title: Protracted armed conflicts, invisible civilian Suffering and international law (II)

authors: Alvarez-Jimenez, Alberto

abstract: The United Nations Security Council receives communications from Israel and Palestine almost weekly, telling the story of their civilians’ indescribable affliction. Fifty were sent from August 2013 to July 2014 – the 65th and 66th years of the conflict.¹ In one letter after another, both states expressed not a single word of concern for the other’s civilians.

text: Protracted armed conflicts, invisible civilian Suffering and international law (II) The United Nations Security Council receives communications from Israel and Palestine almost weekly, telling the story of their civilians’ indescribable affliction. Fifty were sent from August 2013 to July 2014 – the 65th and 66th years of the conflict.¹ In one letter after another, both states expressed not a single word of concern for the other’s civilians.

year: 2018

title: Revisiting deep hybrid models for out-of-distribution detection

authors: Schlumbom, Paul-Ruben

subjects: computer science

abstract: Deep hybrid models (DHMs) for out-of-distribution (OOD) detection, jointly training a deep feature extractor with a classification head and a density estimation head based on a normalising flow, provide a conceptually appealing approach to visual OOD detection. The paper that introduced this approach reported 100% AuROC in experiments on two standard benchmarks, including one based on the CIFAR-10 data. As there are no implementations available, we set out to reproduce the approach by carefully filling in gaps in the description of the algorithm. Although we were unable to attain 100% OOD detection rates, and our results indicate that such performance is impossible on the CIFAR-10 benchmark, we achieved good OOD performance. We provide a detailed analysis of when the architecture fails and argue that it introduces an adversarial relationship between the classification component and the density estimator, rendering it highly sensitive to the balance of these two components and yielding a collapsed feature space without careful fine-tuning. Our implementation of DHMs is publicly available.

text: Revisiting deep hybrid models for out-of-distribution detection Deep hybrid models (DHMs) for out-of-distribution (OOD) detection, jointly training a deep feature extractor with a classification head and a density estimation head based on a normalising flow, provide a conceptually appealing approach to visual OOD detection. The paper that introduced this approach reported 100% AuROC in experiments on two standard benchmarks, including one based on the CIFAR-10 data. As there are no implementations available, we set out to reproduce the approach by carefully filling in gaps in the description of the algorithm. Although we were unable to attain 100% OOD detection rates, and our results indicate that such performance is impossible on the CIFAR-10 benchmark, we achieved good OOD performance. We provide a detailed analysis of when the architecture fails and argue that it introduces an adversarial relationship between the classification component and the density estimator, rendering it highly sensitive to the balance of these two components and yielding a collapsed feature space without careful fine-tuning. Our implementation of DHMs is publicly available.

year: 2025

title: What a difference a default setting makes

authors: Keegan, Te Taka Adrian Gregory

subjects: computer science

abstract: This paper examines the effect of the default interface language on the usage of a bilingual digital library. In 2005 the default interface language of a bilingual digital library was alternated on a monthly basis between Māori and English. A comprehensive transaction log analysis over this period reveals that not only did usage in a particular language increase when the default interface language was set to that language but that the way the interface was used, in both languages, was quite different depending on the default language.

text: What a difference a default setting makes This paper examines the effect of the default interface language on the usage of a bilingual digital library. In 2005 the default interface language of a bilingual digital library was alternated on a monthly basis between Māori and English. A comprehensive transaction log analysis over this period reveals that not only did usage in a particular language increase when the default interface language was set to that language but that the way the interface was used, in both languages, was quite different depending on the default language.

year: 2008