Tootfinder

Ana Tudor rolling into the comments with corrections and useful #CSS values context (trousers!):
https://css-tricks.com/headings-semantics-fluidity-and-styling-oh-my/#…

Headings: Semantics, Fluidity, and Styling — Oh My! | CSS-Tricks
A few links about headings that I've had stored under my top hat.

Operational methods in semantics
Roberto M. Amadio
https://arxiv.org/abs/2510.12295 https://arxiv.org/pdf/2510.12295

Operational methods in semantics
The focus of these lecture notes is on abstract models and basic ideas and results that relate to the operational semantics of programming languages largely conceived. The approach is to start with an abstract description of the computation steps of programs and then to build on top semantic equivalences, specification languages, and static analyses. While other approaches to the semantics of programming languages are possible, it appears that the operational one is particularly effective in th…

Leveraging Language Semantics for Collaborative Filtering with TextGCN and TextGCN-MLP: Zero-Shot vs In-Domain Performance
Andrei Chernov, Haroon Wahab, Oleg Novitskij
https://arxiv.org/abs/2510.12461 …

Leveraging Language Semantics for Collaborative Filtering with TextGCN and TextGCN-MLP: Zero-Shot vs In-Domain Performance
In recent years, various approaches have been proposed to leverage large language models (LLMs) for incorporating textual information about items into recommender systems. Existing methods primarily focus on either fine-tuning LLMs to generate recommendations or integrating LLM-based embeddings into downstream models. In this work, we follow the latter direction and propose \textbf{TextGCN}, which applies parameter-free graph convolution layers directly over LLM-based item-title embeddings, ins…

International postdocs: Come to Bochum for a two-week stay to plan a research project and learn how to apply for funding for it in Germany.
I'm available as a host for any topic related to my research interests: digital forensic linguistics, experimental semantics/pragmatics, emojis, (computational analyses of) harmful language, metaphors, discourse, etc.
https://www.research-academy-ruhr.de/programm/researchexplorer/

Oh no, #Intel platform detection isn't that easy.
There is no simple field like platform ID or something in #IFD to determine it.
Also, IFD fields have changes semantics a bit over time.
So #coreboot

coreboot/util/ifdtool/ifdtool.c at 19feafc018f1b0f5184edd6bf4b4b068ef190dab · coreboot/coreboot
Read-only mirror of https://review.coreboot.org/coreboot.git. Synced every hour. We don't handle Pull Requests. - coreboot/coreboot

KoALA: KL-L0 Adversarial Detector via Label Agreement
Siqi Li, Yasser Shoukry
https://arxiv.org/abs/2510.12752 https://arxiv.org/pdf/2510.12752

KoALA: KL-L0 Adversarial Detector via Label Agreement
Deep neural networks are highly susceptible to adversarial attacks, which pose significant risks to security- and safety-critical applications. We present KoALA (KL-L0 Adversarial detection via Label Agreement), a novel, semantics-free adversarial detector that requires no architectural changes or adversarial retraining. KoALA operates on a simple principle: it detects an adversarial attack when class predictions from two complementary similarity metrics disagree. These metrics-KL divergence an…

Crosslisted article(s) found for cs.LO. https://arxiv.org/list/cs.LO/new
[1/1]:
- Operational methods in semantics
Roberto M. Amadio
https://

Advancing End-to-End Pixel Space Generative Modeling via Self-supervised Pre-training
Jiachen Lei, Keli Liu, Julius Berner, Haiming Yu, Hongkai Zheng, Jiahong Wu, Xiangxiang Chu
https://arxiv.org/abs/2510.12586

Advancing End-to-End Pixel Space Generative Modeling via Self-supervised Pre-training
Pixel-space generative models are often more difficult to train and generally underperform compared to their latent-space counterparts, leaving a persistent performance and efficiency gap. In this paper, we introduce a novel two-stage training framework that closes this gap for pixel-space diffusion and consistency models. In the first stage, we pre-train encoders to capture meaningful semantics from clean images while aligning them with points along the same deterministic sampling trajectory, …

PRoH: Dynamic Planning and Reasoning over Knowledge Hypergraphs for Retrieval-Augmented Generation
Xiangjun Zai, Xingyu Tan, Xiaoyang Wang, Qing Liu, Xiwei Xu, Wenjie Zhang
https://arxiv.org/abs/2510.12434

PRoH: Dynamic Planning and Reasoning over Knowledge Hypergraphs for Retrieval-Augmented Generation
Knowledge Hypergraphs (KHs) have recently emerged as a knowledge representation for retrieval-augmented generation (RAG), offering a paradigm to model multi-entity relations into a structured form. However, existing KH-based RAG methods suffer from three major limitations: static retrieval planning, non-adaptive retrieval execution, and superficial use of KH structure and semantics, which constrain their ability to perform effective multi-hop question answering. To overcome these limitations, w…

Can Representation Gaps Be the Key to Enhancing Robustness in Graph-Text Alignment?
Heng Zhang, Tianyi Zhang, Yuling Shi, Xiaodong Gu, Yaomin Shen, Zijian Zhang, Yilei Yuan, Hao Zhang, Jin Huang
https://arxiv.org/abs/2510.12087

Can Representation Gaps Be the Key to Enhancing Robustness in Graph-Text Alignment?
Representation learning on text-attributed graphs (TAGs) integrates structural connectivity with rich textual semantics, enabling applications in diverse domains. Current methods largely rely on contrastive learning to maximize cross-modal similarity, assuming tighter coupling between graph and text representations improves transfer performance. However, our empirical analysis reveals that both natural gap expansion and forced gap reduction result in performance degradation by disrupting pre-tr…

Data or Language Supervision: What Makes CLIP Better than DINO?
Yiming Liu, Yuhui Zhang, Dhruba Ghosh, Ludwig Schmidt, Serena Yeung-Levy
https://arxiv.org/abs/2510.11835 https:/…

Data or Language Supervision: What Makes CLIP Better than DINO?
CLIP outperforms self-supervised models like DINO as vision encoders for vision-language models (VLMs), but it remains unclear whether this advantage stems from CLIP's language supervision or its much larger training data. To disentangle these factors, we pre-train CLIP and DINO under controlled settings -- using the same architecture, dataset, and training configuration -- achieving similar ImageNet accuracy. Embedding analysis shows that CLIP captures high-level semantics (e.g., object catego…

We are happy to welcome @… from RWTH in today's #nfdicore playground talking about "Bridging the Gap from Biomedical to Domain-Agnostic Semantics".
Besides others, he is demonstrating that our

I wasn't surprised to see Rob Sanderson quoted in this, because rich vs aligned semantics - specifically , wanting both at the same time - is *such* a cultural heritage data interoperability problem #MuseTech
From: @…

Pieter Colpaert (@pietercolpaert@mastodon.social)
Attached: 2 images There’s a tension between being semantically rich (using your own terms and definitions), and being semantically aligned, in which you try to reuse terms from other vocabularies. I think we need a new concept: eventual #interoperability. I propose to start rich with your own vocabularies, and only make alignments when there’s a concrete reason for building those. https://pietercolpaert.be/interoperability/2026/01/08/eventual-interoperability #knowledgegraphs #apis #li…

A cool open source UI component library, but a lot of them I looked at don't have good semantics or accessibility compliance. #webdevelopment

OpenAI and Perplexity, armed with significant AI capabilities, have targeted the shopping domain. And have run into many problems around data access and semantics.
This raises three thoughts:
First, companies which are bullish about AI “changing everything”, are stumbling in maybe the most traditional, mundane domain: shopping. This doesn’t inspire confidence in their technology.
1/5
#ai

A cool open source UI component library, but a lot of them I looked at don't have good semantics or accessibility compliance. #webdevelopment

Brain-aligning of semantic vectors improves neural decoding of visual stimuli #BCI

Syntax is not Semantics
Language is not the same as intelligence.
The entire AI bubble is built on ignoring that.
https://www.theverge.com/ai-artificial-intelligence/827820/large-language-models-ai-intellige…

Large language mistake
Neuroscience indicates language is distinct from thought, raising questions about whether AI large language models are a viable path to artificial general intelligence.

Revised comment on the paper titled "The Origin of Quantum Mechanical Statistics: Insights from Research on Human Language
Miko{\l}aj Sienicki, Krzysztof Sienicki
https://arxiv.org/abs/2512.07881 https://arxiv.org/pdf/2512.07881 https://arxiv.org/html/2512.07881
arXiv:2512.07881v1 Announce Type: new
Abstract: This short note comments on \citet{Aerts2024Origin}, which proposes that ranked word frequencies in texts should be read through the lens of Bose--Einstein (BE) statistics and even used to illuminate the origin of quantum statistics in physics. The core message here is modest: the paper offers an interesting analogy and an eye-catching fit, but several key steps mix physical claims with definitions and curve-fitting choices. We highlight three such points: (i) a normalization issue that is presented as "bosonic enhancement", (ii) an identification of rank with energy that makes the BE fit only weakly diagnostic of an underlying mechanism, and (iii) a baseline comparison that is too weak to support an ontological conclusion. We also briefly flag a few additional concerns (interpretation drift, parameter semantics, and reproducibility).
toXiv_bot_toot

#IsraelIsATerroristState

Historians: Quibbling Over Exact Definition Of Concentration Camp Sign Of Healthy Society
NEW HAVEN, CT—Calling such concern for linguistic precision a clear indicator of a thriving country, a panel of historians from Yale University issued a statement Thursday announcing that quibbling over the exact definition of a concentration camp was a sign of a healthy society. “Studies of the past tell us that nitpicking the particular semantics […]

Scott helpfully reminds us of the differences between technical purity, semantics, and what actually matters to users in the context of — yes, really — paragraphs:
https://www.scottohara.me/blog/2024/08/29/paragraphs.html

🚨 Yesterday, I received official notification that our #emoji project EmDiCom is being funded for another three years! 🥳
I'm looking forward to a lot more 🤩 emoji research 🤩 together with Patrick Grosz and Lea Fricke! #linguistics #dfg #vicom @… https://vicom.info/projects/semantics-and-pragmatics-of-emojis-in-digital-communication/