Tootfinder

Counting Answer Sets of Disjunctive Answer Set Programs
Mohimenul Kabir, Supratik Chakraborty, Kuldeep S Meel
https://arxiv.org/abs/2507.11655 https://

Counting Answer Sets of Disjunctive Answer Set Programs
Answer Set Programming (ASP) provides a powerful declarative paradigm for knowledge representation and reasoning. Recently, counting answer sets has emerged as an important computational problem with applications in probabilistic reasoning, network reliability analysis, and other domains. This has motivated significant research into designing efficient ASP counters. While substantial progress has been made for normal logic programs, the development of practical counters for disjunctive logic pr…

Chameleon: A Surface-Anchored Smartphone AR Prototype with Visually Blended Mobile Display
Seungwon Yang, Suwon Yoon, Jeongwon Choi, Inseok Hwang
https://arxiv.org/abs/2509.14643

Chameleon: A Surface-Anchored Smartphone AR Prototype with Visually Blended Mobile Display
Augmented reality (AR) is often realized through head-mounted displays, offering immersive but egocentric experiences. While smartphone-based AR is more accessible, it remains limited to handheld, single-user interaction. We introduce Chameleon, a prototype AR system that transforms smartphones into surface-anchored displays for co-located use. When placed flat, the phone creates a transparency illusion and anchors digital content visible to multiple users. Chameleon supports natural reposition…

"In theory, AI model makers could eliminate hallucinations by using a dataset that contains no errors."
I think someone has fundamentally misunderstood the technology. Developing a model using a 100% correct training dataset does not mean that the resulting AI will be able to correctly answer questions that were not in the training data.
Over-fitting is a thing.

OpenAI says models are programmed to make stuff up instead of admitting ignorance
: Even a wrong answer is right some of the time

In Sabzevar for the second consecutive night, angry residents held demonstrations.
The protest began at Farmandari Square and Abouzar Street, and protesters blocked Bahonar Street.
Women were at the forefront of the rally, chanting slogans such as:
“Don’t be afraid, don’t be afraid, we’re all in this together,”
“Water, electricity, and life are our basic rights,”
and “We don’t want incompetent officials.”

Iran - Sabzevar: Second Night of Protests Against Water and Power Outages - NCRI
Maryam Rajavi: Like so many of Iran’s resources, the country’s water supplies have not been spared from the plunder and corruption of the clerical regime.

Cin\'{e}aste: A Fine-grained Contextual Movie Question Answering Benchmark
Nisarg A. Shah, Amir Ziai, Chaitanya Ekanadham, Vishal M. Patel
https://arxiv.org/abs/2509.14227 h…

Cinéaste: A Fine-grained Contextual Movie Question Answering Benchmark
While recent advancements in vision-language models have improved video understanding, diagnosing their capacity for deep, narrative comprehension remains a challenge. Existing benchmarks often test short-clip recognition or use template-based questions, leaving a critical gap in evaluating fine-grained reasoning over long-form narrative content. To address these gaps, we introduce $\mathsf{Cin\acute{e}aste}$, a comprehensive benchmark for long-form movie understanding. Our dataset comprises 3,…

I just got sucked into the anachronism of the mention of an 'electric car' in a song about an 1890 bar fight and eventually found this page which has the best explanation:
https://territorialimperatives.com/2013/12/01/duncan-and-bradys-electri…

Duncan and Brady’s Electric Car
The album Classic African-American Ballads, from Smithsonian Folkways, contains a track entitled “Duncan and Brady” by the late Dave Van Ronk, whose story is told in the new film Inside…

ExpliCIT-QA: Explainable Code-Based Image Table Question Answering
Maximiliano Hormaz\'abal Lagos, \'Alvaro Bueno S\'aez, Pedro Alonso Doval, Jorge Alcalde Vesteiro, H\'ector Cerezo-Costas
https://arxiv.org/abs/2507.11694

ExpliCIT-QA: Explainable Code-Based Image Table Question Answering
We present ExpliCIT-QA, a system that extends our previous MRT approach for tabular question answering into a multimodal pipeline capable of handling complex table images and providing explainable answers. ExpliCIT-QA follows a modular design, consisting of: (1) Multimodal Table Understanding, which uses a Chain-of-Thought approach to extract and transform content from table images; (2) Language-based Reasoning, where a step-by-step explanation in natural language is generated to solve the prob…

Language learning has been part of me since high school. I'm solid in 2 non-English languages, crappy but survivable in 2 others. I've played with & started learning others many times.
I'm real busy rn, but language learning could be a fun thing to do for myself & make me feel like I'm still me.
But I'm stumped about my language picks. I learnt the obvious European languages in school; later tried key Asian languages. What do I want to do now?
African languages? I won't be getting a chance to use them much in Aus, & I'm unlikely to get to a stage where I can read literature.
I tried Slovenian/Slovene on a whim & really love it, but I'll never go there. Is the practical but unfun answer grind out more kanji/hanzi? Or is whimsically learning a language spoken by only 2.5 million people reasonable? I will continue struggling through with Ukrainian, 'cause I think it's important.
#LanguageLearning

Checkmate: interpretable and explainable RSVQA is the endgame
Lucrezia Tosato, Christel Tartini Chappuis, Syrielle Montariol, Flora Weissgerber, Sylvain Lobry, Devis Tuia
https://arxiv.org/abs/2508.13086

Checkmate: interpretable and explainable RSVQA is the endgame
Remote Sensing Visual Question Answering (RSVQA) presents unique challenges in ensuring that model decisions are both understandable and grounded in visual content. Current models often suffer from a lack of interpretability and explainability, as well as from biases in dataset distributions that lead to shortcut learning. In this work, we tackle these issues by introducing a novel RSVQA dataset, Chessboard, designed to minimize biases through 3'123'253 questions and a balanced answer distribut…