Publikováno v: Revue Française de Civilisation Britannique, Vol 29, Iss 3 (2024)

Between 1593 and 1599, Queen Elizabeth I of England corresponded with the Ottoman Sultana Safiye (c. 1550-1606), favorite concubine of Sultan Murad III and mother of Sultan Mehmed III. Of this exchange, only the Sultana’s letters and mentions of th

Externí odkaz: https://doaj.org/article/b5baa15098054b7e84afefd6ccfd57b3