Tootfinder

Going to #NoKings Saturday? Try to recruit the newly radicalizing to defunding the police, to defending all in our communities facing displacement—immigrant, queer, unhoused, unable to pay rent—in short, to fighting local fascisms, so we can better fight national fascism, at ICE centers

Immigration Detention Map — Freedom for Immigrants
Map of U.S. Immigration Detention

Archetypes & Myths: ERAH Graduate Conference 2025
https://ift.tt/mlNHySQ
updated: Tuesday, June 10, 2025 - 1:57pmfull name / name of organization: Engaging Research Across…
via Input 4 RELCFP

This https://arxiv.org/abs/2505.18675 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCV_…

Can MLLMs Guide Me Home? A Benchmark Study on Fine-Grained Visual Reasoning from Transit Maps
Multimodal large language models (MLLMs) have recently achieved significant progress in visual tasks, including semantic scene understanding and text-image alignment, with reasoning variants enhancing performance on complex tasks involving mathematics and logic. However, their capacity for reasoning tasks involving fine-grained visual understanding remains insufficiently evaluated. To address this gap, we introduce ReasonMap, a benchmark designed to assess the fine-grained visual understanding …

ICE raids appear to be giving criminals license to do whatever the f--- they want. But silly me... this has always been about Trump's racism, not law & order.
All you Trump voters are responsible for the misery of millions.
Original post: https://bsky.app/profile/did:plc:6m7rb…

Cannot even find where i read it but because i first read about an alleged breach of data from the Israeli government held by the Iranian government (on Mossad agents, recordings from secret cameras installed by Netanyahu to get compromising info on potential rivals, and much more, apparently all from a 2024 hack or leak) i have not been able to shake the twisted thought that the war Israel has now started against Iran is the new worst ever fallout for bad information security.

This https://arxiv.org/abs/2505.16652 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCV_…

Seeing Far and Clearly: Mitigating Hallucinations in MLLMs with Attention Causal Decoding
Recent advancements in multimodal large language models (MLLMs) have significantly improved performance in visual question answering. However, they often suffer from hallucinations. In this work, hallucinations are categorized into two main types: initial hallucinations and snowball hallucinations. We argue that adequate contextual information can be extracted directly from the token interaction process. Inspired by causal inference in the decoding strategy, we propose to leverage causal masks …

#Hamburg-Bubble: Falls ihr schon immer mal auf einem Segel-Frachtschiff helfen wolltet, hier entlang: https://t2d8ee1b3.emailsys1a.net/mailing/143/837…

#Hamburg-Bubble: Falls ihr schon immer mal auf einem Segel-Frachtschiff helfen wolltet, hier entlang: https://t2d8ee1b3.emailsys1a.net/mailing/143/837…

This https://arxiv.org/abs/2505.19028 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCV_…

InfoChartQA: A Benchmark for Multimodal Question Answering on Infographic Charts
Understanding infographic charts with design-driven visual elements (e.g., pictograms, icons) requires both visual recognition and reasoning, posing challenges for multimodal large language models (MLLMs). However, existing visual-question answering benchmarks fall short in evaluating these capabilities of MLLMs due to the lack of paired plain charts and visual-element-based questions. To bridge this gap, we introduce InfoChartQA, a benchmark for evaluating MLLMs on infographic chart understand…

that last boost was already almost two weeks old
Israel is committing genocide by starvation.