Tootfinder

Netflix will buy some of Warner Bros. Discovery’s most valuable media portfolio for nearly $83 billion in a cash-stock deal, the two companies said Friday.

The streaming giant will acquire some of WBD’s most valuable media properties,
including its film and TV studio,
HBO and HBO Max.
WBD’s cable networks, including the news giant CNN, are to be spun off in advance of the deal.
-- That plan was announced in June.
Two other companies
— Comcast and Pa…

Netflix to buy Warner Bros. Discovery in $83 billion cash-stock deal
Largest streaming network says it will purchase Warner Bros.’ studios and streaming assets after winning a bidding war with Comcast and Paramount. 

Repository-Aware File Path Retrieval via Fine-Tuned LLMs
Vasudha Yanuganti, Ishaan Puri, Swapnil Chhatre, Mantinder Singh, Ashok Jallepalli, Hritvik Shrivastava, Pradeep Kumar Sharma
https://arxiv.org/abs/2510.08850

Repository-Aware File Path Retrieval via Fine-Tuned LLMs
Modern codebases make it hard for developers and AI coding assistants to find the right source files when answering questions like "How does this feature work?" or "Where was the bug introduced?" Traditional code search (keyword or IR based) often misses semantic context and cross file links, while large language models (LLMs) understand natural language but lack repository specific detail. We present a method for file path retrieval that fine tunes a strong LLM (Qwen3-8B) with QLoRA and Unslot…

Ich krebs seit Ewigkeiten an "Termination Shock" von Neal Stephenson rum. Ich dachte, vielleicht nimmt es irgendwann Fahrt auf, aber auch bei 60℅ verliert es sich noch in x langweiligen Details.
Wahrscheinlich les ich es nur zu Ende, um guten Gewissens 1 Sternchen bei Calibre vergeben zu können. Vielleicht ja noch dieses Jahr. 😴
Beim andere Buch, wo er ewig von der Pferdefarm oder so erzählte, war der frühe Abbruch wohl die bessere Entscheidung. Hasse aber Abbruch.

Alright, late night dev session has been running for a while.
Someone mentioned, "You should record or stream this"
Fine.... why not. So we're live now.
https://tube.bitsnbytes.dev/w/h8qnYxnHPoqkudqz3U9DsQ
And only on Peertube because I'm …

Protoplanetary disc population synthesis I. Constraining disc parameters to reproduce disc observations
Jose L. Gomez, Octavio M. Guilera, Marcelo M. Miller Bertolami, Elisa Castro-Mart\'inez, Mar\'ia Paula Ronco
https://arxiv.org/abs/2510.06978

Protoplanetary disc population synthesis I. Constraining disc parameters to reproduce disc observations
Context. Protoplanetary discs are the birthplaces of planets. Recent studies highlight the role of stellar mass sampling in determining disc lifetimes from the observed fraction of stars with discs. Low-mass stars tend to host longer-lived discs, allowing planet formation via solid accretion. Observations also reveal a strong correlation between stellar (and substellar) mass and accretion rate, typically following $\dot{M}\propto M_\star^2$. Aims. We aim to identify the optimal parameters of a …

LAPIS: A Performance Portable, High Productivity Compiler Framework
Brian Kelley, Sivasankaran Rajamanickam
https://arxiv.org/abs/2509.25605 https://arxiv.…

LAPIS: A Performance Portable, High Productivity Compiler Framework
Portability, performance, and productivity are three critical dimensions for evaluating a programming model or compiler infrastructure. Several modern programming models for computational science focus on performance and portability. On the other end, several machine learning focused programming models focus on portability and productivity. A clear solution that is strong in all three dimensions has yet to emerge. A second related problem arises when use cases from computational science converg…

Autonomous interpretation of atomistic scattering data
Andy S. Anker, John L. A. Gardner, Louise A. M. Rosset, Andrew L. Goodwin, Volker L. Deringer
https://arxiv.org/abs/2510.05938

Autonomous interpretation of atomistic scattering data
Materials with bespoke properties have long been identified by computational searches, and their experimental realisation is now coming within reach through autonomous laboratories. Scattering experiments are central to verifying the atomic structures of autonomously synthesised materials. Yet, interpreting these measurements typically requires user expertise and manual processing, or machine learning (ML) models trained on predefined datasets, limiting fully autonomous materials discovery. Her…

Si vous consommez du lait de vache, je vous supplie de vous informer sur sa production en regardant cette vidéo : https://peertube.stream/w/ctjgXXS6xUf3BgK3smDvbj
Pas d'images insoutenables au global SAUF un viol de taureau et on voit le gode (oui...) venir plusieurs secondes…

M3Retrieve: Benchmarking Multimodal Retrieval for Medicine
Arkadeep Acharya, Akash Ghosh, Pradeepika Verma, Kitsuchart Pasupa, Sriparna Saha, Priti Singh
https://arxiv.org/abs/2510.06888

M3Retrieve: Benchmarking Multimodal Retrieval for Medicine
With the increasing use of RetrievalAugmented Generation (RAG), strong retrieval models have become more important than ever. In healthcare, multimodal retrieval models that combine information from both text and images offer major advantages for many downstream tasks such as question answering, cross-modal retrieval, and multimodal summarization, since medical data often includes both formats. However, there is currently no standard benchmark to evaluate how well these models perform in medica…

A Flexible Programmable Pipeline Parallelism Framework for Efficient DNN Training
Lijuan Jiang, Xingjian Qian, Zhenxiang Ma, Zan Zong, Hengjie Li, Chao Yang, Jidong Zhai
https://arxiv.org/abs/2510.05112

A Flexible Programmable Pipeline Parallelism Framework for Efficient DNN Training
Pipeline parallelism is an essential distributed parallelism method. Increasingly complex and diverse DNN models necessitate meticulously customized pipeline schedules for performance. However, existing practices typically rely on predefined schedules, each with strengths, but fail to adapt automatically to the emerging model architectures. Exploring novel high-efficiency schedules is daunting due to the enormous and varying schedule space. Besides, manually implementing schedules can be challe…